clinical presentation of diabetes type 1

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Pathophysiology and Clinical Presentation

Pathophysiology:

Type 1 Diabetes Mellitus is a syndrome characterized by hyperglycemia and insulin deficiency resulting from the loss of beta cells in pancreatic islets (Mapes & Faulds, 2014). Nonimmune (type 1B diabetes), occurs secondary to other diseases and is much less common than autoimmune (type 1A). The destruction of beta cells in Type 1A diabetes results from the interaction of both genetic and environmental factors. Although the genetic susceptibility is not well understood, type 1 diabetes is most strongly associated with major histocompatibility complex (MHC), specifically histocompatibility leukocyte antigen (HLA) class II alleles (HLA-DQ and HLA-DR) (McCance & Heuther, 2014). Type 1 diabetes is less hereditary than type 2 but 7-13% of patients also have a first degree relative with type 1 diabetes (Mapes & Faulds, 2014). Environmental factors include viral infections (especially enteroviruses), exposure to infectious microorganisms (such as  Helicobacter pylori ), exposure to cow’s milk proteins and a lack of vitamin D (McCance & Heuther, 2014).

The destruction of insulin-producing beta cells in the pancreas starts with the formation of autoantigens. These autoantigens are ingested by antigen-presenting cells which activate T helper 1 (Th1) and T helper 2 (Th2) lmphocytes. Activated Th1 lymphocytes secrete interluekin-2 (IL-2) and interferon. IL-2 activates autoantigen-specific T cytotoxic lymphocytes which destroy islet cells through the secretion of toxic perforins and granzymes. Interferon activates macrophages and stimulates the release of inflammatory cytokines (including IL-1 and tumor necrosis factor [TNF]) which further destroy beta cells (McCance & Heuther, 2014). Activated Th2 lymphocytes produce  IL-4 which stimulates B lymphocytes to proliferate and produce islet cell autoantibodies (ICAs) and  anti-glutamic acid decarboxylase (antiGAD65) antibodies. AntiGAD65 is an enzyme that helps control the release of insulin from beta cells and can be used to determine the cause of diabetes (McCance & Heuther, 2014). Insulin autoantibodies [IAAs]) and zinc transporter 8 (Znt8) protein are also associated with type 1 diabetes mellitus. Despite it’s complicated pathophysiology, it is important to understand the destruction of beta cells in type 1 diabetes because it leads to a lack of insulin and amylin. Without insulin or amylin the body cannot promote glucose disappearance or limit glucose appearance from the bloodstream, respectively, resulting in hyperglycemia (Mapes & Faulds, 2014).

Clinical Presentation:

Type 1 diabetes does not present clinically until 80-90% of the beta cells have been destroyed (McCance & Heuther, 2014). Because insulin stimulates glucose uptake into tissues, stores glycose as glycogen, inhibits glucagon secretion and inhibits glucose production from the liver, the destruction of insulin-producing beta cells causes hyperglycemia (Mapes & Faulds, 2014). Type 1 diabetics may present with abrupt onset of diabetic ketoacidosis, polyuria, polyphagia, polydipsia, or rapid weight loss with marked hyperglycemia (Mapes & Faulds, 2014).  To diagnose diabetes, patients must have an A1C level greater than 6.5% percent on two separate tests; the presence of ketones in the urine and/or autoantibodies in the blood can distinguish type 1 from type 2 diabetes (Mayo Clinic, 2014).

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What Is Type 1 Diabetes?

People of all ages can develop type 1 diabetes.

If you have type 1 diabetes, your pancreas doesn’t make insulin or makes very little insulin. Insulin helps blood sugar enter the cells in your body for use as energy. Without insulin, blood sugar can’t get into cells and builds up in the bloodstream. High blood sugar is damaging to the body and causes many of the symptoms and complications of diabetes.

Type 1 diabetes was once called insulin-dependent or juvenile diabetes, but it can develop at any age.

Type 1 diabetes is less common than  type 2 —about 5-10% of people with diabetes have type 1. Currently, no one knows how to prevent type 1 diabetes, but it can be treated successfully by:

• Following your doctor’s recommendations for living a healthy lifestyle.
• Managing your blood sugar.
• Getting regular health checkups.
• Getting diabetes self-management education and support .

For Parents

If your child has type 1 diabetes—especially a young child—you’ll handle diabetes care on a day-to-day basis. Daily care will include serving healthy foods, giving insulin injections, and watching for and  treating hypoglycemia  (low blood sugar). You’ll also need to stay in close contact with your child’s health care team. They will help you understand the treatment plan and how to help your child stay healthy.

Much of the information that follows applies to children as well as adults. You can also  visit JDRF’s T1D Resources  for more information on managing your child’s type 1 diabetes.

What Causes Type 1 Diabetes?

Type 1 diabetes is thought to be caused by an autoimmune reaction (the body attacks itself by mistake). This reaction destroys the cells in the pancreas that make insulin, called beta cells. This process can go on for months or years before any symptoms appear.

Some people have certain genes (traits passed on from parent to child) that make them more likely to develop type 1 diabetes. However, many of them won’t go on to have type 1 diabetes even if they have the genes. A trigger in the environment, such as a virus, may also play a part in developing type 1 diabetes. Diet and lifestyle habits don’t cause type 1 diabetes.

Symptoms and Risk Factors

It can take months or years before  symptoms  of type 1 diabetes are noticed. Type 1 diabetes symptoms can develop in just a few weeks or months. Once symptoms appear, they can be severe.

Some type 1 diabetes symptoms are similar to symptoms of other health conditions. Don’t guess! If you think you could have type 1 diabetes, see your doctor to get your blood sugar tested. Untreated diabetes can lead to very serious—even fatal—health problems.

Risk factors  for type 1 diabetes are not as clear as for prediabetes and type 2 diabetes. However, studies show that family history plays a part.

Testing for Type 1 Diabetes

A  simple blood test  will let you know if you have diabetes. If you were tested at a health fair or pharmacy, follow up at a clinic or doctor’s office. That way you’ll be sure the results are accurate.

If your doctor thinks you have type 1 diabetes, your blood may also be tested for autoantibodies. These substances indicate your body is attacking itself and are often found with type 1 diabetes but not with type 2. You may have your urine tested for ketones too. Ketones are produced when your body burns fat for energy. Having ketones in your urine indicates you have type 1 diabetes instead of type 2.

Managing Diabetes

Unlike many health conditions, diabetes is  managed  mostly by you, with support from your health care team:

• Primary care doctor
• Foot doctor
• Registered dietitian nutritionist
• Diabetes educator

Also ask your family, teachers, and other important people in your life for help and support. Managing diabetes can be challenging, but everything you do to improve your health is worth it!

If you have type 1 diabetes, you’ll need to take insulin shots (or wear an insulin pump) every day. Insulin is needed to manage your blood sugar levels and give your body energy. You can’t take insulin as a pill. That’s because the acid in your stomach would destroy it before it could get into your bloodstream. Your doctor will work with you to figure out the most effective type and dosage of insulin for you.

You’ll also need to  do regular blood sugar checks . Ask your doctor how often you should check it and what your target blood sugar levels should be. Keeping your blood sugar levels as close to target as possible will help you prevent or delay diabetes-related  complications .

Stress is a part of life, but it can make managing diabetes harder. Both managing your blood sugar levels and dealing with daily diabetes care can be tougher to do. Regular physical activity, getting enough sleep, and exercises to relax can help. Talk to your doctor and diabetes educator about these and other ways you can manage stress.

Healthy lifestyle habits are really important too:

• Making  healthy food choices
• Being  physically active
• Controlling your  blood pressure
• Controlling your  cholesterol

Make regular appointments with your health care team. They’ll help you stay on track with your treatment plan and offer new ideas and strategies if needed.

Hypoglycemia and Diabetic Ketoacidosis

These 2 conditions are common complications of diabetes, and you’ll need to know how to handle them. Meet with your doctor for step-by-step instructions. You may want to bring a family member with you to the appointment so they learn the steps too.

Hypoglycemia  (low blood sugar) can happen quickly and needs to be  treated  quickly. It’s most often caused by:

• Too much insulin.
• Waiting too long for a meal or snack.
• Not eating enough.
• Getting extra physical activity.

Talk to your doctor if you have low blood sugar several times a week. Your treatment plan may need to be changed.

Diabetic ketoacidosis  (DKA) is a serious complication of diabetes that can be life-threatening. DKA develops when you don’t have enough insulin to let blood sugar into your cells. Very high blood sugar and low insulin levels lead to DKA. The two most common causes are illness and missing insulin shots. Talk with your doctor and make sure you understand how you can prevent and treat DKA.

Get Diabetes Education

Meeting with a diabetes educator is a great way to get support and guidance, including how to:

• Develop and stick to a healthy eating and activity plan
• Test your blood sugar and keep a record of the results
• Recognize the signs of high or low blood sugar and what to do about it
• Give yourself insulin by syringe, pen, or pump
• Monitor your feet, skin, and eyes to catch problems early
• Buy diabetes supplies and store them properly
• Manage stress and deal with daily diabetes care

Ask your doctor about  diabetes self-management education and support services and to recommend a diabetes educator. You can also search this nationwide directory  for a list of programs in your community.

Get Support

Tap into online diabetes communities for encouragement, insights, and support. Check out the American Diabetes Association’s Community page and JDRF’s TypeOneNation . Both are great ways to connect with others who share your experience.

• Type 1 Diabetes Resources and Support from JDRF
• Living With Diabetes
• Just Diagnosed With Type 1 Diabetes
• Learn About Diabetic Ketoacidosis
• 4 Ways To Take Insulin
• Making the Leap From Type 1 Teen to Adult

To receive updates about diabetes topics, enter your email address:

• Diabetes Home
• State, Local, and National Partner Diabetes Programs
• National Diabetes Prevention Program
• Native Diabetes Wellness Program
• Chronic Kidney Disease
• Vision Health Initiative
• Heart Disease and Stroke
• Overweight & Obesity

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Understanding Type 1 Diabetes

Type 1 diabetes is an autoimmune disease. Testing, coupled with education about diabetes symptoms and close follow-up, has been shown to enable earlier diagnosis and to prevent diabetes ketoacidosis.

What is type 1 diabetes?

When you have type 1 diabetes, your immune system mistakenly treats the beta cells in your pancreas that create insulin as foreign invaders and destroys them. When enough beta cells are destroyed, your pancreas can’t make insulin or makes so little of it that you need to take insulin to live. 

Insulin is a hormone that helps blood glucose (blood sugar) enter your body’s cells so that it can be used as energy. If you have diabetes, blood glucose can’t enter your cells so it builds up in your bloodstream. This causes high blood glucose ( hyperglycemia ). Over time, high blood glucose harms your body and can lead to diabetes-related complications if not treated.

Most of the time, type 1 diabetes is diagnosed in young people, but it can develop in anyone at any age. Scientists and researchers today aren’t sure how to prevent type 1 diabetes or what triggers it.

If you have type 1 diabetes, you can live a long, healthy life by having a strong support system and managing it with your diabetes care team . The treatment plan you develop with your diabetes care team will include insulin, physical activity, and an eating plan to reach your health goals.

Type 1 Diabetes Symptoms

If you or your child have the following symptoms of diabetes, let your health care provider know. Symptoms include:

• Urinating often
• Feeling very thirsty
• Feeling very hungry—even though you are eating
• Extreme fatigue
• Blurry vision
• Cuts/bruises that are slow to heal
• Weight loss—even though you are eating more

It’s important to know when you first develop type 1 diabetes, you may not have any symptoms at all.

Children with Type 1 Diabetes

Adults with Type 1 Diabetes

Learning Your Risk for Type 1 Diabetes

Why Learning Your Risk Helps

Children with type 1 diabetes will usually have the symptoms listed above. If your child is potty-trained without issues at night starts having accidents and wetting the bed again, diabetes might be the reason.

Even though it’s easy to diagnose a child with diabetes by checking their blood glucose at the doctor’s office or emergency room, the tricky part is recognizing the symptoms and knowing to take your child to get checked. If you’re a parent, it’s important to know that young children, including infants, can develop type 1 diabetes.

Sometimes children can be in diabetic ketoacidosis (DKA) when they are diagnosed with diabetes. When there is a lack of insulin in the body, high levels of an acid called ketones can build up. DKA is a medical emergency that usually requires hospitalization and immediate care with insulin and IV fluids.

When an adult develops type 1 diabetes, they are often mistakenly told they have type 2 diabetes. This may be from lack of awareness that type 1 diabetes can start at any age and in people of every race, shape, weight, and size. People with type 1 diabetes who also have the classic risk factors for type 2 diabetes—such as overweight/obesity, not being physically active, having high blood pressure, or are over age 35—are often misdiagnosed. It can also be tricky because some adults with new-onset type 1 diabetes are not sick at first. Their health care provider may find an elevated blood glucose level at a routine visit and starts them on diet, exercise, and an oral medication.

Early detection and treatment of diabetes can decrease the risk of developing complications both at the time of diagnosis and in the future. By knowing and recognizing the symptoms above, you can learn if you have type 1 diabetes early and avoid complications, like diabetic ketoacidosis (DKA) . 

Did you know?

• Type 1 diabetes doesn’t develop only in children
• There have been recent advances in type 1 diabetes screening and treatment

If you have a family history of type 1 diabetes, your health care provider may suggest screening for type 1 diabetes. They will order a blood test to measure your islet autoantibodies. The test results can go one of two ways:

• Negative: Your health care provider will retest you in the future.
• Positive: Even if you get a positive result, this doesn’t mean you have type 1 diabetes. Your health care provider will refer you to counseling about the risk of developing diabetes, diabetes symptoms, and DKA prevention. Additional testing as needed may be done to determine the course of your treatment.  

Even if you may not want to know if you, your children, or other family members are at risk for developing type 1 diabetes, there are benefits to knowing.

First, you can learn more about the early warning signs of type 1 diabetes so you and your health care team can detect diabetes early—before DKA or severe illness develops. Because DKA can be life-threatening and early symptoms can be vague, knowing what to watch out for can help detect and treat DKA early or prevent it altogether.

Second, there are emerging treatments and clinical trials that seek to delay the onset of type 1 diabetes in those who are at high risk. If you are at high risk for developing type 1 diabetes, it will be important to speak with an endocrinologist to learn whether these opportunities may be available and right for you.

Calling All Professionals

ADA convened leading experts, including endocrinologists, researchers, primary care professionals, certified diabetes care and education specialists, and mental health professionals, to understand opportunities and barriers to type 1 diabetes screening and awareness. The outcome of this roundtable is a report that outlines the discussion and potential opportunities for future direction. The report does not necessarily reflect official guidelines or recommendations from the American Diabetes Association or other participating organizations.

The Honeymoon Phase

Some people with type 1 diabetes have a "honeymoon" period, a brief period of time where your body is producing enough insulin to lower blood glucose levels. The honeymoon phase usually happens after you start taking insulin and you may not need as much to manage your blood glucose. Work with your diabetes care team for treatment and care to avoid complications like hypoglycemia . A honeymoon period can last as little as a week or even up to a year. It’s important to know that the absence of symptoms doesn't mean the diabetes is gone. The pancreas will eventually be unable to make enough insulin, and, if untreated, the symptoms will return.

Is it Possible You Don't Have Type 2 Diabetes? 

If you or someone you know is diagnosed with type 2 diabetes but isn’t able to manage it with the typical treatments for type 2 diabetes, it may be worth a visit to an endocrinologist to verify what type of diabetes you have. Generally, this requires antibody tests and possibly the measurement of a C-peptide level. It is important to be sure that your diagnosis is correct because that will determine your treatment plan, allowing you manage your diabetes and prevent its complications.

Resources for Type 1 Diabetes

Browse these resources for type 1 diabetes.

Resources for Living with Type 1 Diabetes

Whether you’ve lived with diabetes for a long time, are newly diagnosed, or a caregiver, we have the resources to help you learn about how to navigate life with type 1.

Having diabetes doesn’t mean giving up all your favorite foods, it’s about modifying what you love to fit your new lifestyle and help you manage diabetes.  

Physical Activity

Staying physically active will help you manage your diabetes, improve your mood, and lower your risk for complications.

Diabetes Food Hub®

Access thousands of free diabetes-friendly recipes for all meals, occasions, and dietary restrictions—plus nutrition articles that answer common questions people have about eating with diabetes.

Safe at School®

This program helps to ensure children with diabets receive the care they need at school.

Healthy Living e-newsletter

Sign up to receive diabetes-friendly recipes, articles, and more resources delivered directly to your email inbox every month.

Mental Health Resource

Screening for diabetes has a significant emotional and mental health toll. These resources can help you offer support to people you treat and their families.

Diagnosis and Classification of Type 1 Diabetes

Read our Standards of Care in Diabetes—2024 recommendations on type 1 diabetes screening and diagnosis. 

Prevention or Delay of Diabetes

Read Standards of Care in Diabetes recommendations on interventions to delay type 1 diabetes.  

Infographics

These documents provide at-a-glance guidance for type 1 diabetes screening based on the Standards of Care in Diabetes .

Latest Innovations and Treatments in Type 1 Diabetes

Earn free CE credit in the Institute of Learning.

School Nurse Resources

School nurses play an important role for students with type 1 diabetes and their caregivers. Training resources are available.

Information specialists at the Center for Information are your personal guides to information on diabetes, donation inquiries, as well as American Diabetes Association programs and events.

1-800-diabetes ( 1-800-342-2383 )  , supported in part by:.

Sanofi supports phase 3 of ADA’s Therapeutic Inertia program. The main goal of phase 3 is to promote the measurable adoption of evidence-based practices, strategies, programs and tools that address key barriers associated with therapeutic inertia in diabetes care, leading to improved, timely treatment modification and improved overall glycemic control in adult patients with type 2 diabetes. Sanofi also supported the American Diabetes Association’s 100 Years of Insulin, a year-long campaign that focused on awareness, education and promoting activities that build community.

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Endocrinology

• New treatment option for early type 1 diabetes

April 09, 2024

Type 1 diabetes accounts for 5% to10% of all diabetes, and the only available therapy for patients with type 1 diabetes has been insulin for the past 100 years. However, now there is a new immune-modulating therapy available to slow the rate of islet cell loss for people with early stages of type 1 diabetes.

Ana L. Creo, M.D. , of Pediatric Endocrinology and Metabolism at Mayo Clinic in Rochester, Minnesota, explains how type 1 diabetes is now classified into three stages:

• Stage 1: two or more positive diabetes autoantibodies but normal blood glucose levels.
• Stage 2: two or more positive diabetes autoantibodies and asymptomatic dysglycemia (fasting glucose, 100-125 mg/dL; two-hour glucose, 140-199 mg/dL; or A1C 5.7% to 6.4%).
• Stage 3: two or more positive diabetes autoantibodies and symptomatic hyperglycemia, with clinical disease defined by standard glycemic criteria.

Alaa Al Nofal, M.D., M.B.A. , a pediatric endocrinologist at Mayo Clinic in Rochester, Minnesota, says, "Given the progress in clinical and research domains, we recommend screening for early stages of type 1 diabetes in people who have a first-degree relative with type 1 diabetes, especially offspring of adults with type 1 diabetes. While the risk of type 1 diabetes in children is around 1 in 300, having a first-degree relative increases the risk to 1 in 20, which is 15 times higher than the risk in the general population.

"If a person is found to have positive type 1 diabetes autoantibodies, healthcare professionals recommend referral to a specialized diabetes center for further evaluation and type 1 diabetes staging, as well as consideration for disease-modifying therapy."

Screening for type 1 diabetes can be achieved through national screening programs or local clinical lab evaluation. Screening can identify appropriate participants for clinical trials as well as candidates for FDA-approved therapy that slows the progression to stage 3 type 1 diabetes.

According to findings published in The New England Journal of Medicine in 2023, teplizumab is an anti-CD3 antibody approved for people 8 years and older with stage 2 type 1 diabetes. Teplizumab given as a 14-day infusion slowed the onset of stage 3 disease by a median of two years in a total of 76 participants randomized to teplizumab or placebo.

"Half of the participants receiving teplizumab remained entirely disease-free at 48 months. While further large-scale efficacy studies are needed, hopefully this will be one of several agents targeting the root cause of type 1 diabetes in the future, thus changing the paradigm of future diabetes management," says Dr. Creo.

For more information

Ramos EL, et al. Teplizumab and β-cell function in newly diagnosed type 1 diabetes. The New England Journal of Medicine. 2023;389:2151.

Refer a patient to Mayo Clinic.

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New advances in type 1 diabetes

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• Peer review
• Savitha Subramanian , professor of medicine ,
• Farah Khan , clinical associate professor of medicine ,
• Irl B Hirsch , professor of medicine
• University of Washington Diabetes Institute, Division of Metabolism, Endocrinology and Nutrition, University of Washington, Seattle, WA, USA
• Correspondence to: I B Hirsch ihirsch{at}uw.edu

Type 1 diabetes is an autoimmune condition resulting in insulin deficiency and eventual loss of pancreatic β cell function requiring lifelong insulin therapy. Since the discovery of insulin more than 100 years ago, vast advances in treatments have improved care for many people with type 1 diabetes. Ongoing research on the genetics and immunology of type 1 diabetes and on interventions to modify disease course and preserve β cell function have expanded our broad understanding of this condition. Biomarkers of type 1 diabetes are detectable months to years before development of overt disease, and three stages of diabetes are now recognized. The advent of continuous glucose monitoring and the newer automated insulin delivery systems have changed the landscape of type 1 diabetes management and are associated with improved glycated hemoglobin and decreased hypoglycemia. Adjunctive therapies such as sodium glucose cotransporter-1 inhibitors and glucagon-like peptide 1 receptor agonists may find use in management in the future. Despite these rapid advances in the field, people living in under-resourced parts of the world struggle to obtain necessities such as insulin, syringes, and blood glucose monitoring essential for managing this condition. This review covers recent developments in diagnosis and treatment and future directions in the broad field of type 1 diabetes.

Introduction

Type 1 diabetes is an autoimmune condition that occurs as a result of destruction of the insulin producing β cells of the pancreatic islets, usually leading to severe endogenous insulin deficiency. 1 Without treatment, diabetic ketoacidosis will develop and eventually death will follow; thus, lifelong insulin therapy is needed for survival. Type 1 diabetes represents 5-10% of all diabetes, and diagnosis classically occurs in children but can also occur in adulthood. The burden of type 1 diabetes is expansive; it can result in long term complications, decreased life expectancy, and reduced quality of life and can add significant financial burden. Despite vast improvements in insulin, insulin delivery, and glucose monitoring technology, a large proportion of people with type 1 diabetes do not achieve glycemic goals. The massive burden of type 1 diabetes for patients and their families needs to be appreciated. The calculation and timing of prandial insulin dosing, often from food with unknown carbohydrate content, appropriate food and insulin dosing when exercising, and cost of therapy are all major challenges. The psychological realities of both acute management and the prospect of chronic complications add to the burden. Education programs and consistent surveillance for “diabetes burnout” are ideally available to everyone with type 1 diabetes.

In this review, we discuss recent developments in the rapidly changing landscape of type 1 diabetes and highlight aspects of current epidemiology and advances in diagnosis, technology, and management. We do not cover the breadth of complications of diabetes or certain unique scenarios including psychosocial aspects of type 1 diabetes management, management aspects specific to older adults, and β cell replacement therapies. Our review is intended for the clinical reader, including general internists, family practitioners, and endocrinologists, but we acknowledge the critical role that people living with type 1 diabetes and their families play in the ongoing efforts to understand this lifelong condition.

Sources and selection criteria

We did individual searches for studies on PubMed by using terms relevant to the specific topics covered in this review pertaining to type 1 diabetes. Search terms used included “type 1 diabetes” and each individual topic—diagnosis, autoantibodies, adjuvant therapies, continuous glucose monitoring, automated insulin delivery, immunotherapies, diabetic ketoacidosis, hypoglycemia, and under-resourced settings. We considered all studies published in the English language between 1 January 2001 and 31 January 2023. We selected publications outside of this timeline on the basis of relevance to each topic. We also supplemented our search strategy by a hand search of the references of key articles. We prioritized studies on each highlighted topic according to the level of evidence (randomized controlled trials (RCTs), systematic reviews and meta-analyses, consensus statements, and high quality observational studies), study size (we prioritized studies with at least 50 participants when available), and time of publication (we prioritized studies published since 2003 except for the landmark Diabetes Control and Complications Trial and a historical paper by Tuomi on diabetes autoantibodies, both from 1993). For topics on which evidence from RCTs was unavailable, we included other study types of the highest level of evidence available. To cover all important clinical aspects of the broad array of topics covered in this review, we included additional publications such as clinical reviews as appropriate on the basis of clinical relevance to both patients and clinicians in our opinion.

Epidemiology

The incidence of type 1 diabetes is rising worldwide, possibly owing to epigenetic and environmental factors. Globally in 2020 an estimated 8.7 million people were living with type 1 diabetes, of whom approximately 1.5 million were under 20 years of age. 2 This number is expected to rise to more than 17 million by 2040 ( https://www.t1dindex.org/#global ). The International Diabetes Federation estimates the global prevalence of type 1 diabetes at 0.1%, and this is likely an underestimation as diagnoses of type 1 diabetes in adults are often not accounted for. The incidence of adult onset type 1 diabetes is higher in Europe, especially in Nordic countries, and lowest in Asian countries. 3 Adult onset type 1 diabetes is also more prevalent in men than in women. An increase in prevalence in people under 20 years of age has been observed in several western cohorts including the US, 4 5 Netherlands, 6 Canada, 7 Hungary, 8 and Germany. 9

Classically, type 1 diabetes presents over the course of days or weeks in children and adolescents with polyuria, polydipsia, and weight loss due to glycosuria. The diagnosis is usually straightforward, with profound hyperglycemia (often >300 mg/dL) usually with ketonuria with or without ketoacidemia. Usually, more than one autoantibody is present at diagnosis ( table 1 ). 10 The number of islet autoantibodies combined with parameters of glucose tolerance now forms the basis of risk prediction for type 1 diabetes, with stage 3 being clinical disease ( fig 1 ). 11 The originally discovered autoantibody, islet cell antibody, is no longer used clinically owing to variability of the assay despite standardisation. 12

Autoantibody characteristics associated with increased risk of type 1 diabetes 10

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Natural history of type 1 diabetes. Adapted with permission from Insel RA, et al. Diabetes Care 2015;38:1964-74 11

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Half of all new cases of type 1 diabetes are now recognized as occurring in adults. 13 Misclassification due to misdiagnosis (commonly as type 2 diabetes) occurs in nearly 40% of people. 14 As opposed to typical childhood onset type 1 diabetes, progression to severe insulin deficiency, and therefore its clinical presentation in adults, is variable. The term latent autoimmune diabetes of adults (LADA) was introduced 30 years ago to identify adults who developed immune mediated diabetes. 15 An international consensus defined the diagnostic criteria for LADA as age >30 years, lack of need for insulin use for at least six months, and presence of islet cell autoantibodies. 16 However, debate as to whether the term LADA should even be used as a diagnostic term persists. The American Diabetes Association (ADA) Standards of Care note that for the purpose of classification, all forms of diabetes mediated by autoimmune β cell destruction are included in the classification of type 1 diabetes. 17 Nevertheless, they note that use of the term LADA is acceptable owing to the practical effect of heightening awareness of adults likely to have progressive autoimmune β cell destruction and thereby accelerating insulin initiation by clinicians to prevent diabetic ketoacidosis.

The investigation of adults with suspected type 1 diabetes is not always straightforward ( fig 2 ). 18 Islet cell autoantibodies such as glutamic acid decarboxylase antibody (GADA), tyrosine phosphatase IA2 antibody, and zinc transporter isoform 8 autoantibody act as markers of immune activity and can be detected in the blood with standardized assays ( table 1 ). The presence of one or more antibodies in adults with diabetes could mark the progression to severe insulin deficiency; these individuals should be considered to have type 1 diabetes. 1 Autoantibodies, especially GADA, should be measured only in people with clinically suspected type 1 diabetes, as low concentrations of GADA can be seen in type 2 diabetes and thus false positive measurements are a concern. 19 That 5-10% of cases of type 1 diabetes may occur without diabetes autoantibodies is also now clear, 20 and that the diabetes autoantibodies disappear over time is also well appreciated. 21

Flowchart for investigation of suspected type 1 diabetes in adults, based on data from white European populations. No single clinical feature in isolation confirms type 1 diabetes. The most discriminative feature is younger age at diagnosis (<35 years), with lower body mass index (<25), unintentional weight loss, ketoacidosis, and glucose >360 mg/dL at presentation. Adapted with permission from Holt RIG, et al. Diabetes Care 2021;44:2589-625 1

Genetic risk scoring (GRS) for type 1 diabetes has received attention to differentiate people whose classification is unclear. 22 23 24 Developed in 2019, the T1D-GRS2 uses 67 single nucleotide polymorphisms from known autoimmune loci and can predict type 1 diabetes in children of European and African ancestry. Although GRS is not available for routine clinical use, it may allow prediction of future cases of type 1 diabetes to allow prevention strategies with immune intervention (see below).

A major change in the type 1 diabetes phenotype has occurred over the past few decades, with an increase in obesity; the reasons for this are complex. In the general population, including people with type 1 diabetes, an epidemic of sedentary lifestyles and the “westernized diet” consisting of increased processed foods, refined sugars, and saturated fat is occurring. In people with type 1 diabetes, the overall improvement in glycemic control since the report of the Diabetes Control and Complications Trial (DCCT) in 1993 (when one or two insulin injections a day was standard therapy) has resulted in less glycosuria so that the typical patient with lower body weight is uncommon in high income countries. In the US T1D Exchange, more than two thirds of the adult population were overweight or obese. 25

Similarly, obesity in young people with type 1 diabetes has also increased over the decades. 26 The combination of autoimmune insulin deficiency with obesity and insulin resistance has received several descriptive names over the years, with this phenotype being described as double diabetes and hybrid diabetes, among others, 26 27 but no formal nomenclature in the diabetes classification exists. Many of these patients have family members with type 2 diabetes, and some patients probably do have both types of diabetes. Clinically, minimal research has been done into how this specific population responds to certain antihyperglycemic oral agents, such as glucagon-like peptide 1 (GLP-1) receptor agonists, given the glycemic, weight loss, and cardiovascular benefits seen with these agents. 28 These patients are common in most adult diabetes practices, and weight management in the presence of insulin resistance and insulin deficiency remains unclear.

Advances in monitoring

The introduction of home blood glucose monitoring (BGM) more than 45 years ago was met with much skepticism until the report of the DCCT. 29 Since then, home BGM has improved in accuracy, precision, and ease of use. 30 Today, in many parts of the world, home BGM, a static measurement of blood glucose, has been replaced by continuous glucose monitoring (CGM), a dynamic view of glycemia. CGM is superior to home BGM for glycemic control, as confirmed in a meta-analysis of 21 studies and 2149 participants with type 1 diabetes in which CGM use significantly decreased glycated hemoglobin (HbA 1c ) concentrations compared with BGM (mean difference −0.23%, 95% confidence interval −3.83 to −1.08; P<0.001), with a greater benefit if baseline HbA 1c was >8% (mean difference −0.43%, −6.04 to −3.30; P<0.001). 31 This newer technology has also evolved into a critical component of automated insulin delivery. 32

CGM is the standard for glucose monitoring for most adults with type 1 diabetes. 1 This technology uses interstitial fluid glucose concentrations to estimate blood glucose. Two types of CGM are available. The first type, called “real time CGM”, provides a continuous stream of glucose data to a receiver, mobile application, smartwatch, or pump. The second type, “intermittently scanned CGM,” needs to be scanned by a reader device or smartphone. Both of these technologies have shown improvements in HbA 1c and amount of time spent in the hypoglycemic range compared with home BGM when used in conjunction with multiple daily injections or “open loop” insulin pump therapy. 33 34 Real time CGM has also been shown to reduce hypoglycemic burden in older adults with type 1 diabetes ( table 2 ). 36 Alerts that predict or alarm with both hypoglycemia and hyperglycemia can be customized for the patient’s situation (for example, a person with unawareness of hypoglycemia would have an alert at a higher glucose concentration). Family members can also remotely monitor glycemia and be alerted when appropriate. The accuracy of these devices has improved since their introduction in 2006, so that currently available sensors can be used without a confirmation glucose concentration to make a treatment decision with insulin. However, some situations require home BGM, especially when concerns exist that the CGM does not match symptoms of hypoglycemia.

Summary of trials for each topic covered

Analysis of CGM reports retrospectively can assist therapeutic decision making both for the provider and the patient. Importantly, assessing the retrospective reports and watching the CGM in real time together offer insight to the patient with regard to insulin dosing, food choices, and exercise. Patients should be encouraged to assess their data on a regular basis to better understand their diabetes self-management. Table 3 shows standard metrics and targets for CGM data. 52 Figure 3 shows an ambulatory glucose profile.

Standardized continuous glucose monitoring metrics for adults with diabetes 52

Example of ambulatory glucose profile of 52 year old woman with type 1 diabetes and fear of hypoglycemia. CGM=continuous glucose monitoring; GMI=glucose management indicator

Improvements in technology and evidence for CGM resulting in international recommendations for its widespread use have resulted in greater uptake by people with type 1 diabetes across the globe where available and accessible. Despite this, not everyone wishes to use it; some people find wearing any device too intrusive, and for many the cost is prohibitive. These people need at the very least before meal and bedtime home BGM.

A next generation implantable CGM device (Sensionics), with an improved calibration algorithm that lasts 180 days after insertion by a healthcare professional, is available in both the EU and US. Although fingerstick glucose calibration is needed, the accuracy is comparable to that of other available devices. 53

Advances in treatments

The discovery of insulin in 1921, resulting in a Nobel Prize, was considered one of the greatest scientific achievements of the 20th century. The development of purified animal insulins in the late 1970s, followed by human insulin in the early 1980s, resulted in dramatic reductions in allergic reactions and lipoatrophy. Introduction of the first generation of insulin analogs, insulin lispro in the mid-1990s followed by insulin glargine in the early 2000s, was an important advance for the treatment of type 1 diabetes. 54 We review the next generation of insulin analogs here. Table 4 provides details on available insulins.

Pharmacokinetics of commonly used insulin preparations

Ultra-long acting basal insulins

Insulin degludec was developed with the intention of improving the duration of action and achieving a flatter profile compared with the original long acting insulin analogs, insulin glargine and insulin detemir. Its duration of action of 42 hours at steady state means that the profile is generally flat without significant day-to-day variability, resulting in less hypoglycemia compared with U-100 glargine. 39 55

When U-100 insulin glargine is concentrated threefold, its action is prolonged. 56 U-300 glargine has a different kinetic profile and is delivered in one third of the volume of U-100 glargine, with longer and flatter effects. The smaller volume of U-300 glargine results in slower and more gradual release of insulin monomers owing to reduced surface area in the subcutaneous space. 57 U-300 glargine also results in lesser hypoglycemia compared with U-100 glargine. 58

Ultra-rapid acting prandial insulins

Rapid acting insulin analogs include insulin lispro, aspart, and glulisine. With availability of insulin lispro, the hope was for a prandial insulin that better matched food absorption. However, these newer insulins are too slow to control the glucose spike seen with ingestion of a high carbohydrate load, leading to the development of insulins with even faster onset of action.

The first available ultra-rapid prandial insulin was fast acting insulin aspart. This insulin has an onset of appearance approximately twice as fast (~5 min earlier) as insulin aspart, whereas dose-concentration and dose-response relations are comparable between the two insulins ( table 4 ). 59 In adults with type 1 diabetes, mealtime and post-meal fast acting aspart led to non-inferior glycemic control compared with mealtime aspart, in combination with basal insulin. 60 Mean HbA 1c was 7.3%, 7.3%, and 7.4% in the mealtime faster aspart, mealtime aspart, and post‐meal faster aspart arms, respectively (P<0.001 for non-inferiority).

Insulin lispro-aabc is the second ultra-rapid prandial insulin. In early kinetic studies, insulin lispro-aabc appeared in the serum five minutes faster with 6.4-fold greater exposure in the first 15 minutes compared with insulin lispro. 61 The duration of exposure of the insulin concentrations in this study was 51 minutes faster with lispro-aabc. Overall insulin exposure was similar between the two groups. Clinically, lispro-aabc is non-inferior to insulin lispro, but postprandial hyperglycemia is lower with the faster acting analog. 62 Lispro-aabc given at mealtime resulted in greater improvement in post-prandial glucose (two hour post-prandial glucose −31.1 mg/dL, 95% confidence interval −41.0 to −21.2; P<0.001).

Both ultra-rapid acting insulins can be used in insulin pumps. Lispro-aabc tends to have more insertion site reactions than insulin lispro. 63 A meta-analysis including nine studies and 1156 participants reported increased infusion set changes on rapid acting insulin analogs (odds ratio 1.60, 95% confidence interval 1.26 to 2.03). 64

Pulmonary inhaled insulin

The quickest acting insulin is pulmonary inhaled insulin, with an onset of action of 12 minutes and a duration of 1.5-3 hours. 65 When used with postprandial supplemental dosing, glucose control is improved without an increase in hypoglycemia. 66

Insulin delivery systems

Approved automated insulin delivery systems.

CGM systems and insulin pumps have shown improvement in glycemic control and decreased risk of severe hypoglycemia compared with use of self-monitoring of blood glucose and multiple daily insulin injections in type 1 diabetes. 67 68 69 Using CGM and insulin pump together (referred to as sensor augmented pump therapy) only modestly improves HbA 1c in patients who have high sensor wear time, 70 71 but the management burden of diabetes does not decrease as frequent user input is necessary. Thus emerged the concept of glucose responsive automated insulin delivery (AID), in which data from CGM can inform and allow adjustment of insulin delivery.

In the past decade, exponential improvements in CGM technologies and refined insulin dosing pump algorithms have led to the development of AID systems that allow for minimization of insulin delivery burden. The early AID systems reduced hypoglycemia risk by automatically suspending insulin delivery when glucose concentrations dropped to below a pre-specified threshold but did not account for high glucose concentrations. More complex algorithms adjusting insulin delivery up and down automatically in response to real time sensor glucose concentrations now allow close replication of normal endocrine pancreatic physiology.

AID systems (also called closed loop or artificial pancreas systems) include three components—an insulin pump that continuously delivers rapid acting insulin, a continuous glucose sensor that measures interstitial fluid glucose at frequent intervals, and a control algorithm that continuously adjusts insulin delivery that resides in the insulin pump or a smartphone application or handheld device ( fig 4 ). All AID systems that are available today are referred to as “hybrid” closed loop (HCL) systems, as users are required to manually enter prandial insulin boluses and signal exercise, but insulin delivery is automated at night time and between meals. AID systems, regardless of the type used, have shown benefit in glycemic control and cost effectiveness, improve quality of life by improving sleep quality, and decrease anxiety and diabetes burden in adults and children. 72 73 74 Limitations to today’s HCL systems are primarily related to pharmacokinetics and pharmacodynamics of available analog insulins and accuracy of CGM in extremes of blood glucose values. The iLet bionic pancreas, cleared by the US Food and Drug Administration (FDA) in May 2023, is an AID system that determines all therapeutic insulin doses for an individual on the basis of body weight, eliminating the need for calculation of basal rates, insulin to carbohydrate ratios, blood glucose corrections, and bolus dose. The control algorithms adapt continuously and autonomously to the individual’s insulin needs. 38 Table 5 lists available AID systems.

Schematic of closed loop insulin pump technology. The continuous glucose monitor senses interstitial glucose concentrations and sends the information via Bluetooth to a control algorithm hosted on an insulin pump (or smartphone). The algorithm calculates the amount of insulin required, and the insulin pump delivers rapid acting insulin subcutaneously

Comparison of commercially available hybrid closed loop systems 75

Unapproved systems

Do-it-yourself (DIY) closed loop systems—DIY open artificial pancreas systems—have been developed by people with type 1 diabetes with the goal of self-adjusting insulin by modifying their individually owned devices. 76 These systems are built by the individual using an open source code widely available to anyone with compatible medical devices who is willing and able to build their own system. DIY systems are used by several thousand people across the globe but are not approved by regulatory bodies; they are patient-driven and considered “off-label” use of technology with the patient assuming full responsibility for their use. Clinicians caring for these patients should ensure basic diabetes skills, including pump site maintenance, a knowledge of how the chosen system works, and knowing when to switch to “manual mode” for patients using an artificial pancreas system of any kind. 76 The small body of studies on DIY looping suggests improvement in HbA 1c , increased time in range, decreased hypoglycemia and glucose variability, improvement in night time blood glucose concentrations, and reduced mental burden of diabetes management. 77 78 79 Although actively prescribing or initiating these options is not recommended, these patients should be supported by clinical teams; insulin prescription should not be withheld, and, if initiated by the patient, unregulated DIY options should be openly discussed to ensure open and transparent relationships. 78

In January 2023, the US FDA cleared the Tidepool Loop app, a DIY AID system. This software will connect the CGM, insulin pump, and Loop algorithm, but no RCTs using this method are available.

β cell replacement therapies

For patients with type 1 diabetes who meet specific clinical criteria, β cell replacement therapy using whole pancreas or pancreatic islet transplantation can be considered. Benefits of transplantation include immediate cessation of insulin therapy, attainment of euglycemia, and avoidance of hypoglycemia. Additional benefits include improved quality of life and stabilization of complications. 80 Chronic immunosuppression is needed to prevent graft rejection after transplantation.

Pancreas transplantation

Whole pancreas transplantation, first performed in 1966, involves complex abdominal surgery and lifelong immunosuppressive therapy and is limited by organ donor availability. Today, pancreas transplants are usually performed simultaneously using two organs from the same donor (simultaneous pancreas-kidney transplant (SPKT)), sequentially if the candidate has a living donor for renal transplantation (pancreas after kidney transplant (PAKT)) or on its own (pancreas transplantation alone). Most whole pancreas transplants are performed with kidney transplantation for end stage diabetic kidney disease. Pancreas graft survival at five years after SPKT is 80% and is superior to that with pancreas transplants alone (62%) or PAKT (67%). 81 Studies from large centers where SPKT is performed show that recipients can expect metabolic improvements including amelioration of problematic hypoglycemia for at least five years. 81 The number of pancreas transplantations has steadily decreased in the past two decades.

Islet transplantation

Islet transplantation can be pursued in selected patients with type 1 diabetes marked by unawareness of hypoglycemia and severe hypoglycemic episodes, to help restore the α cell response critical for responding to hypoglycemia. 82 83 Islet transplantation involves donor pancreas procurement with subsequent steps to isolate, purify, culture, and infuse the islets. Multiple donors are needed to provide enough islet cells to overcome islet cell loss during transplantation. Survival of the islet grafts, limited donor supply, and lifelong need for immunosuppressant therapy remain some of the biggest challenges. 84 Islet transplantation remains experimental in the US and is offered in a few specialized centers in North America, some parts of Europe, and Australia. 85

Disease modifying treatments for β cell preservation

Therapies targeting T cells, B cells, and cytokines that find use in a variety of autoimmune diseases have also been applied to type 1 diabetes. The overarching goal of immune therapies in type 1 diabetes is to prevent or delay the loss of functional β cell mass. Studies thus far in early type 1 diabetes have not yet successfully shown reversal of loss of C peptide or maintenance of concentrations after diagnosis, although some have shown preservation or slowing of loss of β cells. This suggests that a critical time window of opportunity exists for starting treatment depending on the stage of type 1 diabetes ( fig 1 ).

Teplizumab is a humanized monoclonal antibody against the CD3 molecule on T cells; it is thought to modify CD8 positive T lymphocytes, key effector cells that mediate β cell death and preserves regulatory T cells. 86 Teplizumab, when administered to patients with new onset of type 1 diabetes, was unable to restore glycemia despite C peptide preservation. 87 However, in its phase II prevention study of early intervention in susceptible individuals (at least two positive autoantibodies and an abnormal oral glucose tolerance test at trial entry), a single course of teplizumab delayed progression to clinical type 1 diabetes by about two years ( table 2 ). 43 On the basis of these results, teplizumab received approval in the US for people at high risk of type 1 diabetes in November 2022. 88 A phase III trial (PROTECT; NCT03875729 ) to evaluate the efficacy and safety of teplizumab versus placebo in children and adolescents with new diagnosis of type 1 diabetes (within six weeks) is ongoing. 89

Thus far, targeting various components of the immune response has been attempted in early type 1 diabetes without any long term beneficial effects on C peptide preservation. Co-stimulation blockade using CTLA4-Ig abatacept, a fusion protein that interferes with co-stimulation needed in the early phases of T cell activation that occurs in type 1 diabetes, is being tested for efficacy in prevention of type 1 diabetes ( NCT01773707 ). 90 Similarly, several cytokine directed anti-inflammatory targets (interleukin 6 receptor, interleukin 1β, tumor necrosis factor ɑ) have not shown any benefit.

Non-immunomodulatory adjunctive therapies

Adjunctive therapies for type 1 diabetes have been long entertained owing to problems surrounding insulin delivery, adequacy of glycemic management, and side effects associated with insulin, especially weight gain and hypoglycemia. At least 50% of adults with type 1 diabetes are overweight or obese, presenting an unmet need for weight management in these people. Increased cardiovascular risk in these people despite good glycemic management presents additional challenges. Thus, use of adjuvant therapies may tackle these problems.

Metformin, by decreasing hepatic glucose production, could potentially decrease fasting glucose concentrations. 91 It has shown benefit in reducing insulin doses and possibly improving metabolic control in obese/overweight people with type 1 diabetes. A meta-analysis of 19 RCTs suggests short term improvement in HbA 1c that is not sustained after three months and is associated with higher incidence of gastrointestinal side effects. 92 No evidence shows that metformin decreases cardiovascular morbidity in type 1 diabetes. Therefore, owing to lack of conclusive benefit, addition of metformin to treatment regimens is not recommended in consensus guidelines.

Glucagon-like peptide receptor agonists

Endogenous GLP-1 is an incretin hormone secreted from intestinal L cells in response to nutrient ingestion and enhances glucose induced insulin secretion, suppresses glucagon secretion, delays gastric emptying, and induces satiety. 93 GLP-1 promotes β cell proliferation and inhibits apoptosis, leading to expansion of β cell mass. GLP-1 secretion in patients with type 1 diabetes is similar to that seen in people without diabetes. Early RCTs of liraglutide in type 1 diabetes resulted in weight loss and modest lowering of HbA 1c ( table 2 ). 49 50 Liraglutide 1.8 mg in people with type 1 diabetes and higher body mass index decreased HbA 1c , weight, and insulin requirements with no increased hypoglycemia risk. 94 However, on the basis of results from a study of weekly exenatide that showed similar results, these effects may not be sustained. 51 A meta-analysis of 24 studies including 3377 participants showed that the average HbA 1c decrease from GLP-1 receptor agonists compared with placebo was highest for liraglutide 1.8 mg daily (−0.28%, 95% confidence interval −0.38% to−0.19%) and exenatide (−0.17%, −0.28% to 0.02%). The estimated weight loss from GLP-1 receptor agonists compared with placebo was −4.89 (−5.33 to−4.45)  kg for liraglutide 1.8 mg and −4.06  (−5.33 to−2.79) kg for exenatide. 95 No increase in severe hypoglycemia was seen (odds ratio 0.67, 0.43 to 1.04) but therapy was associated with higher levels of nausea. GLP-1 receptor agonist use may be beneficial for weight loss and reducing insulin doses in a subset of patients with type 1 diabetes. GLP-1 receptor agonists are not a recommended treatment option in type 1 diabetes. Semaglutide is being studied in type 1 diabetes in two clinical trials ( NCT05819138 ; NCT05822609 ).

Sodium-glucose cotransporter inhibitors

Sodium-glucose cotransporter 2 (SGLT-2), a protein expressed in the proximal convoluted tubule of the kidney, reabsorbs filtered glucose; its inhibition prevents glucose reabsorption in the tubule and increases glucose excretion by the kidney. Notably, the action of these agents is independent of insulin, so this class of drugs has potential as adjunctive therapy for type 1 diabetes. Clinical trials have shown significant benefit in cardiovascular and renal outcomes in type 2 diabetes; therefore, significant interest exists for use in type 1 diabetes. Several available SGLT-2 inhibitors have been studied in type 1 diabetes and have shown promising results with evidence of decreased total daily insulin dosage, improvement in HbA 1c , lower rates of hypoglycemia, and decrease in body weight; however, these effects do not seem to be sustained at one year in clinical trials and seem to wane with time. Despite beneficial effects, increased incidence of diabetic ketoacidosis has been observed in all trials, is a major concern, and is persistent despite educational efforts. 96 97 98 Low dose empagliflozin (2.5 mg) has shown lower rates of diabetic ketoacidosis in clinical trials ( table 2 ). 47 Favorable risk profiles have been noted in Japan, the only market where SGLT-2 inhibitors are approved for adjunctive use in type 1 diabetes. 99 In the US, SGLT-2 inhibitors are approved for use in type 2 diabetes only. In Europe, although dapagliflozin was approved for use as adjunct therapy to insulin in adults with type 1 diabetes, the manufacturer voluntarily withdrew the indication for the drug in 2021. 100 Sotagliflozin is a dual SGLT-1 and SGLT-2 inhibitor that decreases renal glucose reabsorption through systemic inhibition of SGLT-2 and decreases glucose absorption in the proximal intestine by SGLT-1 inhibition, blunting and delaying postprandial hyperglycemia. 101 Studies of sotagliflozin in type 1 diabetes have shown sustained HbA 1c reduction, weight loss, lower insulin requirements, lesser hypoglycemia, and more diabetic ketoacidosis relative to placebo. 102 103 104 The drug received authorization in the EU for use in type 1 diabetes, but it is not marketed there. Although SGLT inhibitors are efficacious in type 1 diabetes management, the risk of diabetic ketoacidosis is a major limitation to widespread use of these agents.

Updates in acute complications of type 1 diabetes

Diabetic ketoacidosis.

Diabetic ketoacidosis is a serious and potentially fatal hyperglycemic emergency accompanied by significant rates of mortality and morbidity as well as high financial burden for healthcare systems and societies. In the past decade, increasing rates of diabetic ketoacidosis in adults have been observed in the US and Europe. 105 106 This may be related to changes in the definition of diabetic ketoacidosis, use of medications associated with higher risk, and admission of patients at lower risk. 107 In a US report of hospital admissions with diabetic ketoacidosis, 53% of those admitted were between the ages of 18 and 44, with higher rates in men than in women. 108 Overall, although mortality from diabetic ketoacidosis in developed countries remains low, rates have risen in people aged >60 and in those with coexisting life threatening illnesses. 109 110 Recurrent diabetic ketoacidosis is associated with a substantial mortality rate. 111 Frequency of diabetic ketoacidosis increases with higher HbA 1c concentrations and with lower socioeconomic status. 112 Common precipitating factors include newly diagnosed type 1 diabetes, infection, poor adherence to insulin, and an acute cardiovascular event. 109

Euglycemic diabetic ketoacidosis refers to the clinical picture of an increased anion gap metabolic acidosis, ketonemia, or significant ketonuria in a person with diabetes without significant glucose elevation. This can be seen with concomitant use of SGLT-2 inhibitors (currently not indicated in type 1 diabetes), heavy alcohol use, cocaine use, pancreatitis, sepsis, and chronic liver disease and in pregnancy 113 Treatment is similar to that for hyperglycemic diabetic ketoacidosis but can require earlier use and greater concentrations of a dextrose containing fluid for the insulin infusion in addition to 0.9% normal saline resuscitation fluid. 114

The diagnosis of diabetic ketoacidosis has evolved from a gluco-centric diagnosis to one requiring hyperketonemia. By definition, independent of blood glucose, a β-hydroxybutyrate concentration >3 mmol/L is required for diagnosis. 115 However, the use of this ketone for assessment of the severity of the diabetic ketoacidosis is controversial. 116 Bedside β-hydroxybutyrate testing during treatment is standard of care in many parts of the world (such as the UK) but not others (such as the US). Concerns have been raised about accuracy of bedside β-hydroxybutyrate meters, but this is related to concentrations above the threshold for diabetic ketoacidosis. 116

Goals for management of diabetic ketoacidosis include restoration of circulatory volume, correction of electrolyte imbalances, and treatment of hyperglycemia. Intravenous regular insulin infusion is the standard of care for treatment worldwide owing to rapidity of onset of action and rapid resolution of ketonemia and hyperglycemia. As hypoglycemia and hypokalemia are more common during treatment, insulin doses are now recommended to be reduced from 0.1 u/kg/h to 0.05 u/kg/h when glucose concentrations drop below 250 mg/dL or 14 mM. 115 Subcutaneous rapid acting insulin protocols have emerged as alternative treatments for mild to moderate diabetic ketoacidosis. 117 Such regimens seem to be safe and have the advantages of not requiring admission to intensive care, having lower rates of complications related to intravenous therapy, and requiring fewer resources. 117 118 Ketonemia and acidosis resolve within 24 hours in most people. 115 To prevent rebound hyperglycemia, the transition off an intravenous insulin drip must overlap subcutaneous insulin by at least two to four hours. 115

Hypoglycemia

Hypoglycemia, a common occurrence in people with type 1 diabetes, is a well appreciated effect of insulin treatment and occurs when blood glucose falls below the normal range. Increased susceptibility to hypoglycemia from exogenous insulin use in people with type 1 diabetes results from multiple factors, including imperfect subcutaneous insulin delivery tools, loss of glucagon within a few years of diagnosis, progressive impairment of the sympatho-adrenal response with repeated hypoglycemic episodes, and eventual development of impaired awareness. In 2017 the International Hypoglycemia Study Group developed guidance for definitions of hypoglycemia; on the basis of this, a glucose concentration of 3.0-3.9 mmol/L (54-70 mg/dL) was designated as level 1 hypoglycemia, signifying impending development of level 2 hypoglycemia—a glucose concentration <3 mmol/L (54 mg/dL). 119 120 At approximately 54 mg/dL, neuroglycopenic hypoglycemia symptoms, including vision and behavior changes, seizures, and loss of consciousness, begin to occur as a result of glucose deprivation of neurons in the central nervous system. This can eventually lead to cerebral dysfunction at concentrations <50 mg/dL. 121 Severe hypoglycemia (level 3), denoting severe cognitive and/or physical impairment and needing external assistance for recovery, is a common reason for emergency department visits and is more likely to occur in people with lower socioeconomic status and with the longest duration of diabetes. 112 Prevalence of self-reported severe hypoglycemia is very high according to a global population study that included more than 8000 people with type 1 diabetes. 122 Severe hypoglycemia occurred commonly in younger people with suboptimal glycemia according to a large electronic health record database study in the US. 123 Self- reported severe hypoglycemia is associated with a 3.4-fold increase in mortality. 124 125

Acute consequences of hypoglycemia include impaired cognitive function, temporary focal deficits including stroke-like symptoms, and memory deficits. 126 Cardiovascular effects including tachycardia, arrhythmias, QT prolongation, and bradycardia can occur. 127 Hypoglycemia can impair many activities of daily living, including motor vehicle safety. 128 In a survey of adults with type 1 diabetes who drive a vehicle at least once a week, 72% of respondents reported having hypoglycemia while driving, with around 5% reporting a motor vehicle accident due to hypoglycemia in the previous two years. 129 This contributes to the stress and fear that many patients face while grappling with the difficulties of ongoing hypoglycemia. 130

Glucagon is highly efficacious for the primary treatment of severe hypoglycemia when a patient is unable to ingest carbohydrate safely, but it is unfortunately under-prescribed and underused. 131 132 Availability of nasal, ready to inject, and shelf-stable liquid glucagon formulations have superseded the need for reconstituting older injectable glucagon preparations before administration and are now preferred. 133 134 Real time CGM studies have shown a decreased hypoglycemic exposure in people with impaired awareness without a change in HbA 1c . 34 135 136 137 138 CGM has shown benefit in decreasing hypoglycemia across the lifespan, including in teens, young adults, and older people. 36 139 Although CGM reduces the burden of hypoglycemia including severe hypoglycemia, it does not eliminate it; overall, such severe level 3 hypoglycemia rates in clinical trials are very low and hard to decipher in the real world. HCL insulin delivery systems integrated with CGM have been shown to decrease hypoglycemia. Among available rapid acting insulins, ultra-rapid acting lispro (lispro-aabc) seems to be associated with less frequent hypoglycemia in type 1 diabetes. 140 141

As prevention of hypoglycemia is a crucial aspect of diabetes management, formal training programs to increase awareness and education on avoidance of hypoglycemia, such as the UK’s Dose Adjustment for Normal Eating (DAFNE), have been developed. 142 143 This program has shown fewer severe hypoglycemia (mean 1.7 (standard deviation 8.5) episodes per person per year before training to 0.6 (3.7) episodes one year after training) and restoration of recognition of hypoglycemia in 43% of people reporting unawareness. Clinically relevant anxiety and depression fell from 24.4% to 18.0% and from 20.9% to 15.5%, respectively. A structured education program with cognitive and psychotherapeutic aspects for changing hypoglycemia related behaviors, called the Hypoglycemia Awareness Restoration Program despite optimized self-care (HARPdoc), showed a positive effect on changing unhelpful beliefs around hypoglycemia and improved diabetes related and general distress and anxiety scores. 144

Management in under-resourced settings

According to a recent estimate from the International Diabetes Federation, 1.8 million people with type 1 diabetes live in low and middle income countries (LMICs). 2 In many LMICs, the actual burden of type 1 diabetes remains unknown and material resources needed to manage type 1 diabetes are lacking. 145 146 Health systems in these settings are underequipped to tackle the complex chronic disease that is type 1 diabetes. Few diabetes and endocrinology specialist physicians are available owing to lack of specific postgraduate training programs in many LMICs; general practitioners with little to no clinical experience in managing type 1 diabetes care for these patients. 146 This, along with poor availability and affordability of insulin and lack of access to technology, results in high mortality rates. 147 148 149 In developed nations, low socioeconomic status is associated with higher levels of mortality and morbidity for adults with type 1 diabetes despite access to a universal healthcare system. 150 Although global governments have committed to universal health coverage and therefore widespread availability of insulin, it remains very far from realization in most LMICs. 151

Access to technology is patchy and varies globally. In the UST1DX, CGM use was least in the lowest fifth of socioeconomic status. 152 Even where technology is available, successful engagement does not always occur. 153 In a US cohort, lower CGM use was seen in non-Hispanic Black children owing to lower rates of device initiation and higher rates of discontinuation. 154 In many LMICs, blood glucose testing strips are not readily available and cost more than insulin. 151 In resource limited settings, where even diagnosis, basic treatments including insulin, syringes, and diabetes education are limited, use of CGM adds additional burden to patients. Need for support services and the time/resources needed to download and interpret data are limiting factors from a clinician’s perspective. Current rates of CGM use in many LMICs are unknown.

Inequities in the availability of and access to certain insulin formulations continue to plague diabetes care. 155 In developed countries such as the US, rising costs have led to insulin rationing by around 25% of people with type 1 diabetes. 156 LMICs have similar trends while also remaining burdened by disproportionate mortality and complications from type 1 diabetes. 155 157 With the inclusion of long acting insulin analogs in the World Health Organization’s Model List of Essential Medicines in 2021, hope has arisen that these will be included as standard of care across the world. 158 In the past, the pricing of long acting analogs has limited their use in resource poor settings 159 ; however, their inclusion in WHO’s list was a major step in improving their affordability. 158 With the introduction of lower cost long acting insulin biosimilars, improved access to these worldwide in the future can be anticipated. 160

Making insulin available is not enough on its own to improve the prognosis for patients with diabetes in resource poor settings. 161 Improved healthcare infrastructure, better availability of diabetes supplies, and trained personnel are all critical to improving type 1 diabetes care in LMICs. 161 Despite awareness of limitations and barriers, a clear understanding of how to implement management strategies in these settings is still lacking. The Global Diabetes Compact was launched in 2021 with the goal of increasing access to treatment and improving outcomes for people with diabetes across the globe. 162

Emerging technologies and treatments

Monitoring systems.

The ability to measure urinary or more recently blood ketone concentrations is an integral part of self-management of type 1 diabetes, especially during acute illness, intermittent fasting, and religious fasts to prevent diabetic ketoacidosis. 163 Many people with type 1 diabetes do not adhere to urine or blood ketone testing, which likely results in unnecessary episodes of diabetic ketoacidosis. 164 Noting that blood and urine ketone testing is not widely available in all countries and settings is important. 1 Regular assessment of patients’ access to ketone testing (blood or urine) is critical for all clinicians. Euglycemic diabetic ketoacidosis in type 1 diabetes is a particular problem with concomitant use of SGLT-2 inhibitors; for this reason, these agents are not approved for use in these patients. For sick day management (and possibly for the future use of SGLT-2 inhibitors in people with type 1 diabetes), it is hoped that continuous ketone monitoring (CKM) can mitigate the risks of diabetic ketoacidosis. 165 Like CGM, the initial CKM device measures interstitial fluid β-hydroxybutyrate instead of glucose. CKM use becomes important in conjunction with a hybrid closed loop insulin pump system and added SGLT-2 inhibitor therapy, where insulin interruptions are common and hyperketonemia is frequent. 166

Perhaps the greatest technological challenge to date has been the development of non-invasive glucose monitoring. Numerous attempts have been made using strategies including optics, microwave, and electrochemistry. 167 Lack of success to date has resulted in healthy skepticism from the medical community. 168 However, active interest in the development of non-invasive technology with either interstitial or blood glucose remains.

Insulin and delivery systems

In the immediate future, two weekly basal insulins, insulin icodec and basal insulin Fc, may become available. 169 Studies of insulin icodec in type 1 diabetes are ongoing (ONWARDS 6; NCT04848480 ). How these insulins will be incorporated in management of type 1 diabetes is not yet clear.

Currently available AID systems use only a single hormone, insulin. Dual hormone AID systems incorporating glucagon are in development. 170 171 Barriers to the use of dual hormone systems include the need for a second chamber in the pump, a lack of stable glucagon formulations approved for long term subcutaneous delivery, lack of demonstrated long term safety, and gastrointestinal side effects from glucagon use. 74 Similarly, co-formulations of insulin and amylin (a hormone co-secreted with insulin and deficient in people with type 1 diabetes) are in development. 172

Immunotherapy for type 1 diabetes

As our understanding of the immunology of type 1 diabetes expands, development of the next generation of immunotherapies is under active pursuit. Antigen specific therapies, peptide immunotherapy, immune tolerance using DNA vaccination, and regulatory T cell based adoptive transfer targeting β cell senescence are all future opportunities for drug development. Combining immunotherapies with metabolic therapies such as GLP-1 receptor agonists to help to improve β cell mass is being actively investigated.

The quest for β cell replacement methods is ongoing. Transplantation of stem cell derived islets offers promise for personalized regenerative therapies as a potentially curative method that does away with the need for donor tissue. Since the first in vivo model of glucose responsive β cells derived from human embryonic stem cells, 173 different approaches have been attempted. Mesenchymal stromal cell treatment and autologous hematopoietic stem cells in newly diagnosed type 1 diabetes may preserve β cell function without any safety signals. 174 175 176 Stem cell transplantation for type 1 diabetes remains investigational. Encapsulation, in which β cells are protected using a physical barrier to prevent immune attack and avoid lifelong immunosuppression, and gene therapy techniques using CRISPR technology also remain in early stages of investigation.

Until recently, no specific guidelines for management of type 1 diabetes existed and management guidance was combined with consensus statements developed for type 2 diabetes. Table 6 summarizes available guidance and statements from various societies. A consensus report for management of type 1 diabetes in adults by the ADA and European Association for the Study of Diabetes became available in 2021; it covers several topics of diagnosis and management of type 1 diabetes, including glucose monitoring, insulin therapy, and acute complications. Similarly, the National Institute for Health and Care Excellence also offers guidance on management of various aspects of type 1 diabetes. Consensus statements for use of CGM, insulin pump, and AID systems are also available.

Guidelines in type 1 diabetes

Conclusions

Type 1 diabetes is a complex chronic condition with increasing worldwide prevalence affecting several million people. Several successes in management of type 1 diabetes have occurred over the years from the serendipitous discovery of insulin in 1921 to blood glucose monitoring, insulin pumps, transplantation, and immunomodulation. The past two decades have seen advancements in diagnosis, treatment, and technology including development of analog insulins, CGM, and advanced insulin delivery systems. Although we have gained a broad understanding on many important aspects of type 1 diabetes, gaps still exist. Pivotal research continues targeting immune targets to prevent or delay onset of type 1 diabetes. Although insulin is likely the oldest of existing modern drugs, no low priced generic supply of insulin exists anywhere in the world. Management of type 1 diabetes in under resourced areas continues to be a multifaceted problem with social, cultural, and political barriers.

Glossary of abbreviations

ADA—American Diabetes Association

AID—automated insulin delivery

BGM—blood glucose monitoring

CGM—continuous glucose monitoring

CKM—continuous ketone monitoring

DCCT—Diabetes Control and Complications Trial

DIY—do-it-yourself

FDA—Food and Drug Administration

GADA—glutamic acid decarboxylase antibody

GLP-1—glucagon-like peptide 1

GRS—genetic risk scoring

HbA1c—glycated hemoglobin

HCL—hybrid closed loop

LADA—latent autoimmune diabetes of adults

LMIC—low and middle income country

PAKT—pancreas after kidney transplant

RCT—randomized controlled trial

SGLT-2—sodium-glucose cotransporter 2

SPKT—simultaneous pancreas-kidney transplant

Questions for future research

What future new technologies can be helpful in management of type 1 diabetes?

How can newer insulin delivery methods benefit people with type 1 diabetes?

What is the role of disease modifying treatments in prevention and delay of type 1 diabetes?

Is there a role for sodium-glucose co-transporter inhibitors or glucagon-like peptide 1 receptor angonists in the management of type 1 diabetes?

As the population with type 1 diabetes ages, how should management of these people be tailored?

How can we better serve people with type 1 diabetes who live in under-resourced settings with limited access to medications and technology?

How patients were involved in the creation of this manuscript

A person with lived experience of type 1 diabetes reviewed a draft of the manuscript and offered input on important aspects of their experience that should be included. This person is involved in large scale education and activism around type 1 diabetes. They offered their views on various aspects of type 1 diabetes, especially the use of adjuvant therapies and the burden of living with diabetes. This person also raised the importance of education of general practitioners on the various stages of type 1 diabetes and the management aspects. On the basis of this feedback, we have highlighted the burden of living with diabetes on a daily basis.

Series explanation: State of the Art Reviews are commissioned on the basis of their relevance to academics and specialists in the US and internationally. For this reason they are written predominantly by US authors

Contributors: SS and IBH contributed to the planning, drafting, and critical review of this manuscript. FNK contributed to the drafting of portions of the manuscript. All three authors are responsible for the overall content as guarantors.

Competing interests: We have read and understood the BMJ policy on declaration of interests and declare the following interests: SS has received an honorarium from Abbott Diabetes Care; IBH has received honorariums from Abbott Diabetes Care, Lifescan, embecta, and Hagar and research support from Dexcom and Insulet.

Provenance and peer review: Commissioned; externally peer reviewed.

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Research Gaps Around Type 1 Diabetes

A large body of research on Type 2 diabetes has helped to develop guidance, informing how patients are diagnosed, treated, and manage their lifestyle. In contrast, Type 1 diabetes, often mistakenly associated only with childhood, has received less attention.

In this Q&A, adapted from the  April 17 episode of Public Health On Call , Stephanie Desmon speaks to Johns Hopkins epidemiologists  Elizabeth Selvin , PhD '04, MPH, and  Michael Fang , PhD, professor and assistant professor, respectively, in the Department of Epidemiology, about recent findings that challenge common beliefs about type 1 diabetes. Their conversation touches on the misconception that it’s solely a childhood condition, the rise of adult-onset cases linked to obesity, and the necessity for tailored approaches to diagnosis and care. They also discuss insulin prices and why further research is needed on medications like Ozempic in treating Type 1 diabetes.

I want to hear about some of your research that challenges what we have long understood about Type 1 diabetes, which is no longer called childhood diabetes. 

MF: Type 1 diabetes was called juvenile diabetes for the longest time, and it was thought to be a disease that had a childhood onset. When diabetes occurred in adulthood it would be type 2 diabetes. But it turns out that approximately half of the cases of Type 1 diabetes may occur during adulthood right past the age of 20 or past the age of 30.

The limitations of these initial studies are that they've been in small clinics or one health system. So, it's unclear whether it's just that particular clinic or whether it applies to the general population more broadly. 

We were fortunate because the CDC has collected new data that explores Type 1 diabetes in the U.S. Some of the questions they included in their national data were, “Do you have diabetes? If you do, do you have Type 1 or Type 2? And, at what age were you diagnosed?”

With these pieces of information, we were able to characterize how the age of diagnosis of Type 1 diabetes differs in the entire U.S. population.

Are Type 1 and Type 2 diabetes different diseases?

ES:  They are very different diseases and have a very different burden. My whole career I have been a Type 2 diabetes epidemiologist, and I’ve been very excited to expand work with Type 1 diabetes.

There are about 1.5 million adults with Type 1 diabetes in the U.S., compared to 21 million adults with Type 2 diabetes. In terms of the total cases of diabetes, only 5 to 10 percent have Type 1 diabetes. Even in our largest epidemiologic cohorts, only a small percentage of people have Type 1 diabetes. So, we just don't have the same national data, the same epidemiologic evidence for Type 1 diabetes that we have for Type 2. The focus of our research has been trying to understand and characterize the general epidemiology and the population burden of Type 1 diabetes.

What is it about Type 1 that makes it so hard to diagnose?

MF: The presentation of symptoms varies by age of diagnosis. When it occurs in children, it tends to have a very acute presentation and the diagnosis is easier to make. When it happens in adulthood, the symptoms are often milder and it’s often misconstrued as Type 2 diabetes. 

Some studies have suggested that when Type 1 diabetes occurs in adulthood, about 40% of those cases are misdiagnosed initially as Type 2 cases. Understanding how often people get diagnosed later in life is important to correctly diagnose and treat patients. 

Can you talk about the different treatments?

MF:  Patients with Type 1 diabetes are going to require insulin. Type 2 diabetes patients can require insulin, but that often occurs later in the disease, as oral medications become less and less effective.

ES: Because of the epidemic of overweight and obese in the general population, we’re seeing a lot of people with Type 1 diabetes who are overweight and have obesity. This can contribute to issues around misdiagnosis because people with Type 1 diabetes will have signs and will present similarly to Type 2 diabetes. They'll have insulin resistance potentially as a result of weight gain metabolic syndrome. Some people call it double diabetes—I don't like that term—but it’s this idea that if you have Type 1 diabetes, you can also have characteristics of Type 2 diabetes as well.

I understand that Type 1 used to be considered a thin person's disease, but that’s not the case anymore.  MF:  In a separate paper, we also explored the issue of overweight and obesity in persons with Type 1 diabetes. We found that approximately 62% of adults with Type 1 diabetes were either overweight or obese, which is comparable to the general U.S. population.

But an important disclaimer is that weight management in this population [with Type 1 diabetes] is very different. They can't just decide to go on a diet, start jogging, or engage in rigorous exercise. It can be a very, very dangerous thing to do.

Everybody's talking about Ozempic and Mounjaro—the GLP-1 drugs—for diabetes or people who are overweight to lose weight and to solve their diabetes. Where does that fit in with this population?

ES: These medications are used to treat Type 2 diabetes in the setting of obesity. Ozempic and Mounjaro are incretin hormones. They mediate satiation, reduce appetite, slow gastric emptying, and lower energy intake. They're really powerful drugs that may be helpful in Type 1 diabetes, but they're  not approved for the management of obesity and Type 1 diabetes. At the moment, there aren't data to help guide their use in people with Type 1 diabetes, but I suspect they're going to be increasingly used in people with Type 1 diabetes.

MF:   The other piece of managing weight—and it's thought to be foundational for Type 1 or Type 2—is dieting and exercising. However, there isn’t good guidance on how to do this in persons with Type 1 diabetes, whereas there are large and rigorous trials in Type 2 patients. We’re really just starting to figure out how to safely and effectively manage weight with lifestyle changes for Type 1 diabetics, and I think that's an important area of research that should continue moving forward.

ES: Weight management in Type 1 diabetes is complicated by insulin use and the risk of hypoglycemia, or your glucose going too low, which can be an acute complication of exercise. In people with Type 2 diabetes, we have a strong evidence base for what works. We know modest weight loss can help prevent the progression and development of Type 2 diabetes, as well as weight gain. In Type 1, we just don't have that evidence base.

Is there a concern about misdiagnosis and mistreatment? Is it possible to think a patient has Type 2 but they actually have Type 1? 

MF: I think so. Insulin is the overriding concern. In the obesity paper, we looked at the percentage of people who said their doctors recommended engaging in more exercise and dieting. We found that people with Type 1 diabetes were less likely to receive the same guidance from their doctor. I think providers may be hesitant to say, “Look, just go engage in an active lifestyle.”

This is why it's important to have those studies and have that guidance so that patients and providers can be comfortable in improving lifestyle management.

Where is this research going next?

ES:  What's clear from these studies is that the burden of overweight and obesity is substantial in people with Type 1 diabetes and it's not adequately managed. Going forward, I think we're going to need clinical trials, clear clinical guidelines, and patient education that addresses how best to tackle obesity in the setting of Type 1 diabetes.

It must be confusing for people with Type 1 diabetes who are   hearing about people losing all this weight on these drugs, but they go to their doctor who says, “Yeah, but that's not for you.”

ES: I hope it's being handled more sensitively. These drugs are being used by all sorts of people for whom they are not indicated, and I'm sure that people with Type 1 diabetes are accessing these drugs. I think the question is, are there real safety issues? We need thoughtful discussion about this and some real evidence to make sure that we're doing more good than harm.

MF:  Dr. Selvin’s group has published a paper, estimating that about 15% of people with Type 1 diabetes are on a GLP-1. But we don't have great data on what potentially can happen to individuals.

The other big part of diabetes that we hear a lot about is insulin and its price. Can you talk about your research on this topic?

MF:  There was a survey that asked, “Has there been a point during the year when you were not using insulin because you couldn’t afford it?” About 20% of adults under the age of 65 said that at some point during the year, they couldn't afford their insulin and that they did engage in what sometimes is called “cost-saving rationing” [of insulin].

Medicare is now covering cheaper insulin for those over 65, but there are a lot of people for whom affordability is an issue. Can you talk more about that? 

MF:  The fight is not over. Just because there are national and state policies, and now manufacturers have been implementing price caps, doesn't necessarily mean that the people who need insulin the most are now able to afford it. 

A recent study in the  Annals of Internal Medicine looked at states that adopted or implemented out-of-pocket cost caps for insulin versus those that didn't and how that affected insulin use over time. They found that people were paying less for insulin, but the use of insulin didn't change over time. The $35 cap is an improvement, but we need to do more.

ES: There are still a lot of formulations of insulin that are very expensive. $35 a month is not cheap for someone who is on insulin for the rest of their lives.

• Overweight and Obesity in People With Type 1 Diabetes Nearly Same as General Population
• The Impacts of COVID-19 on Diabetes and Insulin
• Why Eli Lilly’s Insulin Price Cap Announcement Matters

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Precision medicine in type 1 diabetes

• Open access
• Published: 22 August 2022
• Volume 65 , pages 1854–1866, ( 2022 )

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• Alice L. J. Carr   ORCID: orcid.org/0000-0003-0704-8843 1 ,
• Carmella Evans-Molina   ORCID: orcid.org/0000-0001-7764-8663 2 , 3 , 4 , 5 , 6 , 7 , 8 &
• Richard A. Oram   ORCID: orcid.org/0000-0003-3581-8980 1  

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First envisioned by early diabetes clinicians, a person-centred approach to care was an aspirational goal that aimed to match insulin therapy to each individual’s unique requirements. In the 100 years since the discovery of insulin, this goal has evolved to include personalised approaches to type 1 diabetes diagnosis, treatment, prevention and prediction. These advances have been facilitated by the recognition of type 1 diabetes as an autoimmune disease and by advances in our understanding of diabetes pathophysiology, genetics and natural history, which have occurred in parallel with advancements in insulin delivery, glucose monitoring and tools for self-management. In this review, we discuss how these personalised approaches have improved diabetes care and how improved understanding of pathogenesis and human biology might inform precision medicine in the future.

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Introduction

The year 2022 marks the 100th year since the first patient received insulin. Frederick Banting, Charles Best and James Collip’s transformative discovery of insulin in 1921 has given millions of individuals with type 1 diabetes a second chance at life. Over the ensuing 100 years, type 1 diabetes has evolved from a once inevitable death sentence into a manageable, chronic condition. This evolution has been facilitated by improvements in insulin formulations and insulin delivery, advancements in the convenience, frequency and accuracy of glucose measurement, and the development and application of tools and guidance for lifestyle and dietary management. In parallel, knowledge and understanding of type 1 diabetes pathogenesis have advanced considerably, offering the prospect of therapies that intervene in disease pathogenesis to prevent, reverse or delay the progression of beta cell loss. In this review we describe how advancements in our understanding of type 1 diabetes pathophysiology and treatment have revolutionised clinical care and improved the person-centred approach envisioned by early diabetes clinicians.

The 1920s marked a new era for people living with type 1 diabetes, with insulin injections effectively preventing death from severe insulin deficiency. However, with little understanding of the pathophysiology of diabetes development and no differentiation of disease ‘subtypes’, standards of care remained largely the same for all patients diagnosed with diabetes. Early into this post-insulin era, it was recognised that diabetes is a chronic illness and that treatment would involve the lifelong combination of insulin regimens with diet, exercise and infection protocols [ 1 ]. These medical insights were disseminated to both patients and clinicians in manuals on diabetes. One of the first and most detailed manuals to incorporate insulin treatment was developed by Elliot Joslin in 1924 [ 2 ]. This manual, which encompassed all knowledge required by those living with diabetes and by their clinicians, covered urinalysis using Benedict’s test for glucose monitoring, administration of insulin, nutritional statistics for a variety of foods, and information on how to treat diabetes with insulin and diet. Joslin was prescient in recognising that treatment regimens should be adjusted to an individual’s needs, stating in 1924 that ‘The treatment of a patient with diabetes lasts through life. Treatment therefore must be adjusted to the condition of the patient and should be so arranged that it can be continued for years, not only without harm, but with as little annoyance and interference with the daily routine as is possible. Consequently, the patient must be taught the nature of his disease and how to conquer it’ [ 1 , 2 ]. Arguably, Joslin recognised the need for personalised diabetes treatments and the empowerment of those affected. He realised that patients must be taught the tools for self-management to both prolong life and improve the quality of life for those living with diabetes. This idea of a person-centred approach to care expanded quickly into a variety of treatment regimens.

An in-depth knowledge of type 1 diabetes pathogenesis is critical to understanding how precision medicine may apply to type 1 diabetes. In the early 1930s it was noticed that people with diabetes responded differently to insulin, enabling the differentiation between insulin-insufficient and insulin-sensitive subgroups [ 3 , 4 ]. However, it was not until the 1950s that this observation was confirmed using the first insulin assays, which enabled quantification of circulating insulin in humans [ 5 , 6 , 7 ]. From this point, different types of diabetes were considered, but the aetiological basis of the insulin-deficient disease type was not identified as autoimmune in origin until later, with Willy Gepts reporting evidence of immunological infiltrates in the pancreases of newly diagnosed children with diabetes in 1965 [ 8 ], which was reinforced by the identification of islet cell autoantibodies by Franco Bottazzo in 1974 [ 9 ].

These discoveries formed the foundation of our contemporary understanding of the pathophysiology of type 1 diabetes. The scientific community was quick to accept this paradigm shift, which led to huge advancements in our understanding of the underlying aetiology of type 1 diabetes within the space of a few years. Coincident with these discoveries, clinical observations of familial inheritance of diabetes led to the proposal in the 1950s of a partial genetic basis of diabetes development [ 10 ]. Twin studies in children and young adults in the late 1960s and early 1970s reported around 50% concordance of diabetes in monozygotic pairs (presumed to be type 1 diabetes) compared with >90% concordance of diabetes in those diagnosed at older ages (presumed to be type 2 diabetes) [ 11 , 12 , 13 ]. In addition to these findings, descriptions of the critical role of HLA antigen-presentation genes in the transplant setting led to the association of these genes with autoimmune diseases [ 13 , 14 ]. Identification of HLA associations, combined with the discovery of islet cell autoantibodies, established that these genes transmitted the tendency to develop type 1 diabetes, but not the disease itself [ 14 ]. These findings were summarised by George Eisenbarth in 1986 in the widely adopted Eisenbarth model, which outlined that genetically predisposed individuals encounter a hypothetical triggering event that begins a process of autoimmune-mediated progressive beta cell destruction leading to insulin deficiency [ 15 ].

The Eisenbarth model continues to inform strategies for disease prevention and, more recently, precision medicine approaches. The model was updated by Insel and colleagues in 2015 [ 16 ] based on a landmark meta-analysis of several birth cohorts which showed that >80% of children who develop two or more islet-specific autoantibodies progress to type 1 diabetes by the age of 20 [ 17 ]. It is now recognised that there are three distinct stages of type 1 diabetes that precede clinical diagnosis: stage 1, when islet autoimmunity is measurable by the presence of multiple autoantibodies; stage 2, when there is measurable dysglycaemia; and stage 3, when glucose abnormalities fulfil criteria for clinical diagnosis of diabetes. Summarised in Fig. 1 , these three stages have each seen an expansion of increasingly precise approaches encompassing the prediction, prevention, diagnosis and treatment of type 1 diabetes. Individualised prediction is enabling the early diagnosis and prevention of stage 2 diabetes progression, and for those with established stage 3 diabetes there are a multitude of approaches that can be tailored in order to optimise care for the individual, with many more precise approaches, methods and treatments on the horizon.

The Eisenbarth model continues to inform strategies for disease prevention and, more recently, precision medicine approaches. Using its most up-to-date form, which describes the stages of type 1 diabetes proposed by Insel and colleagues [ 16 ], this figure addresses precision medicine approaches that are, or could be, used at each stage of the model. Beginning in the predisposition phase, we see a future of precision prediction in the form of genetic screening programmes. In stage 1 disease, where autoimmunity begins, and entering into stage 2, current precision prevention options are limited. Screening for autoantibodies in those at high risk is a current helpful option for identifying early disease, with ongoing and future efforts focusing on better identification of these stages and early intervention therapeutics. Around diagnosis, current methods for the precise classification of type 1 diabetes, such as C-peptide measurements and classification models that use a combination of biomarkers, can enable the correct application of precision treatment in type 1 diabetes. In stage 3 overt diabetes, a number of therapies, including advanced technology and education programmes, are already employed in clinical care, with immune and stem cell replacement therapies on the horizon. This figure is available as part of a downloadable slideset

There is momentum in the field of diabetes to take advantage of ‘recent, rapid scientific advances in our ability to measure and characterise human variation through (1) assessment of the genetic and metabolic state, (2) leveraging data to inform disease categories, and (3) science-guided preventive and treatment decisions tailored to specific pathological conditions’ [ 18 ]. The ADA and EASD have partnered to assess the current state of precision medicine in diabetes through a series of systematic reviews across diabetes types, with the aim of understanding the role of precision medicine in diagnosis, subcategorisation, prevention and therapy. The bedrock of good clinical care relies on the human- and person-centred approach advocated by Joslin [ 2 ]; however, there are opportunities to take advantage of the increasing understanding of type 1 diabetes pathogenesis to better intervene. Throughout this review we discuss the current diagnostic, treatment and management strategies for people with type 1 diabetes and, with forethought, discuss how the concept of precision medicine can be applied to type 1 diabetes.

Identification of longitudinal biomarkers in the form of islet-specific autoantibodies in large studies of at-risk individuals (either from genetically high-risk infants from birth or first-degree relatives of people with type 1 diabetes [ 19 ]) has increased our understanding of the progression to type 1 diabetes and improved the prediction of future type 1 diabetes development. Historically, the at-risk population was identified using HLA typing of type 1 diabetes risk-associated HLA alleles ( HLA-DR3-DQ2 and/or HLA-DR4-DQ8 , with avoidance of strong protective alleles such as HLA-DR15-DQ6 ) or by identifying infants or adults at risk because of an affected family member [ 20 ]. Recent advances in genome-wide association studies and the identification of numerous common variants associated with type 1 diabetes have facilitated the combination of HLA and non-HLA genetic risk into polygenic or genetic risk scores that can be used to aid prediction and/or classification of disease. These technological advances allow for the possibility of performing cheap and efficient genetic screening at birth to identify individuals at risk for developing type 1 diabetes [ 21 , 22 ]. The increasing integration of genomics into healthcare means it is realistic that, in the future, type 1 diabetes genetic risk may be measurable from birth.

While genetics can identify at-risk individuals, the majority of those classified as ‘high risk’ will probably not develop type 1 diabetes because of the relatively low background prevalence of this disease [ 23 ]. Islet-specific autoantibodies are a more specific measure of the development of autoimmunity, and the presence of islet autoantibodies forms the basis of the recently revised type 1 diabetes staging paradigm [ 16 ]. Combined analysis of large screening studies may allow for the targeted measurement of islet-specific autoantibodies at key time points during childhood to provide maximum sensitivity and specificity for identifying future type 1 diabetes cases, possibly by integrating screening with other early life healthcare visits [ 24 , 25 ]. The major biomarkers currently used in predicting future type 1 diabetes development include genetics, age, number, types and titres of autoantibodies and age at which these appear, dysglycaemia and C-peptide levels. These markers can be used individually but provide more predictive power when used in combination [ 26 ]. In the future, the increasing availability of genetic information, combined with the proven ability of autoantibody screening to identify early-stage type 1 diabetes, may lead to an era of precision prediction in which we are able to predict type 1 diabetes and intercept before and prevent or delay disease onset.

Many groups are working to improve the precision prediction of type 1 diabetes using novel biomarker and ‘omics’ approaches [ 27 ], including advanced omic, single cell and advanced imaging analysis of pancreatic tissue from organ donors with autoantibody positivity and established type 1 diabetes [ 28 , 29 , 30 , 31 ]. We are now able to study the complex environmental, metabolomic, virome, molecular and microbiome associations in type 1 diabetes progression. A large number of association studies have highlighted the complex interplay between immune abnormalities, genetics and the environment [ 32 , 33 , 34 ]. We now have more markers of beta cell stress and dysfunction and increasing evidence of the complex interplay between the environment, beta cells and the immune system. It is possible that these detailed molecular approaches and the application of novel computational approaches that are better able to integrate multiple features may aid with prediction over and beyond current strategies. It is equally important and likely that further mechanistic insights from these approaches may help identify targets for intervention.

Recognition of type 1 diabetes as an autoimmune disease led to attempts at treating the underlying pathogenesis with immunotherapy. Clinical trials that aimed to prevent the progression of early diabetes initially used steroids, such as prednisone [ 35 ], in combination with azathioprine [ 36 ], anti-thymocyte globulin [ 37 ] and ciclosporin [ 38 ]. Recently, clinical trials have focused on more selective immune agents, such as the anti-CD3 antibody teplizumab [ 39 ] and agents thought to act directly on beta cells (e.g. verapamil) [ 40 , 41 ]. There have been some recent notable successes of agents, including rituximab [ 42 ], teplizumab [ 43 , 44 ], golimumab [ 45 ] and anti-thymocyte globulin [ 46 ], tested closer to the onset of stage 3 diabetes. However, none of these agents has led to durable disease remission, and these successes have been against the backdrop of several unsuccessful trials [ 47 , 48 ]. The findings suggest that there may be irremediable loss of beta cell mass and function after the onset of stage 3 diabetes. To address whether earlier intervention may be more efficacious, teplizumab was tested as a single 14-day course in individuals with two or more autoantibodies and dysglycaemia. In this context, teplizumab delayed the onset of stage 3 disease by a median of 32.5 months [ 39 ]. Teplizumab is currently under consideration by the US Food and Drug Administration as the first potential disease-modifying therapy in diabetes, following nearly three decades of preclinical and clinical studies.

While the teplizumab trial in stage 2 disease showed that earlier intervention is a promising approach and that it is possible to delay the onset of clinical disease in some high-risk individuals, there was still considerable heterogeneity in response noted among trial participants. These findings raise the possibility that there may be subgroups of individuals who require different treatment approaches and that heterogeneity in disease progression may be driven by underlying differences in pathophysiology or endotypes. A disease endotype is broadly defined as a subtype of disease originating from a distinct functional or pathobiological mechanism that can be addressed therapeutically [ 49 ]. This concept was pioneered in the field of asthma, where distinct endotypes have been defined and targeted therapeutically [ 50 ]. However, it is currently not clear whether individuals with type 1 diabetes are ‘more similar than they are different’ and require similar disease-modifying treatments or whether factors such as islet autoimmunity, age at diagnosis and immune phenotype will lead to distinct interventions. Tailored treatments would greatly benefit patients; however, further subdivisions of type 1 diabetes would risk reducing the market for pharmaceutical companies, which already struggle to see a large enough market to invest significantly in type 1 diabetes research.

Notwithstanding this controversy, several recent observations hold promise in identifying type 1 diabetes endotypes. It is well accepted that children and adults exhibit differences in disease progression [ 51 , 52 , 53 ], with children having a higher risk of developing diabetes and a more accelerated rate of progression from seroconversion to stage 3 diabetes [ 17 ]. Along these lines, there are important differences in islet immune cell infiltrates and proinsulin processing, which are correlative with age at diagnosis [ 54 , 55 ]. In addition, evidence from multiple birth cohort studies suggest that progression from first autoantibody development may differ by age of onset. Antibody specificity and background genetics have yet to be directly connected to post-diagnosis progression [ 56 ]. Furthermore, a very recent analysis by Achenbach and colleagues identified multiple variables that classified young type 1 diabetes patients into seven islet autoantibody-positive and three islet autoantibody-negative subgroups. These subgroups demonstrated substantial differences in pathogenic and prognostic outcomes, which could have therapeutic relevance [ 57 ]. Machine learning approaches have also been helpful in identifying autoantibody and disease trajectories [ 58 ]. An important future aspiration will be to design experiments that further investigate the mechanisms of possible age-influenced variation in progression to diabetes, pathogenesis at a tissue level, immune phenotype and progression of beta cell loss post diagnosis.

The correct classification of diabetes subtype is crucial for the correct application of precision treatment in type 1 diabetes and for the investigation of diabetes pathogenesis. There is considerable evidence of misclassification of type 1 diabetes as type 2 diabetes, and misclassification of monogenic diabetes and type 2 diabetes as type 1 diabetes [ 59 , 60 ]. A correct diagnosis is important to determine the appropriate treatment, with type 1 diabetes requiring physiological doses of insulin replacement to avoid acute life-threatening complications such as diabetic ketoacidosis. Up to one in three adults with type 1 diabetes are initially diagnosed as having type 2 diabetes [ 60 ]. Thus, it is apparent that historical approaches to classification have been unable to provide simple criteria to aid in diagnosis and there is room to use more precise methods of classification. Clinical features are predominately used for classification of diabetes type, with age at diagnosis and BMI having evidence of clinical utility at onset [ 61 ]. However, features frequently overlap in adults diagnosed with diabetes, and the high prevalence of type 2 diabetes adds to the difficulty of confirming a diagnosis of type 1 diabetes in adults. Islet autoantibodies can assist in classification, and recent guidance from the ADA and EASD recommend islet autoantibody testing at diagnosis in all adults with clinically suspected type 1 diabetes [ 62 ]. More recently, type 1 diabetes genetic risk scores have also been shown to assist in discriminating between type 1, type 2 and other forms of diabetes in research settings [ 63 , 64 ]. Recent work has shown that these clinical features and biomarkers are most discriminative of diabetes type when combined and modelled as continuous variables in diagnostic models [ 61 , 63 , 65 ].

Rapid progression to insulin deficiency, a major feature of type 1 diabetes, determines treatment and can be used to aid in classification. A marker of endogenous insulin secretion is the level of serum or urine C-peptide, which is co-secreted in equimolar amounts with insulin and has little assay cross-reactivity with exogenous insulin or proinsulin [ 66 , 67 ]. Severe insulin deficiency not only is a biomarker of type 1 diabetes but also, by definition, indicates a need for insulin replacement, thereby linking treatment to pathogenesis [ 68 ]. C-peptide testing in those with clinically diagnosed type 1 diabetes can lead to reclassification and insulin withdrawal [ 59 ]. In addition, C-peptide measured within the first few years of diagnosis may be useful in confirming type 1 diabetes if results indicate severe insulin deficiency (e.g. fasting level <80 pmol/l or post-meal level <200 pmol/l [ 68 ]), as those with either type 2 diabetes or monogenic diabetes almost always have C-peptide levels above these cut-offs. However, C-peptide levels at diagnosis of type 1 diabetes can overlap with those observed in other diabetes types. Instead, the progressive trajectory of C-peptide loss over the immediate years post diagnosis most clearly separates type 1 diabetes from type 2 diabetes, and the utility of C-peptide levels in discriminating type 1 diabetes is greatest 3–5 years post diagnosis [ 68 ]. Recent progress in the ability to measure C-peptide in clinical and remote settings [ 69 , 70 , 71 , 72 ] has facilitated the integration of C-peptide measurement into national and international diabetes guidelines [ 62 ].

Gradual improvements in the formula and delivery of insulin have allowed for significant steps forward in the ability to personalise insulin therapy. Although lifesaving, the insulin preparations of the 1920s were basic and the glucose-lowering effects lasted for only 6 h, thus requiring multiple injections throughout the day. Longer-acting insulins were developed in 1936 through combination of insulin with protamine and then zinc [ 73 , 74 ]. The discovery of the sequence and structure of insulin, the synthesis of the first synthetic human insulin and the emergence of recombinant DNA technology led to the manufacture of insulins with modifiable properties. These advances eventually gave rise to analogue insulins, which dominate the market today and allow for optimisation of absorption rate, time to peak and duration of action depending on their design. The landmark DCCT was published in 1993 and demonstrated the benefit of intensive insulin therapy and tight glycaemic control for the prevention of microvascular complications [ 75 , 76 ]. Thus, newer insulin formulations with optimised pharmacokinetics were a welcome addition, as ‘tight glucose control’ became the goal for all individuals in the post-DCCT era. In current practice, clinicians and patients can choose from a range of insulins that can be employed in various regimens to suit an individual’s needs and lifestyle.

The pace of development of additional tools to aid in diabetes management has been rapid since the end of the DCCT. Flash glucose monitoring and continuous glucose monitoring (CGM) involve sensors that measure glucose levels in interstitial fluid every 5–15 min, providing more detailed, daily insights into glucose control beyond that of the 3- to 4-month estimate HbA 1c provides. Traditional CGM displays trends and data automatically to the user, while flash CGM requires the user to swipe a sensor with a reader to display blood glucose data. Both methods provide several quantitative measures such as glycaemic variability and time spent above (hyperglycaemia), below (hypoglycaemia) and within clinically defined glucose ranges. Unlike HbA 1c measurements and self-monitoring of blood glucose, flash and CGM technologies enable the communication of real-time glucose values, trends and glycaemic variability. These individualised evaluations have been shown to improve HbA 1c levels, decrease the time spent in hyperglycaemia and hypoglycaemia and reduce the risk of severe hypoglycaemia [ 77 , 78 , 79 , 80 ], while also improving quality of life [ 81 ]. Adoption of these technologies as standard of care for all patients with type 1 diabetes, as proposed in the recent updates to the UK’s National Institute for Health and Care Excellence (NICE) guidelines [ 82 , 83 ], represents a much-needed shift toward viewing technology as an integral part of diabetes management. Although HbA 1c measurement remains the most robust and validated measurement associated with chronic diabetes complications, insights from studies using CGM suggest that HbA 1c is unsuitable for determining short-term glycaemic changes accurately [ 84 , 85 , 86 ]. Recent efforts to examine the relationship between CGM-derived time within target glucose range and long-term complications are providing a basis for glycaemic targets for newer glucose monitoring technologies [ 62 , 87 ].

In addition to improvements in glucose monitoring, the last decade has seen rapid improvements in insulin delivery systems. Continuous subcutaneous insulin infusion systems have demonstrated a small but significant benefit for glycaemic control over that of the traditional multiple daily injection method [ 88 ]. However, despite these advances in insulin analogues and delivery systems and glucose sensors, many people with type 1 diabetes still do not achieve glycaemic targets. More recent advances in insulin delivery systems and their integration with CGM technology has enabled automated ongoing adjustment of insulin delivery to optimise glycaemic control throughout the day and night. These ‘closed-loop’ and artificial pancreas systems have been evaluated in children and adolescents and demonstrate improved glucose control and reduced risk of hypoglycaemic events [ 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 ], even compared with sensor-augmented insulin pumps [ 97 ].

Although insulin replacement is essential, it is important to recognise the role that education strategies have in enabling precision treatment in type 1 diabetes. The first of these individualised treatments was the diet regimen developed by Robert Lawrence in 1925 [ 98 ]. Lawrence’s ‘line ration scheme’ was designed to be flexible for patients and manageable for clinicians and remained engrained in care as late as the 1950s [ 99 ]. Today, this education scheme has evolved into the well-established Dose Adjustment for Normal Eating (DAFNE) programme, which was developed originally in the 1990s in Germany [ 100 ] and which was endorsed by the UK NHS [ 101 ]. For adults, this programme is an educational tool to enable individuals to understand the carbohydrate content of foods and the correct insulin dosing and apply this to their lifestyle. In addition, the programme covers insulin management during exercise, illness and social activities. It is recognised that patients and clinicians need more in-depth educational strategies that cover the management of behavioural aspects associated with type 1 diabetes, most notably exercise. People with type 1 diabetes face several barriers to exercise; however, ‘lack of knowledge’ is one of the most expressed concerns [ 102 ]. Employing educational strategies is crucial in enabling the personalised treatment of type 1 diabetes by allowing patients to drive the management of their disease.

Even with the availability of optimised insulins, new technologies for insulin delivery and glucose monitoring and improved tools for self-management, it is acknowledged that care may differ across a person’s lifespan. This is reflected in recent statements surrounding the individualisation of glycaemic targets. It has been rightfully proposed that the glycaemic target ‘should be individualised considering factors that include duration of diabetes, age and life expectancy, comorbid conditions, known cardiovascular disease or advanced microvascular complications, impaired awareness of hypoglycaemia (IAH) and other individual considerations, and it may change over time’, emphasising that this goal should be achieved in conjunction with an understanding of a person’s psychosocial needs and a reduction in diabetes distress [ 62 ]. In addition, specific glycaemic targets are recommended at certain life stages. In particular, women with type 1 diabetes are supported to achieve blood glucose ranges close to those seen in pregnant women without diabetes (HbA 1c ≤48 mmol/mol [≤6.5%]) in addition to focused pre- and postprandial glucose targets, in order to reduce the risk of serious adverse pregnancy outcomes [ 62 , 103 , 104 ]. In older adults, safety of insulin use takes precedence, because of their increased vulnerability to hypoglycaemia, with targets based on functional status and life expectancy and adjusted to minimise the occurrence of hypoglycaemic events [ 62 ].

Risk of hypoglycaemia is perhaps the largest barrier to intensive diabetes control and is often reported as having a profound impact on quality of life and diabetes self-care behaviours [ 105 , 106 ]. Additionally, it is possible that fear of hypoglycaemia is a driver of glycaemic variability and suboptimal glucose control. Although there is evidence that closed-loop insulin therapy is beneficial for glycaemic control, with growing evidence that these benefits extend psychosocially [ 107 , 108 ], some challenges remain. Exercise presents a particular challenge in closed-loop therapy because of the complex glucose physiology that occurs during exercise, with increased glucose turnover and distinct hormonal and metabolic responses to different forms of exercise [ 109 , 110 ]. Compounded by the lag time of current glucose sensing [ 111 , 112 ], closed-loop systems that manage exercise without the risk of hypoglycaemia [ 109 , 113 , 114 ] have not yet been achieved.

It is possible that C-peptide measurement may have a role beyond disease classification in precision clinical care, especially in identifying those most likely to achieve restrictive glycaemic targets. Much as behavioural factors influence glucose levels, the biological factor of preserved endogenous insulin also plays a crucial role in glucose control; however, it is not always considered in clinical care. Numerous studies of endogenous insulin production in people with type 1 diabetes highlight the variation in absolute levels of C-peptide both at diagnosis and in long-duration type 1 diabetes [ 51 , 52 , 53 , 115 , 116 , 117 , 118 ]. Additionally, there is heterogeneity of normal development and endowment of beta cells, in the rate of autoimmune destruction of beta cells and in whether autoimmune destruction progresses to complete loss of insulin-producing beta cells [ 51 , 52 , 53 , 54 , 55 , 115 , 116 , 117 , 118 , 119 , 120 , 121 , 122 ]. There is longstanding and emerging evidence that the amount of persistent endogenous insulin a person with type 1 diabetes maintains influences their glycaemic control, risk of hypoglycaemia and risk of long-term complications across the duration of disease [ 75 , 76 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 ]. Although the key and initial analysis of the DCCT demonstrated the benefit of intensive insulin therapy and tight glycaemic control for the prevention of long-term diabetes complications [ 75 , 76 ], it came at the cost of higher risk of severe hypoglycaemia (self-reported) in those who received intensive insulin therapy, a barrier to intensive insulin therapy that remains today despite improvements in insulin formulations. However, those who retained the ability to secrete higher levels of C-peptide in response to a stimulus demonstrated a significant reduction in the risk of severe hypoglycaemia in addition to decreased retinopathy and nephropathy progression [ 75 , 76 , 123 ]. Increasing numbers of observational studies support these findings [ 125 , 126 , 127 , 128 , 129 , 130 ], with the evidence for persistent endogenous insulin reducing hypoglycaemic risk being most apparent in the setting of islet transplantation, where those at high hypoglycaemia risk commonly have a dramatic reduction of this risk with even modest levels of graft function post transplant. Additionally, the increased use and availability of flash glucose monitoring and CGM has highlighted that there are similar benefits for glycaemic variability and control of persistent C-peptide levels over all durations of diabetes [ 126 , 127 , 131 ]. Routine measurement of C-peptide could aid in understanding the differences in glucose patterns between individuals, regardless of diabetes management behaviours. Incorporation of C-peptide measurements into the standard of care could be an effective approach to supporting newly diagnosed patients by enabling the personalisation of care from the point of diagnosis, which could be expanded across the duration of diabetes. The importance of maintaining C-peptide levels also underlies clinical trial efforts focused on the preservation of beta cell function in those with and at risk of diabetes.

Finally, it is important to recognise that type 1 diabetes is not just a disease of beta cells, as beta cell destruction impacts paracrine interactions within the islet, leading to impairments in the normal secretory patterns of other islet hormones that are critical for glucose homeostasis. In the future, it is possible that the increasing ease with which C-peptide and other islet-associated and glucose-regulating hormones can be measured may allow a more accurate description of an individual’s ability to buffer changes in blood glucose. Moreover, it is possible that the integration of other hormones, such as glucagon, into dual-hormone systems will allow for better management of activities such as exercise that have a high risk for hypoglycaemia [ 132 ]. These insights, combined with precision glucose measurements from CGM, will contribute to disease management in terms of lifestyle changes, additional non-insulin medications, and choice of monitoring and insulin administration.

Contemporary diabetes technologies could be considered a gateway for precision medicine in type 1 diabetes, as they enable treatment to be continually adjusted to the condition of the patient, just as Joslin had hoped. However, a number of barriers remain. New technologies are not accessible to everyone because of their cost. This global disparity in the availability of therapies is one of the main barriers to enabling precision treatment in type 1 diabetes. While closed-loop systems provide significant improvements in insulin delivery and glucose monitoring, thus improving glycaemic control and reducing the daily burden of living with diabetes, there are ongoing challenges related to their implementation and they are not yet able to provide an ‘attach and forget’ solution. Furthermore, a diagnosis of diabetes still imposes additional responsibilities and requires planning and self-monitoring. Such a marked readjustment of daily life is inevitably physically and psychologically draining [ 133 ]. Depression levels among adults with type 1 diabetes are higher than in the general population [ 134 ]. Distinct from depression, diabetes distress [ 135 , 136 ] is also common in diabetes [ 137 ] and is a product of emotional adjustment to the demands of diabetes. Diabetes distress has been found to be significantly associated with higher HbA 1c levels [ 138 ], with a recent study demonstrating that this was pronounced in youth of lower socioeconomic status and/or racial and ethnic minority youth [ 139 ]. Although there are established measures of diabetes distress, including the Problem Areas in Diabetes scale [ 140 ] and the Diabetes Distress Scale [ 141 ], these emotional issues are frequently not integrated into care. The recognition and understanding of emotional issues in diabetes care is a crucial step towards a person-centred and collaborative approach to care [ 133 ]. The recently updated ADA Standards of Medical Care encourage providers to assess symptoms of diabetes distress, depression, anxiety, disordered eating and cognitive capacities using appropriate standardised and validated tools at the initial visit, at periodic intervals and when there is a change in disease, treatment or life circumstance [ 142 ]. Integrating tailored education and professional counselling with standard glucose and well-being metrics may improve the precision of clinical decision making and could aid in predicting future emotional crises [ 18 ].

Significant progress has been made in the personalisation of type 1 diabetes treatment since the discovery of insulin in 1922. These improvements include technological advancements in insulin delivery, marked advances in glucose monitoring and the recognition that these technical advances need to be accompanied by personal and psychosocial support for people with type 1 diabetes. Defining the aetiopathogenesis of type 1 diabetes as a complex autoimmune disease, as summarised by the Eisenbarth model nearly 40 years ago, has opened up the possibility of better prediction, diagnosis and, potentially in the future, prevention of type 1 diabetes. Recently, Florez and Pearson proposed a roadmap to achieve pharmacological precision medicine in monogenic and type 2 diabetes [ 143 ]. Inspired by this construct, Fig. 2 highlights a similar approach in type 1 diabetes. Here, we outline a roadmap for precision medicine in type 1 diabetes across the aspects of prediction, prevention, diagnosis and treatment, highlighting gaps that could be targeted in the future. We are facing a future of increasingly detailed omics techniques and real-time metabolic monitoring that can describe human biology and disease pathogenesis in ever more detail. We hope that improved prediction and understanding of type 1 diabetes through these methods will ultimately lead to a better understanding of variation in type 1 diabetes pathogenesis and improved disease-modifying treatments and biological interventions that can prevent, stop or reverse type 1 diabetes pathogenesis.

Roadmap for precision medicine in type 1 diabetes across the aspects of prediction, prevention, diagnosis and treatment. Steps 1–4 describe the stages of discovery, validation and implementation required for successful precision medicine approaches. The colour scale depicts the current strength of evidence for each of these steps and highlights gaps that could be targeted in the future. DKA, diabetic ketoacidosis. This figure is available as part of a downloadable slideset

Abbreviations

• Continuous glucose monitoring

National Institute for Health and Care Excellence

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Acknowledgements

The authors would like to acknowledge E. Anderson-Baucum (Indianapolis, IN, USA) for her editorial assistance. E. Anderson-Baucum is a freelance scientific writer. The content and views expressed are those of the authors.

Authors’ relationships and activities

The authors declare that there are no relationships or activities that might bias, or be perceived to bias, their work. RAO has previously held a UK MRC Confidence in Concept grant to work with Randox Ltd on a T1D GRS biochip, and has a research grant from Randox to continue this work.

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ALJC wrote the article. RAO and CE-M wrote and edited the article. All authors approved the article for publication.

RAO is funded by a Diabetes UK Harry Keen Fellowship (16/0005529). CE-M is funded by National Institute of Diabetes and Digestive and Kidney Diseases grants (R01DK093954, R01DK127236, U01DK127786, R01DK127308, UC4DK104166), a US Department of Veterans Affairs Merit Award (I01BX001733), and gifts from the Sigma Beta Sorority, the Ball Brothers Foundation and the George and Frances Ball Foundation.

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Alice L. J. Carr & Richard A. Oram

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Carr, A.L.J., Evans-Molina, C. & Oram, R.A. Precision medicine in type 1 diabetes. Diabetologia 65 , 1854–1866 (2022). https://doi.org/10.1007/s00125-022-05778-3

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Diagnostic Tests for Diabetes

Classification, screening criteria for prediabetes and type 2 diabetes:, informal risk factor assessment for prediabetes and type 2 diabetes, additional screening guidelines, section 2: diagnosis and classification of diabetes.

This article is part of a special article collection available at https://diabetesjournals.org/collection/2018/2024-Abridged-Standards-of-Care .

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Section 2: Diagnosis and Classification of Diabetes. Clin Diabetes 15 April 2024; 42 (2): 183–185. https://doi.org/10.2337/cd24-a002

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There is insufficient evidence to support the use of continuous glucose monitoring for screening or diagnosing prediabetes or diabetes.

In the absence of unequivocal hyperglycemia (e.g., hyperglycemic crisis), diagnosis of type 2 diabetes requires confirmatory testing, which can be a different test on the same day or the same test on a different day.

Marked discordance between A1C and repeated blood glucose measurements should raise the possibility of a problem or interference with either test.

Classification of diabetes type is not always straightforward at presentation, and misdiagnosis is common.

Screening for prediabetes and type 2 diabetes should be performed in asymptomatic adults with an informal assessment of risk factors or a validated risk calculator .

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Clinical presentation of type 1 diabetes

Affiliation.

• 1 The National Children's Hospital, AMNCH, Tallaght, Dublin 24, Ireland. [email protected]
• PMID: 15963033
• DOI: 10.1111/j.1399-543X.2005.00110.x

Objective: To identify the presenting features of type 1 diabetes in a national incident cohort aged under 15 yr, the duration of symptoms, the occurrence of diabetic ketoacidosis (DKA) at presentation, and the frequency of a family history of diabetes.

Methods: A prospective study was undertaken of incident cases of type 1 diabetes using an active monthly reporting card system from January 1, 1997 to December 31, 1998 in the Republic of Ireland. Follow-up questionnaires were distributed to pediatricians nationally.

Results: Two hundred and eighty-three incident cases were identified. Polyuria, polydipsia and weight loss were the main presenting symptoms in all age categories. Nocturnal enuresis was reported in 19% under 5 yr and in 31% aged 5-9.99 yr. Constipation was noted in five patients and in 10.4% under 5 yr of age. The median duration of symptoms was highest in the youngest (under 2 yr) and oldest (10-14.99 yr) age categories. Presentation in moderate/severe DKA occurred in 25% overall and six of nine of those aged under 2 yr. A family history of type 1 diabetes in a first-degree relative was found in 10.2%.

Conclusions: This study confirms the abrupt onset of type 1 diabetes, the absence of a family history, and the importance of the classical symptoms of polyuria, polydipsia, and weight loss in the majority of cases. It reveals secondary enuresis as an important symptom, especially in those under 10 yr, and constipation in the under 5 yr age group. The very young (under 2 yr) are more difficult to diagnose, have more variability of symptom duration, and are more likely to present in moderate/severe DKA. A high index of suspicion aids early diagnosis.

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• Comparative Study
• Child, Preschool
• Diabetes Mellitus, Type 1* / complications
• Diabetes Mellitus, Type 1* / epidemiology
• Diabetes Mellitus, Type 1* / genetics
• Diabetic Ketoacidosis / epidemiology
• Diabetic Ketoacidosis / etiology
• Follow-Up Studies
• Genetic Predisposition to Disease
• Infant, Newborn
• Ireland / epidemiology
• Prospective Studies
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• Volume 12, Issue 2
• Child Opportunity Index and clinical characteristics at diabetes diagnosis in youth: type 1 diabetes versus type 2 diabetes
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• Kim Hoyek 1 , 2 ,
• Ingrid Libman 2 , 3 ,
• Nkeiruka Mkparu 2 ,
• Yong Hee Hong 4 ,
• Silva Arslanian 1 , 2 ,
• http://orcid.org/0000-0002-5839-7923 Mary Ellen Vajravelu 1 , 2
• 1 Center for Pediatric Research in Obesity and Metabolism , UPMC Children's Hospital of Pittsburgh , Pittsburgh , Pennsylvania , USA
• 2 Division of Pediatric Endocrinology, Diabetes, and Metabolism , University of Pittsburgh School of Medicine , Pittsburgh , Pennsylvania , USA
• 3 Pediatric Endocrinology , UPMC Children's Hospital of Pittsburgh , Pittsburgh , Pennsylvania , USA
• 4 Pediatrics , Soonchunhyang University Hospital Bucheon , Bucheon , Gyeonggi-do , Korea (the Republic of)
• Correspondence to Dr Mary Ellen Vajravelu; maryellen.vajravelu{at}pitt.edu

Introduction Among youth with type 1 diabetes (T1D), longitudinal poor glycemic control is associated with adverse socioeconomic conditions at the neighborhood level. Child Opportunity Index (COI), which encompasses measures of education, health, environment, social, and economic factors, is associated with obesity in youth but has not been evaluated in youth with new-onset T1D or type 2 diabetes (T2D). We hypothesized that lower COI would be associated with adverse clinical outcomes at diabetes diagnosis, and due to differing risk factors and pathophysiology, that youth with new-onset T2D would have lower COI than youth with T1D.

Research design and methods Retrospective cohort of youth with new-onset diabetes admitted to a large academic pediatric hospital. COI was compared by diabetes type using t-tests and Χ 2 tests. Multivariable linear and logistic regression analyses were used to evaluate associations between COI and clinical characteristics, stratified by diabetes type and adjusted for age and sex.

Results The cohort (n=484) differed in race and age by diabetes type (T1D: n=389; 10.0% black, 81.2% white; age 9.6±0.2 years; T2D: n=95; 44.2% black, 48.4% white; age 14.8±0.3 years). Youth with T2D had lower COI (p<0.001). Low COI was associated with diabetic ketoacidosis in T1D and T2D. Black youth with low COI had the highest hemoglobin A1c among youth with T2D and the highest obesity prevalence among youth with T1D.

Conclusions COI is associated with differing characteristics at diagnosis in youth-onset T1D and T2D but is worse among youth with T2D overall. These findings underscore the need to address socioeconomic adversity when designing interventions to reduce T2D risk and to improve outcomes at diabetes diagnosis in youth.

• Diabetic Ketoacidosis
• Diabetes Mellitus, Type 1
• Diabetes Mellitus, Type 2
• Pediatric Obesity

Data availability statement

Data are available upon reasonable request. De-identified data are available upon reasonable request.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjdrc-2023-003968

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WHAT IS ALREADY KNOWN ON THIS TOPIC

Individual-level and neighborhood-level social determinants of health are increasingly recognized as key determinants of clinical outcomes in youth with type 1 diabetes and type 2 diabetes. Child Opportunity Index, a composite measure of education, health, environment, social, and economic factors important for child thriving, is associated with childhood obesity but has not been evaluated in the context of youth with newly diagnosed type 1 or type 2 diabetes.

WHAT THIS STUDY ADDS

In this cohort of 389 youth with type 1 diabetes and 95 youth with type 2 diabetes, Child Opportunity Index was significantly lower among youth with type 2 diabetes than type 1 diabetes. Among youth with either type 1 or type 2 diabetes, lower Child Opportunity Index was associated with higher odds of diabetic ketoacidosis. An interactive effect between race and Child Opportunity Index was demonstrated among youth with type 2 diabetes, with black youth living in neighborhoods with low Child Opportunity Index having the highest hemoglobin A1c at diagnosis.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

Child Opportunity Index may represent a novel measure to guide future screening or intervention efforts aimed at reducing incidence of diabetic ketoacidosis among incident youth-onset diabetes, as well as earlier recognition of new-onset type 2 diabetes.

Introduction

Social determinants of health, the conditions in which individuals live, work, and play, are tightly linked with clinical outcomes in type 1 and type 2 diabetes (T1D, T2D) across the lifespan. 1 2 Much of these findings have centered on individual-level poverty, food insecurity, and healthcare access among adults. However, neighborhood-level composite indices may illuminate how exposures to a variety of adverse conditions impact diabetes risk and outcomes. This is particularly important for youth-onset T2D given a rapidly rising incidence 3–5 and early, severe outcomes that disproportionately impact minoritized individuals. 6

A recently developed neighborhood-level index, Child Opportunity Index (COI), has emerged as a promising indicator of adverse health outcomes in youth, including obesity, 7 recurrent diabetic ketoacidosis (DKA) in youth with T1D, 8 and potentially avoidable hospitalization. 9 This composite index, developed in 2014 and revised in 2020 to version 2.0, is available for nearly all census tracts within the USA and encompasses 29 measures of neighborhood-level resources influencing pediatric health and development, including but not limited to access to high-quality schools, healthy foods, green space, and toxin-free environments. 10–12 COI is strongly associated with measures of structural racism, including historical redlining, blockbusting, and urban renewal, 13 highlighting the intersectionality of race and racism with adverse social determinants of health.

We investigated whether COI was associated with clinical characteristics at diagnosis of T1D and T2D. We hypothesized that COI would be worse among youth with T2D and would be associated with more severe presentation, including more severe hyperglycemia and acidosis.

Research design and methods

Study cohort.

This retrospective cohort study included youth aged 6 months–20 years who were diagnosed with T1D or T2D and admitted to UPMC Children’s Hospital of Pittsburgh, a large academic center, between January 1, 2021 and December 31, 2022, for management of new-onset diabetes. Electronic medical records were manually reviewed after approval from the University of Pittsburgh Institutional Review Board.

Outcome measures and covariates

Clinical outcomes included DKA (based on pH <7.3, metabolic acidosis with bicarbonate <15 mmol/L or clinical notes if laboratory data were incomplete), pH, serum bicarbonate, glucose, and hemoglobin A1c (HbA1c). Body mass index (BMI) was calculated using admission weight and height. BMI Z-score was determined using Centers for Disease Control and Prevention growth charts, and obesity defined as Z-score ≥1.64. 14 Age, sex, race, ethnicity, and zip code were manually extracted from the medical record. Diabetes type was based on clinical notes and diabetes autoantibody status.

As described above, COI is a measure of neighborhood-level resources that combines 29 indicators of three opportunity domains (educational, health and environmental, and social and economic). COI ranks neighborhoods from very low to very high opportunity. 8 9 Zip code-based nationally normed COI was obtained using the COI V.2.0 database that included 2020 US Postal Service zip codes, the closest available to the study period. 15

Patient characteristics are reported using summary statistics. Continuous variables were compared by diabetes type using t-test and Wilcoxon rank-sum test, depending on distribution. Categorical variables were compared using the Χ 2 test. Multivariable linear and logistic regression analyses were used to evaluate associations between COI and diabetes outcomes in separate models, adjusting for age and sex, stratified by diabetes type. Due to the infrequency of high/very high COIs among youth with T2D, these categories were combined with moderate COI, and low/very low COIs were combined, leading to a two-level categorization of COI ( not low =moderate, high, very high; low =low, very low) for multivariable analyses. This binary classification was also used in unadjusted logistic regression to determine the OR of low/very low COI by diabetes type. Due to the anticipated collinearity of race and COI, intersectional race-COI categories were created (eg, black-not low, black-low). Missing data were not imputed. All analyses were performed using Stata V.17 (StataCorp; College Station, Texas, USA) and used a two-sided alpha=0.05 for statistical significance.

Cohort characteristics

A total of 548 patients with new-onset diabetes mellitus were admitted during the 2-year study period. Of these, n=484 (T1D: n=389; T2D: n=95) were ≤20 years old and had available COI and evaluable DKA status upon admission ( online supplemental figure 1 ). Nearly all (T1D: 91.3%, T2D: 92.8%) were either white or black, so race was collapsed into white, black and other, which included Asian or Indian, multiracial, American Indian or not reported ( table 1 ). Youth with T2D were older on average and had higher prevalence of obesity than youth with T1D. Youth with T1D were predominantly white, while white and black races were nearly equally represented in T2D. HbA1c did not differ by diabetes type, but patients with T1D had lower pH and bicarbonate concentration.

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Cohort characteristics, T1D versus T2D

As shown in table 1 , half of youth with T2D resided in neighborhoods with low or very low COI, in comparison with less than one-quarter of youth with T1D (low/very low COI in T2D vs T1D: OR 3.5 (95% CI 2.2, 5.7)). However, this difference by diabetes type was driven by white youth (low/very low COI in white youth with T1D vs T2D: 16.8% vs 47.9%; OR 4.6 (95% CI 2.4, 8.7)). COI distribution was similar between T1D and T2D for black youth and youth of other races ( figure 1 ). Notably, although in T1D, low/very low COI was significantly more common in black youth (OR 5.8 (95% CI 2.9, 11.6)) and youth of other races (OR 3.1 (95% CI 1.4, 6.5)) than white youth, odds of low/very low COI did not differ significantly by racial group in T2D.

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COI by diabetes type in each racial group, demonstrating higher exposure to low COI for white youth with T2D versus T1D. In contrast, low and very low COI was common among black youth and youth of other races regardless of diabetes type. COI, Child Opportunity Index; T1D, type 1 diabetes; T2D, type 2 diabetes.

Association of race-COI and clinical presentation at diabetes onset

As shown in table 2 , in multivariable regression among youth with T1D, DKA was more common among black youth and youth of other races with low COI (66.7% (95% CI 46.6% to 86.7%) and 76.9% (95% CI 54.1% to 99.8%), respectively), versus white youth with not-low COI (42.2% (95% CI 36.3% to 48.1%)) ( figure 2A ). In contrast, among youth with T2D, DKA was most common among white youth with low COI (31.8% (95% CI 12.5% to 51.1%) vs 4.2% (95% CI −3.8% to 12%) among white youth with not-low COI) ( figure 2B ). Among youth with T1D, obesity was most common among black youth with low COI (36.8% (95% CI 15.3% to 58.4%)) but did not otherwise differ by race and COI ( figure 3A ). In contrast, obesity was equally common among all race-COI groups in T2D, ranging from 70.8% to 95.5% among each subgroup ( figure 3B ). HbA1c did not differ significantly across race-COI groups within T1D. However, among youth with T2D, HbA1c was 1.6% higher in black youth with low COI compared with white youth with not-low COI (12.3% (95% CI 11.3%, 13.3%) vs 10.7% (95% CI 9.7%, 11.8%)). Severity of acidosis as assessed by pH <7 and bicarbonate <5 mmol/L did not differ by race-COI group.

Predicted marginal per cent of youth with DKA on admission for new-onset (A) T1D and (B) T2D, based on multivariable logistic models adjusted for age and sex. DKA was more common among youth with T1D than T2D but differed by race and COI. * indicates significant (p<0.05) difference from the reference category (marked with arrow) of white youth with not-low COI . B-L, black-low COI; B-NL, black-not-low COI; COI, Child Opportunity Index; DKA, diabetic ketoacidosis; O-L, other race-low COI; O-NL, other race-not-low COI; T1D, type 1 diabetes; T2D, type 2 diabetes; W-L, white-low COI; W-NL, white-not-low COI.

Predicted marginal per cent of youth with obesity (BMI Z-score ≥1.64) on admission for new-onset (A) T1D and (B) T2D, based on multivariable logistic models adjusted for age and sex. Obesity was more common among youth with T2D than T1D but was highest among black youth with low COI in the T1D cohort. * indicates significant (p<0.05) difference from the reference category (marked with arrow) of white youth with not-low COI . B-L, black-low COI; BMI, body mass index; B-NL, black-not-low COI; COI, Child Opportunity Index; DKA, diabetic ketoacidosis; O-L, other race-low COI; O-NL, other race-not-low COI; T1D, type 1 diabetes; T2D, type 2 diabetes; W-L, white-low COI; W-NL, white-not-low COI.

Adjusted marginal estimates of diabetes-related outcomes from multivariable regression models, stratified by diabetes type

Conclusions

In a large retrospective cohort of youth with new-onset T1D and T2D, low and very low COIs were more than twice as common among youth with T2D and were present in half of the cohort, underscoring that adverse socioeconomic status is a common experience for youth with T2D. 16 COI was associated with DKA in both T1D and T2D and may therefore be a useful risk-stratification marker when designing population-level interventions to prevent DKA at diagnosis. COI’s differential associations with obesity (in T1D only) and HbA1c (in T2D only) reflect the differences in pathophysiology of these diseases but also that adverse clinical characteristics, in general, are more common among youth with low COI.

In youth with new-onset T1D, COI was associated with obesity. This is consistent with findings in the general pediatric population, in which a dose–response association between COI and BMI was previously demonstrated. 7 The COI–obesity association may reflect differing availability of safe places for physical activity between neighborhoods with higher versus lower COI. 17 18 Notably, we did not detect a difference in obesity prevalence among youth with T2D. This is likely due to the existence of very few youth without obesity in this sample, limiting the power of this analysis. In contrast, obesity was less prevalent among youth with new-onset T1D. It is also possible that youth with new-onset T2D from neighborhoods with low COI, in whom HbA1c tended to be higher, experienced weight loss due to unrecognized and untreated hyperglycemia, thus explaining our null findings. Our finding that COI is associated with DKA at admission is consistent with those from Bergmann et al , who found that lower COI was associated with higher probability of DKA readmission within 1 year among youth with T1D. 8 Bergmann et al also found that black youth remained at highest risk of recurrent DKA, even after accounting for COI.

Although race is a social construct, the impact of structural racism can become embodied 19 in intergenerational risk, with greater risk of youth-onset T2D conferred by maternal diabetes during pregnancy and other family history of T2D. 20 The potential combined effect of adverse socioeconomic exposures and population ancestry-based risk was demonstrated in a study by Cromer et al , who found that an area-level measure of socioeconomic status was associated with obesity and T2D in adults, with an additive effect among those with higher genetic risk scores. 21 These findings, along with our demonstration of low COI in half of youth with T2D, underscore that in order to better understand T2D risk, social determinants of health must be considered, rather than population ancestry alone. 22

Limitations of our study include the single center and limited time range, beginning during the COVID-19 pandemic. However, youth-onset T2D incidence rose significantly during this period, 23 and our study further characterizes this high-risk population. Because our study only included youth with T2D who were admitted for diabetes management, youth in this study may represent a group at higher risk of adverse COI than those whose new-onset T2D was addressed in the outpatient setting. Finally, our cohort reflects the very low population of Hispanic/Latinx youth in our region, 24 an important limitation given the higher prevalence of youth-onset T2D in this population.

In conclusion, COI is significantly lower in youth with T2D and is strongly associated with clinical presentation in youth with new-onset diabetes, including presence of DKA at diagnosis. COI may be a particularly important marker of risk for DKA and for youth-onset T2D and should be the focus of future studies to guide screening and prevention efforts.

Ethics statements

Patient consent for publication.

Not applicable.

Ethics approval

Approval was granted by the University of Pittsburgh Institutional Review Board (STUDY21020049).

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• ↵ Quickfacts: Allegheny County, Pennsylvania; Pittsburgh city, Pennsylvania . 2021 . Available : https://www.census.gov/quickfacts/fact/table/alleghenycountypennsylvania,pittsburghcitypennsylvania/PST045221

Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

• Data supplement 1

Contributors MEV, SA, and IL designed the study. IL, NM, and KH performed data collection. MEV performed data analysis. KH and MEV wrote the manuscript. SA, IL, NM and YHH provided critical review of the manuscript. MEV is the guarantor of this work, and as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Funding MEV was supported by NIH (K23DK125719). KH was supported by the Richard L Day Endowed Chair, held by SA.

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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• v.31(3); May-Jun 2011

Pattern of presentation in type 1 diabetic patients at the diabetes center of a university hospital

Abdulaziz m. al rashed.

From the Department of Pediatrics, King Abdulaziz University Hospital, College of Medicine, King Saud University, Riyadh, Saudi Arabia

BACKGROUND AND OBJECTIVES:

Diabetes mellitus (DM) is a major health problem worldwide. This study aimed to investigate the pattern of presentation and complications of pediatric diabetes.

DESIGN AND SETTING:

Retrospective study of children treated at a diabetes clinic at a university hospitalfor diabetes over 12-year period.

PATIENTS AND METHODS:

We collected data on the age at onset, sex, clinical presentation, duration of symptoms before diagnosis, and partial remission rate that were obtained from the hospital medical records, the National Diabetes Registry, and the statistics department.

Of 369 diabetic children, most (n=321) children had polyuria (92%) 321/369=87% as the presenting symptom; other symptoms included polydipsia (310 patients, 88.8% 310/369=84%), weight loss (292 patients, 83.9%), nocturia (240 patients, 68.8% 240/369=65%), diabetic ketoacidosis (DKA) (174 patients, 49.9% 174/369=47.20%), and abdominal pain (172 patients, 49.3% 174/369=46.6%). Presenting symptoms were missing in 20 files, so the percentages were calculated among 349 patients. Most patients had acute diabetic complications such as hypoglycemia (222 patients, 62%) and DKA (88 patients, 38.1%, but none had severe complications such as coma and cerebral edema. Chronic complications included retinopathy (4 patients, 1.3%), neuropathy (2 patients, 0.6%), coronary heart disease (2 patients, 0.6%), and nephropathy (1 patient, 0.4%).

CONCLUSION:

The pattern of presentation of type 1 diabetes has changed as the incidence of DKA has decreased; unlike in previous studies, DKA was not the most common presenting symptom in this study. Chronic complications of diabetes, such as retinopathy, neuropathy, coronary heart disease, and nephropathy are mostly rare but still present. These complications might be prevented by achieving better awareness of the need for glycemic control.

Diabetes mellitus (DM) is a major health problem worldwide. Current studies have revealed a definite global increase in the incidence and prevalence of diabetes, with the World Health Organization (WHO) projecting that there will be almost 221 million cases in the year 2010 and up to 285 million cases in the year 2025. 1 It is the fourth or fifth leading cause of death in most developed countries. 1 , 2 Although this increase is mainly expected in type 2 diabetes, a parallel increase in childhood diabetes, including type 1 and 2 diabetes, has been reported. 3 DM in children has previously been considered rare in African and Asian populations. 4 – 8 The WHO Diabetes Mondiale (WHO DIAMOND) project group has reported a worldwide increase in the incidence and variation (over 400-fold) of type 1 diabetes, with the highest occurring in Finland (over 45 per 100 000 children under the age of 15 years) and the lowest in parts of China and Fiji. 9

DM in children in Saudi Arabia has not been studied well and further studies are needed. 10 Little local information on the disease is available, and most cases reported have been of type 2 DM. 11 The epidemiology and characteristics of DM, particularly insulin-dependent DM, are not known in the Saudi community, and only a small amount of data is available. 11 Moreover, the data confirm the need to develop a national registry and the need for further epidemiological research. 12 Furthermore, adolescents are not examined in pediatric clinics, and they do not receive adequate attention in adult clinics. 13

Saudi Arabia is a unique country among developing nations in view of its excellent economic status and relatively low literacy rate, particularly among mothers, in addition to the cultural and religious background, which might influence the management of diabetes. 14 The presentation of type 1 diabetes in Saudi children seems to differ from that in children from Western countries. 15 The most common clinical sign is diabetic ketoacidosis (DKA), which is observed in 67.2% of the patients. 11 DKA is the most serious presenting symptom of type 1 DM. The frequency and severity of DKA at presentation vary significantly worldwide. 16 In Saudi Arabia, studies have revealed that DKA is present in 55% to 77% of the DM cases. 15 , 17 Ketoacidosis is the most common presenting symptom of childhood DM in this region. 18

This study presents some of the epidemiological and clinical features and complications of childhood DM as recorded in the Diabetes Center at King Abdulaziz University Hospital, Riyadh, Saudi Arabia. The Diabetes Center receives patients from Riyadh District and suburban areas; in addition, it is a tertiary care center that receives referred patients from different cities in the country. The objective of this study was to investigate the pattern of presentation of pediatric diabetes in patients enrolled in the diabetes center of a university hospital and to review the complications of diabetes in the study group.

PATIENTS AND METHODS

All diabetic children who were enrolled in the study from among those treated at the King Abdulaziz University Hospital over a 12-year period from 1993 to 2005. Vital data for the study were extracted from several sources, including hospital medical records, the National Diabetes Registry, and the statistics department. The data were extracted by an experienced physician under the strict supervision of the author, who also checked for the consistency and completeness of the extracted data. The recorded information included the age at onset, sex, nationality, consanguinity, clinical presentation, duration of symptoms before diagnosis, and partial remission rate (which was defined according to the criteria of the International Study Group of Diabetes in Children and Adolescents as a period of freedom from clinical symptoms of diabetes with insulin requirements of <0.5 units/kg/day and absent or minimal glycosuria for more than 4 weeks). During this study, type 1 diabetes was predominantly diagnosed on the basis of the clinical and biological features. Polyuria, polydipsia, weight loss and fatigability were the principal clinical features for diagnosis. Significant hyperglycemia was taken into account as a biological feature according to the National Diabetes Data Group criteria of fasting blood glucose of >140 mg/dL (>7.7 mmol/L), 2-hour postprandial blood glucose level of >200 mg/dL (>11.1 mmol/L), and glycosuria with or without ketonuria.

Both clinical and biological features were included in the diagnosis of DKA. Clinical features such as vomiting, abdominal pain, moderate-to-severe dehydration, and stupor, in addition to hyperglycemia with blood glucose levels exceeding 15 mmol/L, ketonuria and metabolic acidosis with a bicarbonate level of <15 mmol/L, played significant roles in determining DKA. The chronic complications such as retinopathy, nephropathy and neuropathy were identified by ophthalmic findings indicative of retinopathy, persistent microalbuminuria, and abnormal nerve conductions, respectively. Data analyses (chi square tests, Fischer exact test) were performed using the statistical packages STATA, R, and Minitab.

Of the 369 diabetic patients, 159 (43.1%) patients were between 11 and 15 years of age. The age groups 6-10 years and >15 years consisted of a similar number of patients—100 (27.1%) and 97 (26.3%) patients, respectively. Only 13 (3.5%) patients were less than 5 years old. The mean (standard deviation) age was 12.3 (4.0) years with a range of 2-18 years ( Table 1 ). Of the enrolled patients, 175 (47.4%) were male and 194 (52.6%) were female. The study group included 324 (87.8%) Saudi patients and 45 (12.2%) patients of different Arab nationalities. A positive family history of DM was recorded in 260 (73.7%) patients, including both type 1 and type 2 diabetes patients. The overall mean (SD) duration of diabetes was 4.6 (3.7) years. There were two major peaks of age at diagnosis, one at the age of 7 years and the other at 11 years, with a sharp drop after the age of 11 years; the curve almost reached a plateau at the age of 18 years ( Figure 1 ). Most patients (134 patients, 58.5%) had a less than 15 days duration of symptoms before diagnosis. The duration of symptoms before diagnosis ranged from 1 to 365 days, with a median of 14 days ( Table 1 ). The mean total insulin intake was 36.0 units/d, with a range of 2-106 units/d and a median of 37 units/d. Partial remission was observed in 21 (9.1%) patients ( Table 1 ). Numbers of patients by age group, duration of diabetes, family history, diabetic complications, and were above 17 years of age at the time of diagnosis, and these were the oldest patients in this study. Two peaks [peaks of age at time of diagnosis?] were observed, one as early as at 12 days of age in a case that was diagnosed in another hospital and referred to the Diabetes Center of King Abdulaziz University Hospital. Three patients duration of partial remission by the other variables are presented in Tables ​ Tables2a, 2a , ​ ,2b, 2b , and ​ and2c 2c .

Characteristics of pediatric diabetic patients attending the diabetes center at a university hospital (1993-2005) (n=369).

Distribution curve of age of diagnosis pediatric patients attending the diabetes center at a university hospital (1993-2005).

Sex of pediatric diabetic patients by age group

Sex and and age group by duration of diabetes

Sex, age group and duration by family history of diabetes, diabetic complications and duration of partial remission

The most frequent presenting symptoms were polyuria, polydipsia, weight loss, nocturia ( Table 3 ) while DKA was present in about half ( Table 3 ). Because of missing data, not all information on all parients was available. The data on fatigability was available for 231 patients; fatigability was observed in 179 of these 231 patients. The less frequent symptoms included fever, obesity, delayed wound healing, vomiting, loss of consciousness, and diarrhea; a history of preceding illness was also less frequent. Ten (4.3%) patients of the studied cohort were asymptomatic. Most patients had acute diabetic complications such as hypoglycemia, and DKA ( Table 4 ). None of the patients had severe complications such as coma and cerebral edema. Chronic complications included retinopathy, neuropathy, coronary heart disease and nephropathy.

Symptoms of pediatric diabetic patients on presentation at the diabetes center according sex, age group, and duration of symptoms

Diabetic complications (acute and chronic)

Among the patients in the study, diabetes was diagnosed as early as at 12 days of age in a case that was diagnosed in another hospital and referred to the Diabetes Center of King Abdulaziz University Hospital. Three patients were above 17 years of age at the time of diagnosis, and these were the oldest patients in this study. Two peaks in age at time of diagnosis were observed, one at 7 and the other at 11 years of age. In a study by Salman et al, the age at onset ranged from 7.5 months to 12 years, with a peak at around 5-7 years and 11-14 years, respectively. The second peak in this study was observed to occur in the age range similar to that reported by Abdullah (10-13 years), while the first peak was observed to occur slightly earlier (4-6 years). 19 , 20 In the study by Abdullah, the youngest patient was 6 months old at diagnosis.

The present study showed a female preponderance, with 194 (52.6%) females versus 175 (47.4%) males; such a female preponderance was also observed in the series conducted by Salman et al, wherein 53.6% of patients were female. On the contrary, the series conducted by Abdullah showed a male preponderance, with a male-to-female ratio of 1.3:1; this ratio is similar to the ratios observed in the UK, Denmark and India. 19 , 20 In this study, the duration of symptoms before diagnosis was 1-35 days with a median of 14 days as compared to a duration of 2-60 days with a mean of 18.2 days in the series conducted by Salman et al.

The most common clinical presentations in the present study were polyuria (92%) and polydipsia (88.8%). In the study by Salman et al, DKA was the most common clinical presentation and was observed in 74 (67.3%) patients; while in the present study, DKA was observed in 49.9% of the patients. In the study by Abdullah, 55% of the patients presented with DKA. Studies in Malaysia revealed a figure (48%) similar to that in the present study, while studies in Philippines and India revealed figures of 63% and 20%-40%, respectively. 6 , 21 , 22 DKA is considered uncommon in Japan and Indonesia. 23 , 24 DKA was observed in 49.9% of the patients in this series; thus DKA was less common in this study than in other local studies, such as those by Salman et al (DKA was observed in 67.2% of the patients) and Abdullah (DKA observed in 55% of the patients). This difference may be explained by a higher level of awareness among parents and improvement in health services with early diagnosis.

The partial remission rate in this study was only 9.1%, which is lower than the rates observed in the studies by Abdullah (32%) and Salman et al. (30.9%). It correlates to those studies in relation to age group; none of the patients below 5 years of age had any episode. Partial remission is considered more common when diabetes is diagnosed in older children and teenagers, and most patients in the present study were diagnosed when they were less than 11 years of age ( Figure 1 ); this might explain the low rate of partial remission observed in this study. The lower incidence of DKA may further explain the low rate of partial remission.

A positive family history of both types (1 and 2) of diabetes was observed in 73.7% of the patients in this study; this figure is higher than that reported in the study by Abdullah (56.7%). DM occurs significantly more frequently in the parents and siblings of diabetics than in those of the control population. 25 , 26 In the study by Salman et al,, both the consanguinity rate and family history of type 1 and 2 diabetes were higher than those reported in the literature and also in a similar local study. 25 – 29

The treatment of DM in children requires the provision of a comprehensive, well-coordinated and continuous service. This is best achieved by teamwork. Adolescents or “young adults” in Saudi Arabia and in some other non-Western countries are not examined at pediatric clinics and do not receive adequate attention at adult clinics. Studies of the microvascular complications in non-insulin-dependent DM patients suggest that the onset of these complications occurs at least 4-6 years before clinical diagnosis. Evidence shows that strict glycemic control prevents microvascular complications. 30

In summary, the incidence of DKA was lower than that reported in previous studies; in addition, unlike in previous studies, DKA was not the most common clinical presentation. This difference is due to better awareness and early diagnosis. Additionally, the partial remission rate was lower, which indicates early diagnosis. Although chronic complications are uncommon in children, retinopathy, neuropathy, coronary heart disease and nephropathy have been observed; this necessitates an awareness among physicians, caretakers and patients about the importance of early diagnosis and strict control of DM. The incidence of family history was higher than that reported previously, which can be explained by the higher rate of consanguinity in the Saudi community. This observation indicates the need for further genetic studies of DM in the Saudi population.

• Case report
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• Published: 17 April 2024

Pneumoperitoneum, pneumoretroperitoneum and pneumomediastinum: rare complications of perforation peritonitis: a case report

• H. Hafiani   ORCID: orcid.org/0000-0002-3198-1783 1 ,
• N. Bouknani 1 ,
• E. M. Choukri 1 ,
• R. Charif Saibari 1 &
• A. Rami 1  

Journal of Medical Case Reports volume  18 , Article number:  187 ( 2024 ) Cite this article

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Gas extravasation complications arising from perforated diverticulitis are common but manifestations such as pneumoperitoneum, pneumoretroperitoneum, and pneumomediastinum happening at the same time are exceedingly rare. This case report explores the unique presentation of these 3 complications occurring simultaneously, their diagnosis and their management, emphasizing the importance of interdisciplinary collaboration for accurate diagnosis and effective management.

Case presentation

A 74-year-old North African female, with a medical history including hypertension, dyslipidemia, type 2 diabetes, goiter, prior cholecystectomy, and bilateral total knee replacement, presented with sudden-onset pelvic pain, chronic constipation, and rectal bleeding. Clinical examination revealed hemodynamic instability, hypoxemia, and diffuse tenderness. After appropriate fluid resuscitation with norepinephrine and saline serum, the patient was stable enough to undergo computed tomography scan. Emergency computed tomography scan confirmed perforated diverticulitis at the rectosigmoid junction, accompanied by the unprecedented presence of pneumoperitoneum, pneumoretroperitoneum, and pneumomediastinum. The patient underwent prompt surgical intervention with colo-rectal resection and a Hartmann colostomy. The postoperative course was favorable, leading to discharge one week after admission.

Conclusions

This case report highlights the clinical novelty of gas extravasation complications in perforated diverticulitis. The unique triad of pneumoperitoneum, pneumoretroperitoneum, and pneumomediastinum in a 74-year-old female underscores the diagnostic challenges and the importance of advanced imaging techniques. The successful collaboration between radiologists and surgeons facilitated a timely and accurate diagnosis, enabling a minimally invasive surgical approach. This case contributes to the understanding of atypical presentations of diverticulitis and emphasizes the significance of interdisciplinary teamwork in managing such rare manifestations.

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Introduction

Potential sources of gas extravasation include the respiratory tract, the gastrointestinal tract or infections with gas-generating germs [ 1 ]. While pneumoperitoneum is a classic complication of diverticulitis, pneumomediastinum [ 2 ] and pneumoretroperitoneum are very rare complications of perforated diverticulitis [ 3 ]. Imaging studies can help to diagnose such diseases, their complications and even sometimes, their own etiology. While abdominal X-ray alone can help diagnose air outside the peritoneum, CT scan remains the gold standard today with fine localisation of air bubbles, eventual ascites and other things such as perforation location. We present the unusual case of a 74 years old female with peritonitis from perforated diverticulitis at the rectosigmoid junction that resulted in pneumoperitoneum, pneumoretroperitoneum and even pneumomediastinum.

The patient of the case is a 74 years old North African female with hypertension, dyslipidemia, type 2 diabetes, goiter, prior cholecystectomy, and bilateral total knee replacement. The patient's symptoms began with sudden onset of cramp-like pelvic pain, accompanied by chronic constipation and scant rectal bleeding. Notably, there were no associated vomiting or urinary symptoms, but the presentation occurred within a febrile and altered general condition.

Clinical examination showed hemodynamic and respiratory instability with low blood pressure and hypoxemia associated with diffuse tenderness and hypogastric guarding, while rectal examination didn’t show any rectal bleeding or melena. After appropriate resuscitation done with appropriate quantities of norepinephrine and saline serum, the patient was stable enough to undergo imaging. A CT scan was ordered at the emergency room and the final diagnosis was perforated diverticulitis but what caught our attention was that the patient had both pneumoperitoneum (Fig.  1 ) and pneumoretroperitoneum (Fig.  2 ) and pneumomediastinum (Fig.  3 ) that suggested perforation at the rectosigmoid junction.

CT scan axial view showing pneumoperitoneum. Arrow points to pneumoperitoneum

CT scan axial view showing pneumoretroperitoneum. Arrow points to pneumoretroperitoneum

CT scan axial view showing pneumomediastinum. Arrow points to pneumodiastinum

Our patient was sent to the operating room for surgery on that same day and had laparoscopic colo-rectal resection with a Hartmann colostomy. The postoperative course was favorable and the patient was discharged from the hospital 1 week afterward.

Perforation of the colic wall can happen due to diverticulitis, neoplasm, iatrogenic or traumatic mechanisms. Colonic diverticulosis is common in the western countries affecting nearly 50% of the population [ 4 ] with approximately 20% of them that may develop inflammation of the diverticula [ 5 ]. This inflammation can lead to perforation which is a serious complication that requires urgent intervention. Extradigestive air secondary to perforated diverticula can help localize the site of the perforation on CT scan, whether it is in the peritoneum, behind it, or in the mediastinum. While pneumoperitoneum is a classic localisation of air after perforation, pneumoretroperitoneum is less usual.

Pneumomediastinum secondary to colonic perforation is extremely rare and only 20 cases of spontaneous perforation (not iatrogenic or traumatic) were reported before 2019 [ 6 ]. Diverticulitis was the most common cause of mediastinal emphysema [ 6 ].

In our case, the air was localized in the 3 parts (Fig.  4 ) and made us immediately think that the perforation occurred at the rectosigmoid junction, near the Douglas, where the peritoneum folds (Fig.  2 ). The mechanism of the pneumomediastinum is not fully understood but a few theories emerged: it could either come from extravasation of air through the fascial planes or the esophagus and its perivascular spaces or come directly from the retroperitoneum [ 7 ].

CT scan sagittal view showing pneumoperitoneum [ 1 ], pneumoretroperitoneum [ 3 ] and pneumomediastinum [ 2 ]. Arrow 1 points to pneumoperitoneum, arrow 2 points to pneumomediastinum, arow 3 points to pneumoretroperitoneum

Another theory includes the foramina of Morgagni and Bochdalek, which are responsible for diaphragmatic hernias when they are weak. These 2 visceral peritoneal folds could constitute air passage from the peritoneum to the mediastinum.

In our particular scenario, the radiologist readily established the diagnosis due to clear manifestations of diverticulitis in addition to the presence of extradigestive air. However, in certain instances, the detection of air may serve as the sole indicator, necessitating extensive paraclinical investigations. This underscores the rationale behind the diagnostic algorithm proposed by Wang et al. [ 8 ] for situations where air constitutes the sole available information.

Following the diagnosis, the patient promptly underwent laparoscopic colorectal resection, during which the surgeons validated the radiologist's diagnosis of peritonitis resulting from diverticulitis perforation (Additional file 1 : Video S1). Peritoneal lavage was done, and a Hartmann colostomy was performed by the surgeon. Subsequently, the patient was discharged without any complications after a 10-day hospitalization period.

The question of the origin of the extradigestive air remains, and this case highlights the fact that the collaboration between radiologists and surgeons should be optimal. With a good and clear diagnosis, the surgeon chose the laparoscopic approach (less harmful for the patient) and could cure a potentially fatal disease with a minimalist approach, sending the patient back home 10 days after admission.

In conclusion, our case report underscores the complexity and rarity of gas extravasation complications resulting from perforated diverticulitis. The presentation of a 74-year-old female with peritonitis at the rectosigmoid junction led to the unique occurrence of pneumoperitoneum, pneumoretroperitoneum, and pneumomediastinum. This very unusual manifestation necessitated a prompt and collaborative effort between radiologists and surgeons for accurate diagnosis and timely intervention. The effective coordination between radiologists and surgeons, coupled with advanced imaging techniques, not only facilitated a timely and accurate diagnosis but also enabled a minimally invasive surgical approach with a favorable outcome.

Availability of data and materials

The data that support the findings of this study are available from the corresponding author, Hafiani Hamza, upon reasonable request.

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Hamza Hafiani—Conception of the work, Design of the work, Acquisition of data, Analysis of data, Interpretation of data, Drafting the work, Revising the work critically for important intellectual content, Final approval of the version to be published, Agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Nawal Bouknani—Conception of the work, Design of the work, Acquisition of data, Analysis of data, Interpretation of data, Drafting the work, Revising the work critically for important intellectual content, Final approval of the version to be published, Agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. El Mehdi Choukri—Conception of the work, Design of the work, Acquisition of data, Analysis of data, Interpretation of data, Drafting the work, Revising the work critically for important intellectual content, Final approval of the version to be published, Agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Rayhana Charif Saibari—Conception of the work, Design of the work, Acquisition of data, Analysis of data, Interpretation of data, Drafting the work, Revising the work critically for important intellectual content, Final approval of the version to be published, Agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Amal Rami—Conception of the work, Design of the work, Acquisition of data, Analysis of data, Interpretation of data, Drafting the work, Revising the work critically for important intellectual content, Final approval of the version to be published, Agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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Supplementary Information

Additional file 1. Video of the laparoscopic surgery showing the perforation.

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Hafiani, H., Bouknani, N., Choukri, E.M. et al. Pneumoperitoneum, pneumoretroperitoneum and pneumomediastinum: rare complications of perforation peritonitis: a case report. J Med Case Reports 18 , 187 (2024). https://doi.org/10.1186/s13256-024-04488-1

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Received : 22 January 2024

Accepted : 01 March 2024

Published : 17 April 2024

DOI : https://doi.org/10.1186/s13256-024-04488-1

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• Pneumomediastinum
• Pneumoperitoneum
• Pneumoretroperitoneum
• Perforation
• Peritonitis
• Diverticulitis

Journal of Medical Case Reports

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