clinical case study urine

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VICTORIA J. SHARP, MD, DANIEL K. LEE, MD, AND ERIC J. ASKELAND, MD

A more recent article on  office-based urinalysis  is available.

Am Fam Physician. 2014;90(8):542-547

Author disclosure: No relevant financial affiliations.

Urinalysis is useful in diagnosing systemic and genitourinary conditions. In patients with suspected microscopic hematuria, urine dipstick testing may suggest the presence of blood, but results should be confirmed with a microscopic examination. In the absence of obvious causes, the evaluation of microscopic hematuria should include renal function testing, urinary tract imaging, and cystoscopy. In a patient with a ureteral stent, urinalysis alone cannot establish the diagnosis of urinary tract infection. Plain radiography of the kidneys, ureters, and bladder can identify a stent and is preferred over computed tomography. Asymptomatic bacteriuria is the isolation of bacteria in an appropriately collected urine specimen obtained from a person without symptoms of a urinary tract infection. Treatment of asymptomatic bacteriuria is not recommended in nonpregnant adults, including those with prolonged urinary catheter use.

Urinalysis with microscopy has proven to be an invaluable tool for the clinician. Urine dipstick testing and microscopy are useful for the diagnosis of several genitourinary and systemic conditions. 1 , 2 In 2005, a comprehensive review of urinalysis was published in this journal. 3 This article presents a series of case scenarios that illustrate how primary care physicians can utilize the urinalysis in common clinical situations.

Microscopic Hematuria: Case 1

Microscopic hematuria is common and has a broad differential diagnosis, ranging from completely benign causes to potentially invasive malignancy. Causes of hematuria can be classified as glomerular, renal, or urologic 3 – 5 ( Table 1 6 ) . The prevalence of asymptomatic microscopic hematuria varies among populations from 0.18% to 16.1%. 4 The American Urological Association (AUA) defines asymptomatic microscopic hematuria as three or more red blood cells per high-power field in a properly collected specimen in the absence of obvious causes such as infection, menstruation, vigorous exercise, medical renal disease, viral illness, trauma, or a recent urologic procedure. 5 Microscopic confirmation of a positive dipstick test for microscopic hematuria is required. 5 , 7

DIAGNOSTIC APPROACH

Case 1: microscopic hematuria.

A 58-year-old truck driver with a 30-year history of smoking one pack of cigarettes per day presents for a physical examination. He reports increased frequency of urination and nocturia, but does not have gross hematuria. Physical examination reveals an enlarged prostate. Results of his urinalysis with microscopy are shown in Table 2 .

Based on this patient's history, symptoms, and urinalysis findings, which one of the following is the most appropriate next step?

A. Repeat urinalysis in six months.

B. Obtain blood urea nitrogen and creatinine levels, perform computed tomographic urography, and refer for cystoscopy.

C. Treat with an antibiotic and repeat the urinalysis with microscopy.

D. Inform him that his enlarged prostate is causing microscopic hematuria, and that he can follow up as needed.

E. Perform urine cytology to evaluate for bladder cancer.

The correct answer is B .

For the patient in case 1 , because of his age, clinical history, and lack of other clear causes, the most appropriate course of action is to obtain blood urea nitrogen and creatinine levels, perform computed tomographic urography, and refer the patient for cystoscopy. 5 An algorithm for diagnosis, evaluation, and follow-up of patients with asymptomatic microscopic hematuria is presented in Figure 1 . 5 The AUA does not recommend repeating urinalysis with microscopy before the workup, especially in patients who smoke, because tobacco use is a risk factor for urothelial cancer ( Table 3 ) . 5

A previous article in American Family Physician reviewed the American College of Radiology's Appropriateness Criteria for radiologic evaluation of microscopic hematuria. 8 Computed tomographic urography is the preferred imaging modality for the evaluation of patients with asymptomatic microscopic hematuria. 5 , 8 It has three phases that can detect various causes of hematuria. The non–contrast-enhanced phase is optimal for detecting stones in the urinary tract; the nephrographic phase is useful for detecting renal masses, such as renal cell carcinoma; and the delayed phase outlines the collecting system of the urinary tract and can help detect urothelial malignancies of the upper urinary tract. 9 Although the delayed phase can detect some bladder masses, it should not replace cystoscopy in the evaluation for bladder malignancy. 9 After a negative microscopic hematuria workup, the patient should continue to be followed with yearly urinalysis until at least two consecutive normal results are obtained. 5

In patients with microscopic hematuria, repeating urinalysis in six months or treating empirically with antibiotics could delay treatment of potentially curable diseases. It is unwise to assume that benign prostatic hyperplasia is the explanation for hematuria, particularly because patients with this condition typically have risk factors for malignancy. Although urine cytology is typically part of the urologic workup, it should be performed at the time of cystoscopy; the AUA does not recommend urine cytology as the initial test. 5

Dysuria and Flank Pain After Lithotripsy: Case 2

After ureteroscopy with lithotripsy, a ureteral stent is often placed to maintain adequate urinary drainage. 10 The stent has one coil that lies in the bladder and another that lies in the renal pelvis. Patients with ureteral stents may experience urinary frequency, urgency, dysuria, flank pain, and hematuria. 10 They may have dull flank pain that becomes sharp with voiding. This phenomenon occurs because the ureteral stent bypasses the normal nonrefluxing uretero-vesical junction, resulting in transmission of pressure to the renal pelvis with voiding. Approximately 80% of patients with a ureteral stent experience stent-related pain that affects their daily activities. 11

POTENTIALLY MISLEADING URINALYSIS

Case 2: dysuria and flank pain after lithotripsy.

A 33-year-old woman with a history of nephrolithiasis presents with a four-week history of urinary frequency, urgency, urge incontinence, and dysuria. She recently had ureteroscopy with lithotripsy of a 9-mm obstructing left ureteral stone; she does not know if a ureteral stent was placed. She has constant dull left flank pain that becomes sharp with voiding. Results of her urinalysis with microscopy are shown in Table 4 .

A. Treat with three days of ciprofloxacin (Cipro), and tailor further antibiotic therapy according to culture results.

B. Treat with 14 days of ciprofloxacin, and tailor further antibiotic therapy according to culture results.

C. Obtain a urine culture and perform plain radiography of the kidneys, ureters, and bladder.

D. Perform a 24-hour urine collection for a metabolic stone workup.

E. Perform computed tomography.

The correct answer is C .

The presence of a ureteral stent causes mucosal irritation and inflammation; thus, findings of leukocyte esterase with white and red blood cells are not diagnostic for urinary tract infection, and a urine culture is required. In this setting, plain radiography of the kidneys, ureters, and bladder would be useful to determine the presence of a stent. If a primary care physician identifies a neglected ureteral stent, prompt urologic referral is indicated for removal. Retained ureteral stents may become encrusted, and resultant stone formation may lead to obstruction. 10

Flank discomfort and recent history of urinary tract manipulation suggest that this is not an uncomplicated urinary tract infection; therefore, a three-day course of antibiotics is inadequate. Although flank pain and urinalysis suggest possible pyelonephritis, this patient should not be treated for simple pyelonephritis in the absence of radiography to identify a stent. A metabolic stone workup may be useful for prevention of future kidney stones, but it is not indicated in the acute setting. Finally, although computed tomography would detect a ureteral stent, it is not preferred over radiography because it exposes the patient to unnecessary radiation. Typically, microscopic hematuria requires follow-up to ensure that there is not an underlying treatable etiology. In this case , the patient's recent ureteroscopy with lithotripsy is likely the etiology.

Urinalysis in a Patient Performing Clean Intermittent Catheterization: Case 3

Case 3: urinalysis in a patient performing clean intermittent catheterization.

A 49-year-old man who has a history of neurogenic bladder due to a spinal cord injury and who performs clean intermittent catheterization visits your clinic for evaluation. He reports that he often has strong-smelling urine, but has no dysuria, urge incontinence, fever, or suprapubic pain. Results of his urinalysis with microscopy are shown in Table 5 .

A. Inform the patient that he has a urinary tract infection, obtain a urine culture, and treat with antibiotics.

B. Refer him to a urologist for evaluation of a complicated urinary tract infection.

C. Perform computed tomography of the abdomen and pelvis to evaluate for kidney or bladder stones.

D. Inform him that no treatment is needed.

E. Obtain a serum creatinine level to evaluate for chronic kidney disease.

The correct answer is D .

Although the urinalysis results are consistent with a urinary tract infection, the clinical history suggests asymptomatic bacteriuria. Asymptomatic bacteriuria is the isolation of bacteria in an appropriately collected urine specimen obtained from a person without symptoms of a urinary tract infection. 12 The presence of bacteria in the urine after prolonged catheterization has been well described; one study of 605 consecutive weekly urine specimens from 20 chronically catheterized patients found that 98% contained high concentrations of bacteria, and 77% were polymicrobial. 13

Similar results have been reported in patients who perform clean intermittent catheterization; another study of 1,413 urine cultures obtained from 407 patients undergoing clean intermittent catheterization found that 50.6% contained bacteria. 14 Guidelines from the Infectious Diseases Society of America recommend against treatment of asymptomatic bacteriuria in nonpregnant patients with spinal cord injury who are undergoing clean intermittent catheterization or in those using a chronic indwelling catheter. 12

In the absence of symptoms of a urinary tract infection or nephrolithiasis, there is no need to culture the urine, treat with antibiotics, refer to a urologist, or perform imaging of the abdomen and pelvis. There is no reason to suspect acute kidney injury in this setting; thus, measurement of the serum creatinine level is also unnecessary.

Data Sources : Literature searches were performed in PubMed using the terms urinalysis review, urinalysis interpretation, microscopic hematuria, CT urogram, urinary crystals, indwelling ureteral stent, asymptomatic bacteriuria, and bacteriuria with catheterization. Guidelines from the American Urological Association were also reviewed. Search dates: October 2012 and June 2013.

Wu X. Urinalysis: a review of methods and procedures. Crit Care Nurs Clin North Am. 2010;22(1):121-128.

Hardy PE. Urinalysis interpretation. Neonatal Netw. 2010;29(1):45-49.

Simerville JA, Maxted WC, Pahira JJ. Urinalysis: a comprehensive review [published correction appears in Am Fam Physician . 2006;74(7):1096]. Am Fam Physician. 2005;71(6):1153-1162.

Cohen RA, Brown RS. Clinical practice. Microscopic hematuria. N Engl J Med. 2003;348(23):2330-2338.

American Urological Association. Diagnosis, evaluation and follow-up of asymptomatic microhematuria (AMH) in adults. http://www.auanet.org/education/asymptomatic-microhematuria.cfm . Accessed June 6, 2014.

Ahmed Z, Lee J. Asymptomatic urinary abnormalities. Hematuria and proteinuria. Med Clin North Am. 1997;81(3):641-652.

Rao PK, Jones JS. How to evaluate ‘dipstick hematuria’: what to do before you refer. Cleve Clin J Med. 2008;75(3):227-233.

Choyke PL. Radiologic evaluation of hematuria: guidelines from the American College of Radiology's Appropriateness Criteria. Am Fam Physician. 2008;78(3):347-352.

Sadow CA, Wheeler SC, Kim J, Ohno-Machado L, Silverman SG. Positive predictive value of CT urography in the evaluation of upper tract urothelial cancer. AJR Am J Roentgenol. 2010;195(5):W337-W343.

Haleblian G, Kijvikai K, de la Rosette J, Preminger G. Ureteral stenting and urinary stone management: a systematic review. J Urol. 2008;179(2):424-430.

Joshi HB, Stainthorpe A, MacDonagh RP, Keeley FX, Timoney AG, Barry MJ. Indwelling ureteral stents: evaluation of symptoms, quality of life and utility. J Urol. 2003;169(3):1065-1069.

Nicolle LE, Bradley S, Colgan R, Rice JC, Schaeffer A, Hooton TM Infectious Diseases Society of America; American Society of Nephrology; American Geriatric Society. Infectious Diseases Society of America guidelines for the diagnosis and treatment of asymptomatic bacteriuria in adults [published correction appears in Clin Infect Dis . 2005;40(10):1556]. Clin Infect Dis. 2005;40(5):643-654.

Warren JW, Tenney JH, Hoopes JM, Muncie HL, Anthony WC. A prospective microbiologic study of bacteriuria in patients with chronic indwelling urethral catheters. J Infect Dis. 1982;146(6):719-723.

Bakke A, Digranes A. Bacteriuria in patients treated with clean intermittent catheterization. Scand J Infect Dis. 1991;23(5):577-582.

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Patient Presentation

Ms. Smith is a 27-year-old woman who presents to her PCP after just finishing a course of antibiotics for an upper respiratory infection with complaints of dysuria and foul-smelling urine. She also complains of frequency to void, but only able to get out a few drops at a time. She has had 4/10 abdominal discomfort for the past 5 days, endorses lower back pain, and denies any hematuria with urination. She denies nausea/vomiting and denies having a fever.

Past Medical History

• Type I diabetic
• Recent use of antibiotics for URI
• History of chlamydia at age 19

Pertinent Surgical History

• No surgical history

Pertinent Family History

• Mother healthy and alive at 56 years
• Father healthy and alive at 59 years
• Sister alive and type I diabetic at age 24 years old
• Healthy 3 year old son

Pertinent Social History

• Married to husband for 5 years
• Sexually active
• Spermicide as a contraceptive method
• Physically active and attends spinning class 5 times a week

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• URINALYSIS CASES AND CRITICAL THINKING

Gerald D. Redwine, PhD, MT(ASCP)

The physical and chemical examination of urine samples plays an essential role in the diagnosis of patients’ pathological conditions. However, the sheer number of routine urinalysis can minimize their significance, especially considering that most analyses are automated, which can foster complacency for less than apparent problems. As a result of seemingly more critical concerns, one may defer the interpretation for the clinician to assess. Nevertheless, detecting abnormal results and possible causes is required, regardless of whether the analysis was manual or automated. Knowing the effects of pigmentation, drugs, pH, and ascorbic acid, for example, are samples that always need attention.

Manual analysis is further complicated, with several idiosyncrasies innate to manufacturers. For example, differences in popular brands, such as, Multistix, that requires reading each chemical pad at the specific time indicated. But the Chemstrip and vChem strips readings are stable between one and two minutes, except leukocytes read at two minutes, all necessitating the need for special attention to the manufacturers’ instructions. Concerning ascorbic acid, knowing that Chemstrip eliminates ascorbic acid interference with blood by overlaying the pad with iodate, and the vChem strips have a detection pad for the substance; in contrast, knowing that the Multistix has neither, is essential. Finally, knowing to ignore the different coloration on the perimeter of the pad on all strips and asking for a recollect on extremely high pH is also vital.

How are the critical thinking skills needed for a urinalysis assessment best developed? In academia, it seemed best, following initial training, to have students complete weeks of daily intensive practice of the entire urinalysis (physical, chemical, and microscopic) in an open lab setting on multiple patient samples. In combination with these analyses, they were given case studies like the ones administered later in a practical examination. The following is a composite of the answer stating what they thought was the most probable cause to three of the 17 cases given on their exam, using Multistix, with further comments in parenthesis. Assessments constrained the students to answer the question under the given condition, knowing they would ask for a recollect in some instances.

• What would explain the apparent disagreement between the nitrite and leukocyte reaction?
• What accounts for the clarity of the sample in the chemical examination?
• What does the Acetest suggest about the chemical reactions, based on literature?
• Non-nitrate reducing organism. (i.e., bacteria, yeast, trichomonads, and chlamydia) Or Trauma. (Other less likely possibilities.)
• Large blood. (Also slightly enhanced the protein.)
• More sensitive because of the added glycine. (Glycine detects acetone. vChem strips have the same.)

• What could explain the single most unexpected finding within the chemical reactions?
• What could account for the protein and SSA discrepancy?
• What should the adjusted strip value read?
• What is the definitive source(s) for reporting the final specific gravity (SG) reading (manual/analyzer/and or name another source) on this specimen?
• With an SG = 1.040, what value is the final specific gravity?
• Negative leukocytes could result from any or all three of the following. 1) Alkalinity 2) >3g/dL glucose 3) High specific gravity.
• Alkaline pH can cause a false positive protein; also, the blood that is missing in the supernatant for the SSA could account for the 2+ SSA.
• Because pH is ≥ 6.5, then add .005 to the dip strip value. Strip SG = 1.035 . (Multistix only)
• Because of the ≥ 100 protein, then run on the refractometer. (Total Solid (TS) meter/Refractometer.)
• Subtract 0.003 for every 1 g/dl protein; subtract 0.004 for every 1 g/dl glucose. Report SG: 1.026 .

• What could explain the disagreement that exists within the chemical reactions?
• Explain the correlation between chemical reactions and the SSA?
• What are the two specific adjustments needed for the specific gravity?
• What is the final strip specific gravity?
• A non-nitrite reducing microbe such as Trichomonas or Chlamydia . Or postrenal trauma. (Other nitrite negative possibilities. Also, if not for the trace protein, ascorbic acid is suspect.) Best observation: Yellow-Green ~ Biliverdin. False-negative bilirubin. Hence, the need for a recollection and run on a fresh sample to ascertain the true values.
• Expected the SSA to be greater. Alkaline pH can cause a false positive protein, or in this case, falsely increase the value.
• Because pH is ≥ 6.5, then add .005 to the dip strip value. Because of the ≥ 100 protein, then run on the refractometer. TS (Total Solid) meter/Refractometer. (Multistix only)
• Strip SG = 1.015.

Responses to the open lab concept, despite significantly more than usual time commitment on behalf of all involved, and reagents, the sacrifices were met with positive feedback from the students on superseding their learning outcomes. The learning outcomes summarized is critical thinking applied to urinalysis case studies.

Reference: Brunzel, N. A., MS, MLS(ASCP) CM . Fundamentals of Urine and Body Fluid Analysis , 4th Edition

Gerald D. Redwine is an associate professor at Texas State University Clinical Laboratory Science Program in San Marcos, Texas.

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Article Contents

Introduction, case report, conflicts of interest statement, ethical approval.

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Educational case: a patient with proteinuria

• Article contents
• Figures & tables
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Christopher N Kassam, Vivian W M Yiu, Meryl H Griffiths, William G Petchey, Educational case: a patient with proteinuria, Oxford Medical Case Reports , Volume 2020, Issue 6, June 2020, omz148, https://doi.org/10.1093/omcr/omz148

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This is an educational case suitable for all readers, but aimed particularly at trainees preparing for MRCP. Using the example of a patient presenting to clinic with proteinuria, aspects of differential diagnosis, pathology and management are explored.

A 37-year-old male Caucasian administrator presented to general nephrology clinic after his GP noted 3+ proteinuria on urinalysis.

His symptoms included tiredness and frothy urine for 6 months. He had not experienced any haematuria, lower urinary tract symptoms, flank pain, ankle swelling, breathlessness or recent weight change. He had a past medical history of obstructive sleep apnoea and was not diabetic. He took no regular medications and had no known allergies. He had a family history of cardiovascular disease on his father’s side and lung cancer on his mother’s side. There was no family history of renal disease. He had never smoked. A recent HbA1c performed by his GP was 41 mmol/mol (5.9%).

On examination, the patient’s BMI was 38 kg/m 2 , and his blood pressure was 133/76 mmHg. There was no detectable peri-orbital or pedal oedema. His JVP was not raised. His chest was clear on auscultation and his kidneys were not palpable. There was no rash. Urinalysis confirmed 3+ proteinuria and no haematuria.

Diabetic nephropathy

Membranous nephropathy

Granulomatosis with polyangiitis

Lupus nephritis (class V)

Alport syndrome

Explanation: Membranous nephropathy is an immune-mediated glomerulopathy which is the commonest primary cause of nephrotic syndrome in Caucasian adults [ 1 ]. Diabetic nephropathy is a common cause of proteinuria, but HbA1c is not elevated and it is unusual for previously undiagnosed diabetes to present with proteinuria in the absence of other symptoms. Granulomatosis with polyangiitis is rare and tends to present with systemic malaise and multi-organ involvement; urinalysis typically shows both protein and blood. Class V lupus nephritis is a possibility in this case, but is less common than membranous nephropathy, and would often cause haematuria in addition. Alport syndrome is a genetic disorder (usually X-linked) caused by defects in type IV collagen synthesis; it is unlikely in the absence of a family history or deafness, and usually presents with progressive renal impairment rather than proteinuria. There is some evidence that primary focal segmental glomerulosclerosis may be overtaking membranous nephropathy as the leading primary cause of nephrotic syndrome, particularly in black patients; however, FSGS was not an option in this question [ 2 ].

Investigations were performed (Table 1). Additionally, screening tests for HIV, hepatitis B and hepatitis C were negative. Renal ultrasound demonstrated that both kidneys were of normal size, with no cysts or masses (bipolar length LEFT 11.3 cm, RIGHT 11.7 cm).

> 3.5 mg/mmol

> 30 mg/mmol

> 150 mg/mmol

> 250 mg/mmol

> 300 mg/mmol

Explanation: 24-hour urinary protein excretion is no longer routinely measured due to impracticality and inaccuracies in timing urine collection; it has largely been replaced by the spot measurement of albumin:creatinine or protein:creatinine ratio (PCR). An ACR of > 250 mg/mmol corresponds to a 24-hour urinary protein excretion of > 3.5 g, the threshold for nephrotic-range proteinuria. If urinary PCR is used, the threshold is 300 mg/mmol. An ACR of < 2.5 mg/mmol (males) or < 3.5 mg/mmol (females) is considered normal, while an ACR of 2.5–30 mg/mmol (males) or 3.5–30 mg/mmol (females) indicates microalbuminuria. Note that microalbuminuria is not usually detected by urine dipsticks.

A renal biopsy was performed to establish the underlying cause of the patient’s proteinuria. A biopsy of his left kidney was successfully taken. Representative sections are shown in Fig. 1 .

Representative sections from the biopsy of the patient’s left kidney, H&E stain.

Investigation results

Congo red staining was negative. Immunofluorescence showed some staining for IgM and complement C3 in sclerotic glomerular lesions, but was otherwise unremarkable.

Amyloidosis

Obesity-related glomerulopathy

Primary focal segmental glomerulosclerosis

Explanation: Obesity-related glomerulopathy (ORG) typically presents with sub-nephrotic proteinuria in patients with BMIs > 30 kg/m 2 . Nephrotic syndrome is not usually seen, even when the proteinuria reaches nephrotic range [ 3 , 4 ]. In case series, the prevalence of renal impairment at diagnosis has ranged from 33 to 44%, with 10–33% of patients eventually progressing to end-stage kidney disease [ 5–7 ]. However, in early stages of the disease, creatinine may be normal or low due to glomerular hyperfiltration. Pathologically, renal biopsy histology demonstrates glomerulomegaly and focal segmental glomerulosclerosis (predominantly perihilar in distribution), with non-specific immunofluorescence findings. In this case, the biopsy findings are not typical of either amyloidosis or membranous nephropathy. In addition, negative Congo red staining and myeloma screen make amyloidosis unlikely, while anti-phospholipase A2 receptor antibody is positive in 70% of patients with primary membranous nephropathy [ 1 ]. While the histological appearance of ORG has some similarities to that of diabetic nephropathy (so-called ‘diabetoid’ changes), this patient’s HbA1c indicates normal glycaemic control. Primary FSGS remains a possibility; however, patients commonly present with nephrotic syndrome, glomerulomegaly is not usually seen and a perihilar distribution of sclerotic lesions is typically associated with secondary (adaptive) causes of FSGS such as ORG. It is essential to distinguish between primary and secondary FSGS so as to avoid treating obese patients with high-dose corticosteroids for prolonged periods. Electron microscopy may further assist in making this distinction: typically in primary FSGS podocyte foot processes are diffusely effaced from early in the disease course, whereas in secondary FSGS, foot process effacement is segmental and develops more slowly [ 8 ].

Bariatric surgery

Spironolactone

Structured weight-loss programme

Watchful waiting

Explanation: There is no definitive evidence available as yet on the management of ORG. However, Renin-Angiotensin-Aldosterone blockade with an angiotensin converting enzyme (ACE) inhibitor or an angiotensin receptor blocker (ARB) is the most evidence-based intervention for reducing proteinuria and preventing progression to end-stage renal disease [ 3 ]. Indeed, NICE recommends that all patients with ACR > 70 mg/mmoL due to any cause should be offered an ACE inhibitor or ARB [ 9 ]. There is also some evidence that weight-loss interventions (particularly bariatric surgery) may induce rapid improvements in glomerular hyperfiltration and proteinuria, both in patients with ORG and more broadly in obese patients with CKD [ 3 ]. However, the literature on weight-loss interventions suffers from flaws in study design and limited follow-up, and provides little evidence regarding long-term progression to end-stage renal disease.

The patient was started on ramipril 5 mg OD and advised to return for 6-monthly review in nephrology clinic. After 12 years, his BMI had increased to 41 kg/m 2 , his serum creatinine had progressively risen to 622 μmol/L and his eGFR had fallen to 8 mL/min/1.73 m 2 . He was referred to the low-clearance clinic to discuss renal replacement therapy (RRT).

Automated peritoneal dialysis

Conservative management

Continuous ambulatory peritoneal dialysis

Intermittent haemodialysis

Kidney transplant

Explanation: While all patients should be offered the option of conservative management, this will not usually be the first choice in a young patient. Transplantation offers a clear survival benefit over any modality of dialysis irrespective of BMI, and current NICE guidelines suggest that patients should not be excluded from transplantation on the basis of BMI alone [ 10 , 11 ]. Kidney transplant is, therefore, the most appropriate option. However, BMI >  35 is associated with an increased risk of adverse outcomes including surgical complications and graft loss, and in practice, in the context of donor scarcity, many centres exclude very obese patients from transplantation or require weight loss prior to transplant listing [ 12 ]. Clinicians will, therefore, often find themselves offering other RRT modalities for obese patients, either long-term or as a bridge to transplant. There is no high-quality evidence regarding the effect of peritoneal dialysis versus haemodialysis on mortality or quality of life in adults, and the patient should be offered the choice of haemodialysis and peritoneal dialysis modalities depending on local service availability [ 13 ]. However, from a technical perspective, insertion of a peritoneal dialysis catheter would be difficult for a patient with BMI 41 kg/m 2 , potentially requiring a pre-sternal catheter, which is not available at all centres.

The pathogenesis of ORG is complex and incompletely understood. Obesity is known to be associated with increased circulating levels of angiotensin II, due in part to angiotensinogen synthesis in adipose tissue [ 14 ]. Increased angiotensin II results in efferent arteriole constriction and afferent arteriole dilatation (both directly and via tubuloglomerular feedback), leading to glomerular hyperfiltration. Increased glomerular pressure is thought to lead first to glomerulomegaly and eventually to podocyte detachment and FSGS lesions. There is also evidence that insulin resistance and alterations in circulating adipokine concentrations may directly contribute to podocyte loss [ 3 ].

The prevalence of obesity (defined as BMI > 30) among adults in England has risen from 15% in 1993 to 26% in 2016; similar rates are found in other parts of the UK [ 15 ]. All physicians will undoubtedly be required to manage ever-increasing numbers of obese patients. The obesity epidemic has important implications for renal medicine. Obesity is a major risk factor for both malignant and non-malignant renal disease: the relative risk for end-stage renal failure in obesity is 4.07, while 26% of non-malignant renal disease in industrialised countries is attributable to being overweight [ 16 ]. While much of this excess risk is due to the complications of obesity such as diabetes and hypertension, a sub-population of obese patients develop proteinuria in the absence of other risk factors. Studies on these patients have defined ORG as an independent pathological entity. Indeed, in the absence of routine renal biopsy, some evidence suggests that up to 10% of cases of presumed diabetic nephropathy may in fact be wholly or partly due to ORG [ 17 ].

As obesity rates continue to rise globally, the incidence of ORG is likely to rise in tandem. Being alert to the clinical presentation of ORG may facilitate early intervention with ACE inhibitors, helping to slow progression to end-stage kidney disease in these patients.

No conflicts of interest.

No funding.

No ethical approval required.

No consent required.

Couser WG . Primary membranous nephropathy . Clin J Am Soc Nephrol 2017 ; 12 : 983 – 97 .

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Neil Clancy, MD

Associate Chief of VA Pittsburgh Health System (VAPHS) and Opportunistic Pathogens Associate Professor of Medicine Director, Mycology Program Chief, Infectious Diseases Section VA Pittsburgh Health Care System Pittsburgh, Pennsylvania

Disclosure: Neil Clancy, MD, has the following relevant financial relationships: Advisor or consultant for: Astellas; Cidara; Merck; Needham & Company; Qpex; Scynexis; Shionogi; The Medicines Company Speaker or a member of a speakers bureau for: Merck; T2 Biosystems Grants for clinical research from: Astellas; Cidara; Melinta; Merck

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CME Reviewer

Amanda Jett, PharmD, BCACP

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CME / ABIM MOC / CE

Clinical challenge: case studies in recurrent complicated utis.

• Authors: Neil Clancy, MD

CME / ABIM MOC / CE Released: 8/20/2021

• THIS ACTIVITY HAS EXPIRED FOR CREDIT

Valid for credit through: 8/20/2022 , 11:59 PM EST

Target Audience and Goal Statement

This activity is intended for infectious disease specialists, urologists, primary care physicians, pharmacists, and other healthcare providers involved in the management of recurrent complicated urinary tract infections (UTIs).

The goal of this activity is to improve clinicians' ability to evaluate the role of newer antibiotic agents for the treatment of recurrent, complicated UTIs caused by multidrug-resistant organisms. 

Upon completion of this activity, participants will:

• Risk factors for multidrug-resistant infection in UTIs
• The use of an antibiogram to guide antibiotic selection
• The selection of appropriate therapies for the treatment of recurrent complicated UTIs

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CASE 1: PATIENT HISTORY AND PRESENTATION

Tara is a 26-year-old Korean American woman who presents to the emergency department (ED) with fevers, chills, and right-sided flank pain, which developed acutely during the previous night. After she telephoned her healthcare provider in the morning about these symptoms, she was told to go directly to the ED. She is sexually active in a jointly monogamous relationship with her boyfriend of 2 years. Her only standing medication is an oral contraceptive, which she takes regularly. Her medical history is significant for an asymptomatic horseshoe kidney that was found incidentally and approximately 1 episode of cystitis per year, characterized by dysuria. After developing symptoms of cystitis, she telephones her healthcare provider and receives a prescription for ciprofloxacin or trimethoprim-sulfamethoxazole. She does not recall providing a urine sample for urinalysis or culture in the past. Her last episode of dysuria was 2 weeks ago, for which she took ciprofloxacin "for a couple of days." Her symptoms resolved without apparent incident. Since the onset of her presenting symptoms, she took 2 doses of ciprofloxacin that were left over from her previous prescription.

• Abbreviations

The educational activity presented above may involve simulated, case-based scenarios. The patients depicted in these scenarios are fictitious and no association with any actual patient, whether living or deceased, is intended or should be inferred. The material presented here does not necessarily reflect the views of Medscape, LLC, or any individuals or commercial entities that support companies that support educational programming on medscape.org. These materials may include discussion of therapeutic products that have not been approved by the US Food and Drug Administration, off-label uses of approved products, or data that were presented in abstract form. These data should be considered preliminary until published in a peer-reviewed journal. Readers should verify all information and data before treating patients or employing any therapies described in this or any educational activity. A qualified healthcare professional should be consulted before using any therapeutic product discussed herein.

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Urine Tests

A Case-Based Guide to Clinical Evaluation and Application

• © 2020
• Victoria J.A. Sharp 0 ,
• Lisa M. Antes 1 ,
• M. Lee Sanders 2 ,
• Gina M. Lockwood 3

Department of Urology and Department of Family Medicine, University of Iowa, Iowa City, USA

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Department of Internal Medicine Division of Nephrology, University of Iowa, Iowa City, USA

Department of urology, university of iowa, iowa city, usa.

• Is the first-of-its-kind comprehensive text on the evaluation and applications of urine tests
• Is written by primary care and specialists
• Includes best practices and national guidelines from a variety of specialty associations

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About this book

Urine tests are used by a variety of primary care providers and specialists in order to diagnose, monitor and treat patients with various medical conditions. This first-of-its-kind text is a comprehensive clinical guide to the evaluation and application of urine tests. Clinical cases are used to highlight important aspects of urine testing. Further evaluation and management are then discussed based on the results of the urine tests.

Topics covered include financial considerations, regulations, proper collection, testing methods, dipstick analysis, microscopy as well as cancer and drug screening tests, among others. Each chapter contains specific objectives for focus of study. Pertinent images, algorithms and board style review questions for important topics are also included.

Written by nephrologists, urologists, other specialists and primary care physicians, Urine Tests uses a comprehensive approach to the clinical use of both common and uncommon urinetesting. Primarily appealing to practicing primary care physicians, this book is also a useful resource for specialists, nurse practitioners, physician assistants, physician fellows, residents and medical students alike.    

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Table of contents (17 chapters)

Front matter, urine: the golden elixir of life.

• M. Lee Sanders, Lisa M. Antes

Follow the Money: Costs, Reimbursement and Regulations of Urine Based Testing

• Matthew A. Uhlman, Victoria J. A. Sharp, Nora Kopping, Mark S. Uhlman

Going with the Flow: Proper Urine Testing Methods for Clinical Practice

• Gina M. Lockwood, Victoria J. A. Sharp

Urine Dipstick: Blood – The Spectrum of Red

• Alexandra J. Sharp, Victoria J. A. Sharp

Urine Dipstick: Proteinuria – Causes, Consequences and Diagnostic Approach

• Lewis Mann, Lisa M. Antes, M. Lee Sanders

Urine Dipstick: Urinary Nitrites and Leukocyte Esterase – Dipping into Murky Waters

• A. Ben Appenheimer, Bradley Ford

Urine Dipstick: An Approach to Glucosuria, Ketonuria, pH, Specific Gravity, Bilirubin and Urobilinogen – Undeniable Chemistry

• Puja T. Pape, Victoria J. A. Sharp, Jessica Rockafellow

Urine Microscopy: The Burning Truth – White Blood Cells in the Urine

• Andrew M. Vitale, Gina M. Lockwood

Urine Microscopy: Seeing Red – Understanding Blood in the Urine

• Christopher Meier, Gina M. Lockwood

Urine Microscopy: The Utility of Urinary Casts in Patient Care – Practical and Useful Tips for Busy Clinicians

• Stephanie J. Houston, M. Lee Sanders, Lyndsay A. Harshman

Urine Microscopy: Clouding Over – Bacteria, Yeast, Parasites and Zika

• Bradley Ford, Wendy Fiordellisi, Victoria J. A. Sharp, A. Ben Appenheimer

Urine Microscopy – Urine Made Crystal Clear

• Courtney Yong, Chad R. Tracy, Lisa M. Antes

Urine Testing in Children: Little People, Big Challenges

• Gina M. Lockwood, Douglas W. Storm

Urine Based Tests in the Diagnosis of Genitourinary Cancers

• Morgan Schubbe, Laila Dahmoush, KennethG. Nepple

Kidney Excretions: The Lyter Side of Urine

• Jeremy Steinman, Carly Kuehn, Lisa M. Antes

Other Common Uses for Urine Screening in Clinical Practice: Substance Use Disorders, Antipsychotic Adherence, Sexually Transmitted Infections

• Aubrey Chan, Puja T. Pape, M. Lee Sanders

Urine Tests: Solidifying Concepts – Questions and Answers

• M. Lee Sanders, Lisa M. Antes, Victoria J. A. Sharp, Gina M. Lockwood

Back Matter

Editors and affiliations.

Victoria J.A. Sharp

Lisa M. Antes, M. Lee Sanders

Gina M. Lockwood

About the editors

Dr. M Lee Sanders obtained his MD degree from the University of Tennessee Health Science Center after completion of a PhD in Pharmaceutical Sciences. He completed internal medicine residency and chief residency at the University of Iowa Hospitals and Clinics followed by completion of both a general nephrology and transplant nephrology fellowship at Vanderbilt University Medical Center. He is Board Certified in both Internal Medicine and Nephrology, and his current medical practice incorporates internal medicine, generalnephrology, and transplant nephrology. His academic interests include medical education and kidney transplant outcomes. 

Dr. Gina Lockwood obtained her MD degree from Southern Illinois University School of Medicine. She completed urology residency at the Medical College of Wisconsin. She completed her pediatric urology fellowship at Connecticut Children’s Medical Center and obtained her Master of Science degree in Clinical and Translational Research at University of Connecticut. She is Board certified in Urology. She currently practices pediatric urology and has research interests in patient and parent education and quality improvement.

Bibliographic Information

Book Title : Urine Tests

Book Subtitle : A Case-Based Guide to Clinical Evaluation and Application

Editors : Victoria J.A. Sharp, Lisa M. Antes, M. Lee Sanders, Gina M. Lockwood

DOI : https://doi.org/10.1007/978-3-030-29138-9

Publisher : Springer Cham

eBook Packages : Medicine , Medicine (R0)

Copyright Information : Springer Nature Switzerland AG 2020

Softcover ISBN : 978-3-030-29137-2 Published: 20 July 2020

eBook ISBN : 978-3-030-29138-9 Published: 19 July 2020

Edition Number : 1

Number of Pages : XXI, 389

Number of Illustrations : 6 b/w illustrations, 71 illustrations in colour

Topics : General Practice / Family Medicine , Primary Care Medicine , Urology

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Urine output on an intensive care unit: case-control study

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• Peer review
• Anthony W Solomon , specialist registrar 1 2 3 ,
• Christopher J Kirwan , specialist registrar 1 4 ,
• Neal D E Alexander , reader 5 ,
• Kofi Nimako , specialist registrar 1 6 ,
• Angela Jurukov , audit clerk 1 ,
• Rebecca J Forth , research fellow 7 ,
• Tony M Rahman , consultant 1 8
• on behalf of the Prospective Analysis of Renal Compensation for Hypohydration in Exhausted Doctors (PARCHED) Investigators
• 1 General Intensive Care Unit, St George’s Hospital, London, UK
• 2 Clinical Infection Unit, St George’s Hospital, London
• 3 Clinical Research Department, London School of Hygiene and Tropical Medicine, London
• 4 Department of Renal Medicine, St George’s Hospital, London
• 5 Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London
• 6 Department of Chest Medicine, St George’s Hospital, London
• 7 Portex Anaesthesia, Intensive Therapy and Respiratory Unit, Institute of Child Health, London
• 8 Department of Gastroenterology and Hepatology, St George’s Hospital, London
• Correspondence to: A W Solomon, Clinical Research Department, London School of Hygiene and Tropical Medicine, London WC1E 7HT anthony.solomon{at}lshtm.ac.uk
• Accepted 19 November 2010

Objective To compare urine output between junior doctors in an intensive care unit and the patients for whom they are responsible.

Design Case-control study.

Setting General intensive care unit in a tertiary referral hospital.

Participants 18 junior doctors responsible for clerking patients on weekday day shifts in the unit from 23 March to 23 April 2009 volunteered as “cases.” Controls were the patients in the unit clerked by those doctors. Exclusion criteria (for both groups) were pregnancy, baseline estimated glomerular filtration rate <15 ml/min/1.73 m 2 , and renal replacement therapy.

Main outcome measures Oliguria (defined as mean urine output <0.5 ml/kg/hour over six or more hours of measurement) and urine output (in ml/kg/hour) as a continuous variable.

Results Doctors were classed as oliguric and “at risk” of acute kidney injury on 19 (22%) of 87 shifts in which urine output was measured, and oliguric to the point of being “in injury” on one (1%) further shift. Data were available for 208 of 209 controls matched to cases in the data collection period; 13 of these were excluded because the control was receiving renal replacement therapy. Doctors were more likely to be oliguric than their patients (odds ratio 1.99, 95% confidence interval 1.08 to 3.68, P=0.03). For each additional 1 ml/kg/hour mean urine output, the odds ratio for being a case rather than a control was 0.27 (0.12 to 0.58, P=0.001). Mortality among doctors was astonishingly low, at 0% (0% to 18%).

Conclusions Managing our own fluid balance is more difficult than managing it in our patients. We should drink more water. Modifications to the criteria for acute kidney injury could be needed for the assessment of junior doctors in an intensive care unit.

Introduction

Assessing the intravascular fluid balance of critically ill patients is a crucial role of intensive care physicians. Adequate fluid resuscitation can optimise cardiac output and improve outcome, especially in sepsis or after major surgery. 1 2

When intrinsic renal function is normal and the urinary tract is unobstructed, urine output is a key indicator of intravascular volume status. In critically ill patients, the routine use of indwelling urinary catheters allows accurate hourly measurement of urine output. Such data are closely followed by doctors in intensive care. In doing so alongside their other multitudinous responsibilities, however, doctors’ own autologous hydration can be delayed; they might become “dry” (intravascularly deplete) as a result. We hypothesised that this should not occur to such an extent as to lower doctors’ urine output below that of the patients in the unit, as the latter often have one or more reasons for developing oliguria (hypoperfusion, acute or chronic renal damage, urinary tract obstruction). In this prospective case-control study we compared the urine output of intensive care doctors and their patients.

The study was performed in a 17 bed general intensive care unit in a tertiary referral hospital in south west London over 22 consecutive weekdays (excluding public holidays) from 23 March to 23 April 2009. The unit admits a mixture of trauma, elective and emergency post-surgical, and emergency medical admissions. There are separate neurological intensive care, cardiothoracic intensive care, and coronary care units in the trust.

All junior doctors working on the unit (ranging from foundation year 1 doctors to specialist registrars) who took responsibility for the daily clerking of one or more patients on day shifts during the study were fully informed of the objectives and were eligible to volunteer as cases. The weight of each doctor (wearing scrubs but no footwear, seated and still, having divested themselves of stethoscope, pager, and pocket contents) was determined with Marsden MPDC-250 professional weighing scales (Marsden, Henley, UK).

For each case, controls comprised the patients on the same unit clerked by the case that day. Each patient is routinely clerked on admission to the unit and again each morning by a nominated junior doctor, who might or might not have admitted or clerked the patient previously. On any day, a case can have been matched with more than one control. During data collection, patients (controls) were allocated to doctors (cases) by the specialist registrar in charge of the unit (based on multiple factors, including patients’ diagnoses and overall complexity, and the interests and experience of the available doctors), as normal; whenever practical, doctors do not clerk the same patient two days in a row. We determined the patients’ weights by self report or from relatives. If both of these sources were unavailable or thought to be unreliable, we recorded the most recent weight documented in the medical notes. If weight had not previously been documented, we recorded an estimated weight, with estimation performed jointly by nursing and medical staff. 3

Pregnancy, estimated glomerular filtration rate <15 ml/min/1.73 m 2 (chronic kidney disease stage 5), and renal replacement therapy (including renal transplantation) were exclusion criteria for both cases and controls because urine output for individuals with these characteristics was likely to be artificially high or low. Those included once as cases were eligible for later inclusion as controls, and vice versa 4 (subject to the hospital’s usual procedures for recruitment and allocation of medical staff, and criteria for patient admission to the intensive care unit).

On each data collection day, participating doctors emptied their bladders on arrival at work, noting the time at which they did so on anonymised charts fixed to the inside of the male and female staff changing rooms. On each subsequent occasion that they voided during the course of their working day, they measured the volume of urine voided using a wide mouthed 1l graduated plastic measuring jug (RML 200-003, Rochialle, Mountain Ash, Wales, UK) and recorded the amount on the appropriate chart. Regardless of whether or not they had the urge to do so, they voided once more at the conclusion of their shift, noting the volume of urine and the time at which it was passed.

Hourly urine volume passed by controls was recorded on flow charts, as normal. As day shifts for doctors start at 8 am and are scheduled to finish between noon and 6 pm (depending on rota) but occasionally overrun (because of emergencies or other unforeseen circumstances 5 ), we included control data for the period 8 am to 8 pm. For patients admitted to or discharged from intensive care during these hours, we included data only for the period in which they were in the unit, regardless of whether or not urine output was continuously monitored in the source or destination environment.

We placed no restrictions on the use by either doctors or controls of fluids (whether oral or intravenous) or diuretics (including loop diuretics, thiazides, and foods and drinks containing caffeine) with the exception of alcohol, which was not used by either group. Each participating doctor was offered a single 300 ml cup of caffeinated coffee, made up to strengths that varied from day to day (as dictated by the consultant in charge), at the multidisciplinary team ward round each morning, but he or she was not obliged to drink it: its consumption and any subsequent fluid intake were at the discretion of the individual and not recorded. None of our cases or controls fasted during the period of the study for religious or other reasons.

Control data were entered into Microsoft Excel and transferred to Microsoft Access; case data were entered directly into Access.

Statistical analyses

The exposure of main interest was oliguria as a binary variable. A commonly accepted definition of oliguria is a urine output <0.5 ml/kg for each of six or more consecutive hours, which is thought to confer “risk” of renal injury; when urine output <0.5 ml/kg persists for 12 or more consecutive hours, the kidneys are designated to be “in injury.” 6 Use of this definition of oliguria was possible for controls, as their urine output was measured hourly, but lack of routine catheterisation of doctors on shift meant that hourly output data were not available for cases. We therefore defined oliguria for both cases and controls as a mean urine output <0.5 ml/kg/hour over a period of six or more hours of measurement.

The sample size was calculated to allow detection of an association between being oliguric and being an intensive care unit doctor. Assuming three controls per case and a 25% prevalence of oliguria in controls, we anticipated requiring 410 case days to detect an odds ratio of 1.5. 4 The unit of analysis was a stratum consisting of one day’s data from a case (doctor) and one day’s data from each of one or more matched controls (patients). Oliguria was evaluated in terms of the odds ratio of being a case, relative to being a control, on any given day. 4 Our secondary analysis looked for a “dose response effect,” 7 investigating whether urine output analysed as a continuous variable tended to be lower in cases than in controls. Both analyses used conditional logistic regression, matching on stratum. To allow for the presence of some of the cases in multiple strata, we inflated standard errors using the “sandwich” estimator 8 ; we did not, however, adjust for the presence of the same controls in multiple strata on different days. We performed our analyses in Stata version 11 (StataCorp, College Station, TX, USA).

Nineteen junior doctors (12 men, seven women) worked a total of 127 weekday day shifts during the 22 days of data collection; this period spanned a rota changeover, so the low mean number of shifts per doctor should not be interpreted as suggesting that the rota was light. No doctors were excluded on the basis of pregnancy, known stage 5 chronic kidney disease, or renal replacement therapy. On nine of these days, the specialist registrar in charge of the unit did not take primary responsibility for clerking any patients. There were therefore 118 eligible case days. Eighteen doctors (12 men, six women; 95%) volunteered for the study, contributing a total of 87 case days (range per case 1-13 days, median 5, 74% of eligible case days). Non-participation on any day was invariably attributed to forgetfulness.

For case days, mean and median urine outputs were 0.77 ml/kg/hour and 0.68 ml/kg/hour respectively. In 22 (25%) of 87 case days, the mean shift long urine output was <0.5 ml/kg/hour. Twenty of these shifts lasted more than six hours, including one that lasted for more than 12 hours (mean shift length 9.2 (SD 1.9) hours, range 4.5-12.3 hours). If we assume that doctors’ urine output was relatively constant throughout each shift, they were “at risk” of acute kidney injury (based on urine output criteria 6 ) on 19 shifts (22%) and “in injury” on one further shift (1%). Ten (six men, four women; 55%) of 18 cases had at least one day (range 1-3 days) “at risk” of renal injury or worse over the course of the study.

For the 87 case days, there were 209 control days in which controls were matched to participating cases. We excluded 13 control days because the controls received renal replacement therapy on the day in question and one control day because of missing data on urine output. We therefore analysed data for 195 control days paired to case days in 87 strata; each stratum had an average of 2.2 control days. Controls had mean urine output <0.5 ml/kg/hour on 29 (15%) of these 195 control days.

Pooling 20 oliguric case days together with 29 oliguric control days and considering oliguria as a risk factor, the odds ratio for being a case rather than a control (given the presence of oliguria) was 1.99 (95% confidence interval 1.08 to 3.68, P=0.03). With output assessed as a continuous variable, for each additional 1 ml/kg/hour mean urine output, the odds ratio for being a case rather than a control was about one quarter (0.27, 0.12 to 0.58, P=0.001). For both primary and secondary analyses, being a doctor was associated with lower urine output.

Oliguria was significantly more frequent, and urine outputs significantly lower, in the doctors than in the patients they cared for. Our data monitoring committee therefore stopped the study early on safety grounds. (Several of us also reached the end of our intensive care unit attachment.)

The incidence of urine outputs equivalent to risk and injury in our prospective cohort of day shift doctors in intensive care units was startlingly high, at 22% and 1% respectively. Doctors were twice as likely as their patients to be oliguric. The RIFLE criteria, used widely to describe and classify acute kidney injury in critically ill patients, incorporate the assessment of urine output (measured hourly) adjusted for body weight. 6 Because hourly urine output data were not available for doctors in this study, we modified the RIFLE definitions so that we assessed mean hourly output rather than hour by hour output. Notwithstanding this change, the incidence of urine outputs equivalent to RIFLE risk and injury in our prospective cohort of dayshift intensive care doctors was startlingly high, at 22% and 1%, respectively. Doctors were twice as likely as their patients to be oliguric. We hope (and expect, given that most do not work as hard as us) that these results are not generalisable to the whole UK medical workforce.

A surprising lack of mortality

Ostermann and Chang determined the incidence of acute kidney injury for 41 972 admissions to 22 intensive care units in Germany and the UK between 1989 and 1999. 9 They determined that 7207 (17%) patients were “at risk” of acute kidney injury at some time during their stay in intensive care and 4613 (11%) had “injury.” In that series, patients without acute kidney injury had mortality rates in hospital of 8%, while those with risk or injury had mortalities of 21% and 46%, respectively. 9 The cumulative 0% (95% confidence interval 0% to 18%) mortality in our series of (frequently oliguric) intensive care unit doctors seems nothing short of miraculous in comparison and is presumably attributable to the robust constitutions of doctors on our unit. We did not collect mortality data on controls.

The RIFLE criteria are a relatively recent innovation and are subject to ongoing debate and refinement. 10 In a recent systematic review, the relative risk of death conferred by risk, injury, or failure according to RIFLE was lower in studies that used both creatinine and urine output criteria, compared with studies using creatinine alone. 11 In other words, urine output might be a “softer” marker of acute kidney injury than changes in serum biochemistry. This could explain why, for each stratum of acute kidney injury, mortality was higher in the Ostermann and Chang series (in which the classification of acute kidney injury was based solely on serum creatinine values 9 ) than in our cases (in which the analysis used only urine output data). An alternative explanation could be the need for separate acute kidney injury criteria in patients in intensive care units and their doctors.

In any event, mortality was not a prespecified outcome of our study, and our main finding— that intensive care unit doctors are twice as likely as their patients to be oliguric—remains striking. Of course, as already mentioned, all our controls had urine output monitored on an hourly basis by experienced intensive care nurses, 24 hours a day; such data are not merely recorded but acted on. Nursing and medical personnel working on the unit are trained to repeatedly assess patients for intravascular volume depletion and, whenever necessary, appropriately intervene to correct it. With such close and continuous supervision, we expected the incidence of prolonged periods of low urine output because of inadequate filling in controls to be low. Similar close monitoring of urine output with consequent appropriate intervention for doctors has been declined by our nursing staff, even after presentation of these results, and despite advice from the Royal College of Nurses that “looking after colleagues . . . helps to build trust and increase feelings of security” in the workplace. 12 This might be an important issue to address as our data suggest that auto-fluid balance management is more difficult than auto-appendectomy, which has been successful in 100% of published attempts during the past five decades. 13 An obvious parallel conclusion to be drawn here is that medicine is far more complex than surgery.

Accuracy of methods

Our keenness to involve nursing staff in measuring urine output in doctors and disappointment at their rebuff should not be interpreted as indicating a lack of confidence from the authors in the accuracy of doctors’ measurement of urine volume. The common belief that timed urine self collections are inherently inaccurate is, in fact, a misconception. In a 2008 UK study of dietary sodium intake supported by the Medical Research Council and the National Centre for Social Research, 780 members of the general public were selected by random digit dialling of telephone numbers and asked to perform a 24 hour urine collection. 14 Completeness of collection was assessed through oral administration of three 80 mg para-amino-benzoic acid (PABA) tablets during the collection period; collections containing 85-110% of administered PABA were considered complete. Of 751 samples for which PABA results were available, urine collection was considered complete or near complete in 692 (92%). In comparison with that work, the circumstances of our study were far more conducive to accurate collection. Our urine was self collected by medically trained individuals in a single location to which participants, by virtue of their work commitments, were essentially confined for the duration of their shift; the unit had one male and one female washroom, and notices concerning the study were prominently displayed in both. The study was a common topic of conversation in the unit at the time it was conducted. Supplementary personal reminders of the importance of accurate collection were given to each participating doctor on a daily basis. In addition, all our collections were for considerably shorter periods than 24 hours and did not include normal hours of sleep, when complete collection is presumably more difficult to ensure.

Study weaknesses

There are, however, several limitations to our analysis. We did not prescribe or record the intake of fluids in cases, so did not attempt to analyse the association of fluid intake volume and urine output volume for either cases or controls. Caffeine intake was also not restricted or recorded. If caffeine consumption by doctors did have a diuretic effect, it would have resulted in a reduction in the observed difference between cases and controls, but the effect of caffeine on increasing urine output is probably generally overestimated. It had no impact on urine production during three hours of cycling at 60% VO 2 max 15 or two hours of cycling at 60-75% VO 2 max followed by 15 minutes of maximal effort cycling 16 : physiological work intensities that are virtually identical to our work intensities on the unit. More generally, chronic caffeine use at doses of 3-6 mg/kg/day has no impact on urine output, renal function, or fluid and electrolyte balance. 17 We were unable to record an objective measure of each doctor’s stress each day without unduly disrupting clinical activity and can therefore not exclude an antidiuretic effect of stress induced vasopressin release. We also cannot rule out a Hawthorne effect (the tendency of study participants to positively modify behaviours that are under observation). Finally, we did not attempt to ultrasonographically exclude postmicturition urinary retention in our cases at the end of each shift.

Implications

Oligoanuria is usually acute renal success rather than failure, being a sophisticated response to tubular damage caused by renal hypoperfusion or nephrotoxins, preventing life threatening polyuria when reabsorption of glomerular filtrate is impaired. 18 Increased concentration of chloride at the macula densa, however caused, is interpreted as an imbalance between filtration and reabsorption and leads via multiple mechanisms to a reduction in glomerular filtration, conserving intravascular volume. 18 The frequency with which this response was manifest in our doctors could (as suggested by our renal and intensive care physician) be interpreted as a demonstration of the physiological superiority of doctors in intensive care units or merely show (as suggested by the rest of us) that we should try to drink more water while on shift. We need a functioning water fountain in the staff room and the sense to go and drink from it.

What is already known on this topic

Oliguria is a common occurrence in patients admitted to intensive care and is associated with a marked increase in morbidity and mortality

What this study adds

Oliguria occurs twice as frequently in junior doctors on an intensive care unit as in their patients

This oliguria was not associated with increased mortality

Markers of acute kidney injury in junior intensive care unit doctors might diverge from those for the intensive care unit population as a whole

Cite this as: BMJ 2010;341:c6761

We thank the medical, nursing, administrative and cleaning staff of St George’s general intensive care unit for their support and encouragement and all our cases for their careful and good humoured participation. The PARCHED Investigators are: Aleksandar Aleksic, Neal D E Alexander, Nawaf Al-Subai, Jonathan Ball, Maurizio Cecconi, Arup Chakraborty, Richard Dodds, Costandine Fakiris, James Fletcher, Rebecca J Forth, Tim Gatheral, Petrut Gogalniceanu, Michael Grounds, Mark Hamilton, Hooi-Ling Harrison, Eloise Helme, Robin Johns, Angela Jurukov, Christopher J Kirwan, Jane Kung, Greg McAnulty, Nighat Nadeem, Phil Newman, Kofi Nimako, Oluwakemi Okubote, Kayur Patel, Barbara Philips, Tony M Rahman, Andrew Rhodes, Rajnish Saha, Anthony W Solomon, Shelley Vamadevan, Jo Wilson, Mark Wyldbore.

Funding: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Competing interests: Several authors have been surprised by the colour and particulate nature of the water that emerges from the water cooler in the intensive care unit staff room and would be keen to be able to drink water that doesn’t first require filtering through a shirt. All authors have completed the Unified Competing Interest form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare that they have no other financial or non-financial interests that may be relevant to the submitted work.

Contributors: TMR had the original idea for the study. AWS prepared a draft study design, which was developed by all the authors. AWS, CJK, NDEA, and RJF carried out the analyses. AWS wrote the first draft of the paper. All authors contributed to further drafts and had full access to all data. TMR is guarantor.

Ethical approval: The study protocol was reviewed by the Wandsworth Research Ethics Committee, who ruled that the study was a survey and that therefore, under NHS research governance arrangements, did not require formal ethical approval (00105.09).

Data sharing: Anonymised data are available, on request, from AWS at anthony.solomon{at}lshtm.ac.uk .

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode .

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Clinical pearls, case study: tea-colored urine in a patient with diabetic ketoacidosis.

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Hylton V. Joffe , Martin J. Abrahamson; Case Study: Tea-Colored Urine in a Patient With Diabetic Ketoacidosis. Clin Diabetes 1 October 2004; 22 (4): 197–198. https://doi.org/10.2337/diaclin.22.4.197

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C.S., a previously healthy 26-year-old Cantonese woman, presented with 6 days of nausea, vomiting, occasional fevers, and nonspecific abdominal pain that progressed to myalgias, polyuria, polydipsia, fatigue, and delirium. She had been asleep in bed for many hours preceding admission. Her only medication was an oral contraceptive, and she did not use herbals or alcohol. Her father had type 2 diabetes.

In the emergency room, she was mildly delirious, hyperventilating,afebrile, and dehydrated. She weighed 133 lb, her pulse was 110 bpm, and her blood pressure was 102/62 mmHg. The physical exam was otherwise normal.

Urinalysis revealed 4+ glucose and ketones, large blood without red blood cells, and no infection. The urine was tea-colored. Plasma glucose was 809 mg/dl, betahydroxybutyrate 6.9 mmol/l, lactate 3.2 mmol/l, sodium 126 mmol/l,potassium 4.9 mmol/l, creatinine 2.2 mg/dl, carbon dioxide 9 mmol/l,leukocytes 24,800/ml, arterial pH 7.06, and partial pressure of arterial carbon dioxide (PaCO 2 ) was 15 mmHg. Toxicology screen was negative,phosphate was 3.0 mmol/l, alanine aminotransferase was 299 IU/l, and aspartate aminotransferase was 782 IU/l, with normal bilirubin and alkaline phosphatase levels. Creatine kinase (CK) was 46,305 IU/l. Troponin I peaked at 5.8 ng/ml,but C.S. reported no chest pain, and electrocardiogram showed only sinus tachycardia. Islet cell, insulin, and glutamic acid decarboxylase antibodies were negative. Her hemoglobin A 1c was 6.7%.

Treating physicians diagnosed diabetic ketoacidosis (DKA) and rhabdomyolysis and initiated intravenous insulin and fluids with bicarbonate. Within 18 hours, C.S. was alert and oriented, and the metabolic abnormalities had been corrected. She was then transitioned to glargine insulin with pre-meal lispro insulin. CK peaked at 51,330 IU/l, but serum creatinine normalized. Blood and urine cultures and serology for acute cytomegalovirus and Epstein-Barr virus infections were negative.

How often is rhabdomyolysis associated with DKA?

What is the mechanism of DKA-mediated muscle injury?

Should the management of DKA be modified when there is co-existing rhabdomyolysis?

Do patients who present with DKA and rhabdomyolysis have a worse prognosis than patients presenting with DKA only?

Rhabdomyolysis occurs in as many as 50% of patients presenting with DKA or the hyperglycemic hyperosmolar nonketotic syndrome (HHNK) and varies in severity from mildly elevated CK levels with no symptoms to markedly elevated CK with acute renal failure, possibly requiring hemodialysis. 1 - 3   DKA and HHNK patients with rhabdomyolysis have higher blood glucose concentrations, serum osmolalities, and serum creatinine measurements than do those without rhabdomyolysis. 1 - 3   However, the mechanism of DKA-mediated muscle injury is uncertain. Theories include insufficient energy delivery to muscle, hyperosmolar effects, and underlying metabolic defects, such as McArdle's (myophosphorylase deficiency causing glycogen accumulation and reduced muscle ATP generation, usually characterized by fatigue, exercise intolerance, and myalgias). 1  

Although CK measurements are often obtained in older patients to rule out myocardial infarction as a precipitant for DKA, CK levels are not routinely tested in younger patients because their likelihood of myocardial ischemia is low. Furthermore, troponin measurements, which are more specific markers for myocardial injury, are replacing CK testing in many centers. Therefore,rhabdomyolysis associated with DKA may be overlooked, resulting in further complications, such as renal failure.

Nonetheless, rhabdomyolysis is important to diagnose because significant potential complications, such as acute renal failure, may be averted with appropriate therapy. Although controlled clinical trials are lacking, case series and animal data support the use of bicarbonate therapy, aggressive fluid resuscitation, and possibly mannitol infusion in patients with severe rhabdomyolysis to prevent acute renal failure, which may occur in as many as one-fourth of patients with rhabdomyolysis and HHNK. 3 - 5  

Rhabdomyolysis may also be associated with a high 1-week mortality rate in patients with DKA and HHNK. One report 2   described a fourfold higher 1-week mortality in patients with DKA and rhabdomyolysis compared to patients with DKA only (38.5 vs. 9.7%). Patients with HHNK and rhabdomyolysis also had a higher mortality rate compared to patients with HHNK only (35.5 vs. 25.4%).

C.S.'s relative immobilization possibly contributed to the extreme CK elevation. Perhaps she had a Coxsackie virus infection, characterized by fever, nausea, vomiting, myocarditis, rhabdomyolysis, and new-onset diabetes. Unfortunately, we considered this diagnosis when laboratory testing to confirm it was no longer possible.

Rhabdomyolysis occurs commonly in patients presenting with DKA but is usually subclinical

Patients who present with DKA and severe rhabdomyolysis may have higher short-term mortality rates than patients presenting with DKA only.

Serum CK is recommended when DKA patients have other risk factors for rhabdomyolysis (prolonged bed rest, significant alcohol consumption, drug use,and toxin exposure) or signs and symptoms of rhabdomyolysis (myalgias, urine dipstick with heme but no red blood cells, or tea-colored urine).

Consider adding bicarbonate and mannitol to insulin and intravenous fluids when DKA patients present with severe rhabdomyolysis.

Hylton V. Joffe, MD, is a clinical and research fellow in the Division of Endocrinology, Diabetes, and Hypertension at the Brigham and Women's Hospital and Harvard Medical School, and Martin J. Abrahamson, MD, is acting chief medical officer at the Joslin Diabetes Center and an associate professor of medicine at Harvard Medical School, in Boston, Mass.

Note of disclosure:   Dr. Abrahamson has received honoraria for speaking engagements from Aventis, which makes glargine, and Eli Lilly, which makes lispro insulin.

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Case Study: Four-Year-Old Male with Red Urine and Fever

• Agenda for Nematology Research
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A four-year-old male presents to the emergency department with a history of six days of fever and acute onset of red colored urine. Birth history and past medical history are unremarkable. Family history is non-contributory. He has a two-year-old sister who is healthy. There has been no recent travel. He was seen by his PCP approximately five days ago for evaluation of cough and rhinorrhea and was prescribed Augmentin for an ear infection. ROS is negative for dysuria, bloody stools, hemoptysis, or epistaxis. He has no increased bruising, no petechiae, and no extremity pain. He has been having intermittent fevers for three days.

Vitals: Temperature 104.6 degrees Fahrenheit, HR 100, RR 22, Oxygen saturations 98% on room air. Physical Exam: (+) scleral icterus, (+) jaundice, (+) soft flow murmur on cardiac exam. Physical exam is otherwise normal.

Labs: Initial hemoglobin 10.4 g/dL--&gt; decreased to 6.3 g/dL 12 hours later, Platelets 153,000 cells/UL, Reticulocyte count 0.4%, White blood cells 11.1 x10 3 cells/UL (48% bands, 16% lymphocytes), Absolute neutrophil count 7.90 x 10 3 cells/UL. Coagulation studies normal. Liver function test are normal. LDH is 5056 Units/ml, haptoglobin 12 mg/dL (low). Unconjugated bilirubin is 3.7 mg/dL, Conjugated bilirubin is 1.2 mg/dL. Electrolytes are all within normal limits. Viral panel is pending.

DAT: IgG, C3 (+).

Urinalysis: dark, red-brown urine, 3+ blood, 3+ protein, 0-4 RBCs/hpf, 0-4 WBCs/hpf, urobilinogen &gt;8mg/dL.

Case study submitted by Robyn Dennis, MD, Texas Children’s Cancer Center, Houston, TX.

1. What would be the next best test to help determine this patient’s diagnosis?

• Mycoplasma titers
• Abdominal ultrasound to detect splenomegaly
• Donath-Landsteiner assay
• Peripheral smear

2. What is the best initial therapy for this patient?

• Emergent plasmapheresis
• Warmed intravenous fluids, packed red blood cell transfusion, observation
• Splenectomy

Answers: (1) C; (2) B.

Explanation

This patient's clinical presentation and laboratory results suggest that he has a form of autoimmune hemolytic anemia (AIHA). More specifically, this child has a type of paroxysmal cold hemoglobinuria also known as Donath-Landsteiner hemolytic anemia (DLHA). DHLA is relatively rare (3/100,000) representing 30 percent to 40 percent of autoimmune hemolytic anemia in children. DLHA is caused by Donath-Landsteiner (D-L) auto antibody activation against the P-antigen on the red blood cell (RBC), which causes activation of complement, resulting in RBC membrane perforation and intravascular hemolysis (hence, the red urine and elevated urobilinogen in the urine). D-L auto-antibodies appear approximately one week following an acute illness, usually a virus, causing sudden onset of hemoglobinuria, jaundice, and anemia. Direct antibody test (DAT) is typically positive. C3, IgG, and P-antigen are positive. This is in contrast to cold agglutinin disease (CAD) which is typically IgM positive. Anemia and reticulocytopenia may be seen. The next best test to confirm his diagnosis is the Donath-Landsteiner assay which exposes the patient’s plasma to normal plasma at varying temperatures to determine the temperature at which RBCs are lysed by D-L autoantibody-associated complement fixation. RBC hemolysis due to D-L autoantibody activation typically occurs at cold temperatures (28-31 degrees Fahrenheit). Although evaluation of viral titers such as mycoplasma may help determine the etiology it will not confirm the diagnosis, however a treatable etiology should always be investigated. Hepatosplenomegaly may be observed in 25 percent of cases but is not specific to DLHA. A peripheral smear is always essential for diagnosis of hemolytic anemia and may reveal shistocytes, spherocytes, and/or rouleaux formation (more suggestive of warm autoimmune hemolysis). The best initial therapy for this patient is to keep him warm (gloves, hat, warming blanket, etc.). Warmed intravenous fluids and red blood cells are essential. If an underlying etiology is determined (i.e., mycoplasma infection) it should be treated. The most likely etiologies for this patient’s AIHA are the history of a preceding viral illness +/- initiation of Augmentin (several commonly prescribed medications have been associated with this form of AIHA). Splenectomy is typically reserved for refractory cases. Plasmapheresis should only be used in severe cases that are refractory to initial therapy. The role of steroids in D-L AIHA is controversial. Generally, this disease is self-limited in children and young adults, although antibodies may persist for up to three months. Recurrence may occur but is rare in children.

American Society of Hematology. (1). Case Study: Four-Year-Old Male with Red Urine and Fever. Retrieved from https://www.hematology.org/education/trainees/fellows/case-studies/child-red-urine-fever .

American Society of Hematology. "Case Study: Four-Year-Old Male with Red Urine and Fever." Hematology.org. https://www.hematology.org/education/trainees/fellows/case-studies/child-red-urine-fever (label-accessed September 07, 2024).

"American Society of Hematology." Case Study: Four-Year-Old Male with Red Urine and Fever, 07 Sep. 2024 , https://www.hematology.org/education/trainees/fellows/case-studies/child-red-urine-fever .

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HELLP Syndrome: a biopsychosocial case report

• Felicia Deonarine https://orcid.org/0009-0001-8825-2311

This case concerns a 30 year old female patient (HS), G2P1 (2 gravidity, 1 parity), who was admitted to the high dependency unit at Cork University Maternity Hospital in Cork, Ireland at 37 weeks and 1 days’ gestation. She was admitted after experiencing a 5 minute tonic-clonic seizure at home with no obvious relieving factors. Relevant positive symptoms included nausea, headache, and right hypochondrial pain. Relevant negative symptoms included denying tongue biting, incontinence, speech or visual disturbances, sensory or mental aura, vomiting and cyanosis. There were no drugs, trauma, recent illness or history of previous seizures. On examination, HS was confused and displayed signs consistent with pregnancy. In addition, a focused examination revealed hypertension, hyperreflexia, right hypochondrial pain, and lower limb oedema. The investigations included a urine dipstick, CT scan and blood tests which showed anaemia, low platelets and proteinuria. The history, examination and investigations in this case were consistent with a presentation of HELLP (haemolysis, elevated liver enzymes and low platelets) syndrome.  In this case report, the biopsychosocial aspects of the patient’s recovery are discussed.

Wade DT, Halligan PW. The biopsychosocial model of illness: a model whose time has come. Clin Rehabil. 2017;31(8):995–1004.

Engel GL. The clinical application of the biopsychosocial model. Am J Psychiat. 1980;137(5):535–44.

Portis R, Jacobs MA, Skerman JH, Skerman EB. HELLP syndrome (hemolysis, elevated liver enzymes, and low platelets) pathophysiology and anesthetic considerations. Aana J. 1997;65(1):37–47.

Fox R, Kitt J, Leeson P, Aye CYL, Lewandowski AJ. Preeclampsia: Risk Factors, Diagnosis, Management, and the Cardiovascular Impact on the Offspring. J Clin Medicine. 2019;8(10):1625.

Haram K, Svendsen E, Abildgaard U. The HELLP syndrome: Clinical issues and management. A Review. Bmc Pregnancy Childb. 2009;9(1):8.

Kaur AP, Kaur N, Dhillon SPS. HELLP syndrome and its implications on maternal and perinatal outcome. Int J Reproduction Contracept Obstetrics Gynecol. 2017;7(3):1007–11.

Wallace K, Harris S, Addison A, Bean C. HELLP Syndrome: Pathophysiology and Current Therapies. Curr Pharm Biotechno. 2018;19(10):816–26.

Easterling T, Mundle S, Bracken H, Parvekar S, Mool S, Magee LA, et al. Oral antihypertensive regimens (nifedipine retard, labetalol, and methyldopa) for management of severe hypertension in pregnancy: an open-label, randomised controlled trial. Lancet. 2019;394(10203):1011–21.

Barton JR, Sibai BM. Gastrointestinal Complications of Pre-eclampsia. Semin Perinatol. 2009;33(3):179– 88.

Morrison JJ, Crosby DA, Crankshaw DJ. In vitro contractile effects of agents used in the clinical management of postpartum haemorrhage. Eur J Pharmacol. 2016;789:328–33.

Kidner MC, Flanders-Stepans MB. A Model for the HELLP Syndrome: The Maternal Experience. J Obstetric Gynecol Neonatal Nurs. 2004;33(1):44–53.

Pampus M van, Wolf H, Schultz WW, Neeleman J, Aarnoudse J. Posttraumatic stress disorder following preeclampsia and HELLP syndrome. J Psychosom Obst Gyn. 2004;25(3–4):183–7.

Bedaso A, Adams J, Peng W, Sibbritt D. The relationship between social support and mental health problems during pregnancy: a systematic review and meta-analysis. Reprod Health. 2021;18(1):162.

Aziato L, Odai PNA, Omenyo CN. Religious beliefs and practices in pregnancy and labour: an inductive qualitative study among post-partum women in Ghana. Bmc Pregnancy Childb. 2016;16(1):138.

Heitzman J. Impact of COVID-19 pandemic on mental health. Psychiatr Pol. 2020;54(2):187–98.

• Case Reports

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Blood-, tissue- and urine-based prognostic biomarkers of upper tract urothelial carcinoma.

1. Introduction

2. materials and methods, 3.1. blood-based biomarkers, 3.1.1. c-reactive protein, 3.1.2. fibrinogen, 3.1.3. complete blood count (cbc), 3.1.4. neutrophil to lymphocyte ratio, 3.1.5. systemic immune–inflammation index (sii), 3.1.6. albumin, 3.1.7. albumin to globulin ratio (agr), 3.1.8. prognostic nutritional index (pni), 3.1.9. lactate dehydrogenase (ldh), 3.1.10. de ritis ratio, 3.1.11. alkaline phosphatase (alp), 3.1.12. renal function tests, 3.1.13. cholinesterases, 3.1.14. matrix metalloproteinases (mmps), 3.1.15. growth differentiation factor-15 (gdf-15), 3.2. tumor tissue-based biomarkers, 3.2.1. e-cadherin, 3.2.2. ki-67, 3.2.4. murine double minute 2 (mdm2), 3.2.5. the urokinase-type plasminogen activator (upa) system, 3.2.6. sry-related hmg-box 2 (sox2), 3.2.7. the brca1-associated protein-1 (bap1), 3.2.8. programmed death-ligand 1 (pd-l1), 3.2.9. human epidermal growth factor receptor (her-2), 3.2.10. enhancer of zeste homolog 2 (ezh2), 3.2.11. matrix metalloproteinase 11 (mmp-11), 3.2.12. insulin-like growth factor messenger rna-binding protein 3 (imp3), 3.2.13. pyruvate dehydrogenase kinase 3 (pdk3), 3.3. urine-based biomarkers, 3.3.1. dna methylation, 3.3.2. fluorescence in situ hybridization (fish), 3.3.3. b2-microglobulin (b2-mg), 3.3.4. urine cytology, 4. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Łaszkiewicz, J.; Krajewski, W.; Sójka, A.; Nowak, Ł.; Chorbińska, J.; Subiela, J.D.; Tomczak, W.; Del Giudice, F.; Małkiewicz, B.; Szydełko, T. Blood-, Tissue- and Urine-Based Prognostic Biomarkers of Upper Tract Urothelial Carcinoma. Diagnostics 2024 , 14 , 1927. https://doi.org/10.3390/diagnostics14171927

Łaszkiewicz J, Krajewski W, Sójka A, Nowak Ł, Chorbińska J, Subiela JD, Tomczak W, Del Giudice F, Małkiewicz B, Szydełko T. Blood-, Tissue- and Urine-Based Prognostic Biomarkers of Upper Tract Urothelial Carcinoma. Diagnostics . 2024; 14(17):1927. https://doi.org/10.3390/diagnostics14171927

Łaszkiewicz, Jan, Wojciech Krajewski, Aleksandra Sójka, Łukasz Nowak, Joanna Chorbińska, José Daniel Subiela, Wojciech Tomczak, Francesco Del Giudice, Bartosz Małkiewicz, and Tomasz Szydełko. 2024. "Blood-, Tissue- and Urine-Based Prognostic Biomarkers of Upper Tract Urothelial Carcinoma" Diagnostics 14, no. 17: 1927. https://doi.org/10.3390/diagnostics14171927

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Metformin May Help Manage Central Centrifugal Cicatricial Alopecia, Study Suggests

Edited by Gargi Mukherjee

September 06, 2024

Metformin significantly improved symptoms and resulted in hair regrowth in Black women with treatment-refractory central centrifugal cicatricial alopecia (CCCA), in a retrospective case series.

METHODOLOGY:

• Researchers conducted a case series involving 12 Black women in their 30s, 40s, and 50s, with biopsy-confirmed, treatment-refractory CCCA, a chronic inflammatory hair disorder characterized by permanent hair loss, from the Johns Hopkins University alopecia clinic.
• Participants received CCCA treatment for at least 6 months and had stagnant or worsening symptoms before oral extended-release metformin (500 mg daily) was added to treatment. (Treatments included topical clobetasol, compounded minoxidil, and platelet-rich plasma injections.)
• Scalp biopsies were collected from four patients before and after metformin treatment to evaluate gene expression changes.
• Changes in clinical symptoms were assessed, including pruritus, inflammation, pain, scalp resistance, and hair regrowth, following initiation of metformin treatment.
• Metformin led to significant clinical improvement in eight patients, which included reductions in scalp pain, scalp resistance, pruritus, and inflammation. However, two patients experienced worsening symptoms.
• Six patients showed clinical evidence of hair regrowth after at least 6 months of metformin treatment with one experiencing hair loss again 3 months after discontinuing treatment.
• Transcriptomic analysis revealed 34 upregulated genes, which included upregulated of 23 hair keratin-associated proteins, and pathways related to keratinization, epidermis development, and the hair cycle. In addition, eight genes were downregulated, with pathways that included those associated with extracellular matrix organization, collagen fibril organization, and collagen metabolism.
• Gene set variation analysis showed reduced expression of T helper 17 cell and epithelial-mesenchymal transition pathways and elevated adenosine monophosphate kinase signaling and keratin-associated proteins after treatment with metformin.

IN PRACTICE:

"Metformin's ability to concomitantly target fibrosis and inflammation provides a plausible mechanism for its therapeutic effects in CCCA and other fibrosing alopecia disorders," the authors concluded. But, they added, "larger prospective, placebo-controlled randomized clinical trials are needed to rigorously evaluate metformin's efficacy and optimal dosing for treatment of cicatricial alopecias."

The study was led by Aaron Bao, Department of Dermatology, Johns Hopkins University School of Medicine, Baltimore, and was published online on September 4 in JAMA Dermatology .

LIMITATIONS:

A small sample size, retrospective design, lack of a placebo control group, and the single-center setting limited the generalizability of the study findings. Additionally, the absence of a validated activity or severity scale for CCCA and the single posttreatment sampling limit the assessment and comparison of clinical symptoms and transcriptomic changes.

DISCLOSURES:

The study was supported by the American Academy of Dermatology. One author reported several ties with pharmaceutical companies, a pending patent, and authorship for the UpToDate section on CCCA.

This article was created using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.

Send comments and news tips to [email protected] .

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Use of Automated Urine Microscopy Analysis in Clinical Diagnosis of Urinary Tract Infection: Defining an Optimal Diagnostic Score in an Academic Medical Center Population

Dimard e. foudraine.

a Department of Infectious Diseases, Leiden University Medical Center, Leiden, The Netherlands

Martijn P. Bauer

Anne russcher.

b Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands

Elske Kusters

c Department of Clinical Chemistry, Leiden University Medical Center, Leiden, The Netherlands

Christa M. Cobbaert

Martha t. van der beek, janneke e. stalenhoef.

A retrospective case record study was conducted that established a scoring tool based on clinical and iQ200 parameters, able to predict or rule out the clinical diagnosis of UTI in the majority of adult patients in an academic hospital. Automated standardized quantitative urine analysis, such as iQ200 analysis, is on the rise because of its high accuracy and efficiency compared to those of traditional urine analysis. Previous research on automated urinalysis focused mainly on predicting culture results but not on the clinical diagnosis of urinary tract infection (UTI). A retrospective analysis was conducted of consecutive urine samples sent in for culture because of suspected UTI. UTI was defined by expert opinion, based on reported symptoms, conventional urine sediment analysis, and urine cultures. Parameters of iQ200 analysis and clinical symptoms and signs were compared between cases and controls. Optimal cutoff values were determined for iQ200 parameters, and multivariate logistic regression analysis was used to identify the set of variables that best predicts the clinical diagnosis of UTI for development of a scoring tool. A total of 382 patients were included. Optimal cutoff values of iQ200 analysis were 74 white blood cells (WBC)/μl, 6,250 “all small particles” (ASP)/μl, and a bacterial score of 2 on an ordinal scale of 0 to 5. The scoring tool attributed 1 point for frequent micturition or increased urge, 2 points for dysuria, 1 point for a bacterial score of ≥2, 2 points for WBC/μl of ≥50, and an additional point for WBC/μl of ≥150. This score had a sensitivity of 86% and a specificity of 92% when using a threshold of <4 points. The combination of iQ200 analysis and a simple survey could predict or rule out UTIs in a majority of patients in an academic medical center.

INTRODUCTION

Urinary tract infection (UTI) is among the most frequently occurring infections and is the second most frequent clinical indication for empirical antibiotic treatment in primary and secondary care ( 1 , 2 ). The gold standard for diagnosis is detection of a pathogen in the urine in the presence of clinical symptoms. Because the result of a traditional urine culture is not readily available, presumptive diagnosis of UTI is based on diagnostic tests such as dipstick or urinary sediment analysis ( 3 ).

In some populations, the diagnosis of UTI is not as straightforward and should be distinguished from asymptomatic bacteriuria or inflammatory conditions, such as interstitial cystitis ( 2 ). This is especially the case in a tertiary hospital, where relatively many patients have complex urinary tract problems or kidney transplants or are treated with immunosuppressive medication.

In the past few years, automated, standardized, quantitative urine analysis has been introduced in clinical practice and has shown high efficiency and accuracy compared to traditional sediment analysis ( 4 ). One of these systems is the IRIS Diagnostics iQ200 Elite (iQ200), currently marketed by Beckman Coulter Inc., which analyzes urinary samples using flow imaging technology and auto particle recognition. The iQ200 classifies and quantifies particles, including bacteria, yeasts, white blood cells (WBC), and squamous epithelial cells, and correlates well with traditional urinary sediment examination with manual cell counts ( 5 ). Our group and other research groups have so far focused mainly on the use of automated urinalysis as a screening tool to predict negative urine cultures and thus to reduce the culture workload in the laboratory ( 6 , – 9 ).

For this purpose, a positive culture was used as the “laboratory” gold standard of UTI without taking clinical symptoms into account, therefore predicting the presence of bacteriuria, but not of symptomatic UTI ( 10 , 11 ). This distinction is important because it is currently thought that there is no role for treatment of patients with asymptomatic bacteriuria other than for pregnant women and patients undergoing urologic procedures ( 12 ).

The test results of automated urine analysis are, however, subject to different clinical interpretations. This is partly because of unfamiliarity with quantitative results, instead of the semiquantitative test results that clinicians used before, and the lack of optimal cutoff values for the clinical diagnosis of UTI.

The goal of the current study was to establish cutoff values for parameters of iQ200 analysis, to be used in diagnosing symptomatic UTI in a tertiary hospital population. Subsequently, we aimed to develop a scoring model to predict the clinical diagnosis of urinary tract infection, based on both symptoms and these cutoff values.

MATERIALS AND METHODS

Setting and patient population..

A retrospective study was performed at Leiden University Medical Center, which is an academic tertiary hospital in Leiden, the Netherlands. It has approximately 400 hospital beds and focuses on transplant medicine (solid organ transplants and stem cell transplants), resulting in a large proportion of immunocompromised patients. Samples from inpatients and outpatients of the hospital constitute the majority of samples sent to the clinical chemistry and microbiological laboratories ( 6 ). The study was approved by the Ethics Committee.

Urine samples.

Upon receipt at the Department of Medical Microbiology, all urine samples submitted for bacterial culture during a 12-week period from 25 February to 17 May 2013 were divided into two portions under sterile conditions if they had sufficient volume (at least 2 ml for culture and Gram stain and 3 ml for the iQ200 screening). One portion was analyzed by the iQ200 system in the clinical chemistry laboratory within 2 h after receipt from the microbiological laboratory. Results were not reported to the clinician because the iQ200 was still under validation. The other portion was analyzed by the microbiological laboratory. For more detailed information regarding procedures we refer to Russcher et al. ( 6 ).

For the purpose of this study, urine samples from children, pregnant women, and patients with an indwelling urinary catheter for more than 24 h, a nephrostomy, or a urostomy were excluded because the diagnosis of UTI is defined differently within these groups. Urine samples from patients without clinical data or clinical suspicion for UTI (e.g., preoperative routine urine controls) were excluded as well. Only the first sample of each patient was included.

Microbiological analysis.

Urine samples were analyzed using local standard microbiological methods for Gram stain and culture ( 6 ). The bacterial load was assessed and scored from <100 CFU/ml (no growth) to ≥10 5 CFU/ml. The relevance of the urine sample was assessed according to our standard protocol for urine cultures, taking a quality score (the Q score) based on white blood cell (WBC) and squamous epithelial cell (SEC) counts in the Gram stain into account, as previously described ( 6 ). In urine samples with a high Q score (≥1, corresponding with a high WBC and low SEC count), all growth was identified to the species level. Colonies in samples with a Q score of zero were only identified to the species level if a monoculture with a bacterial load of ≥10 5 CFU/ml was present. Samples with Q scores of ≤0 were generally classified as mixed flora.

A positive culture was defined as having ≥10 3 CFU/ml of not more than two different usual uropathogens or as having ≥10 5 CFU/ml of a single unusual urinary pathogen. Common and uncommon pathogens and nonpathogens that were cultured are listed in Table 1 .

Pathogens isolated from urine cultures of 381 patients with and without UTIs

Automated urine microscopic analysis.

All samples derived from the Department of Medical Microbiology were tested by the iQ200 Elite analyzer (Iris Diagnostics, Chatsworth, CA), which is an automated urine microscopy analyzer that uses flow cytometry and digital photography. Automatic particle recognition software categorizes urine particles into 12 groups, including leukocytes, erythrocytes, bacteria, and “all small particles” (ASP). The ASP group consists of unclassified particles of <3 μm, such as cocci, which are not recognized well by the iQ200, some other bacteria, crystals, and other formed elements ( 4 , 6 , 10 ). All elements other than bacteria were quantitatively reported (per microliter), and bacteria were reported semiquantitatively (on a scale from 0 to 5). After automatic classification, a trained technician reviewed all images. Misplaced or unclassified images were placed in the correct categories, and bacterial counts were adjusted in cases when cocci were present.

Conventional urine analysis.

In a vast majority of patients from whom a urine sample was sent in for culture, a different sample was sent to the clinical chemistry for dipstick analysis. If the dipstick tested positive for leukocytes or erythrocytes, sediment analysis was performed using local standard protocol. The positively tested urine was centrifuged for 5 min at 2,000 rpm. Subsequently, urine was poured off until 0.5 ml supernatant remained. This was shaken, and one drop was analyzed on a slide under a microscope. Observed elements were quantified as the number per high power field and reported qualitatively in the medical record.

Clinical assessment.

Clinical data and characteristics of included patients were obtained from the electronic medical records. Patients were retrospectively classified as either cases having a UTI or controls who did not have a UTI by two infectious diseases specialists using medical chart review. The expert reviewers used data on symptoms, signs, antibiotic (pre)treatment, and outcome, as documented in the electronic patient files. They used data on culture results and conventional urine analysis, which consisted of dipstick and sediment analysis. They also considered whether another diagnosis was more likely or could be the cause of complaints and/or fever. They were blinded to the iQ200 results, which were not reported in the medical records. If they differed in opinion, they reached consensus by means of discussion.

Statistical analysis.

Baseline characteristics were compared with χ 2 tests for dichotomous variables and an unpaired t test for age. Symptoms and signs were compared with χ 2 tests. Parameters from the iQ200 analysis were compared using unpaired t tests, and receiver operating characteristic (ROC) curves were plotted. Cutoff values were determined based on the optimal tradeoff between sensitivity and specificity. These cutoffs correspond with coordinates on the ROC curves that are closest to 0.1 (the upper left corner) ( 13 ). Distances for all coordinates on the ROC curves to 0.1 were calculated by the formula d = (1 − sensitivity) 2 + (1 − specificity) 2 .

A logistic regression model was established, using symptoms and parameters from the iQ200. In the case of information on a specific sign or symptom not being documented in the electronic patient file, that patient was excluded for this specific analysis. Backward selection excluded parameters based on likelihood ratios without significantly changing the fit of the model. The final model retained all variables significantly associated with the presence of UTI at a P < 0.05 level. A numerical scoring tool was developed using the model by simplifying β-coefficients of all independent predictor variables. We calculated the area under the receiver operating characteristic curve (AUC) with 95% confidence interval (CI) to assess the scoring tool's discriminatory power to predict or rule out UTI. ROC curves were also plotted for the separate iQ200 and clinical variables derived from the model.

Cutoff values were considered based on sensitivity, specificity, and positive and negative predictive values (PPV and NPV, respectively). All analyses were performed using SPSS 21.0 (SPSS Inc., Chicago, IL).

Population characteristics.

During the study period, 1,442 urine samples from 1,084 unique patients were submitted. The following samples were excluded: 641 samples from patients not suspected of having a UTI, 152 samples from patients with an indwelling urinary catheter for >24 h, 76 samples from pregnant patients, 62 samples of children below the age of 18, 33 samples from a nephrostomy or urostomy drain, 91 subsequent samples of patients already included, and 13 samples lacking data in the corresponding electronic patient files. After exclusion, 381 unique patients and urine samples remained. A total of 29 of 381 urine samples submitted were obtained by one-time catheterization and the rest by midstream clean catch. The prevalence of UTI among the 381 patients according to the expert review was 59. The expert reviewers initially differed in opinion in 30 of 381 patients (7.8%), but reached consensus for all patients by means of discussion. Table 2 shows demographic and clinical characteristics of the two patient groups (with and without urinary tract infections). Patients who had a UTI were significantly older ( P = 0.041) than those who did not. None of the other characteristics differed significantly between both groups.

Baseline characteristics of 381 patients with and without UTIs

Culture results.

Table 1 shows culture results of cases and controls. Escherichia coli was the most prevalent pathogen ( n = 57). A total of 192 cultures displayed mixed flora, and 80 cultures showed no growth. Patients who were assessed as cases with a UTI while their culture showed no growth were all treated with antibiotics in the 48 h prior to culture ( n = 3).

Signs and symptoms.

The prevalences of signs and symptoms among both patient groups are listed in Table 3 . Dysuria, recognition of symptoms from a previous UTI, frequent micturition, and cloudy urine were most strongly associated with UTI. Subgroup analysis was conducted for aggravated lower urinary tract symptoms (LUTS) in male patients, increased cognitive impairment in patients older than 59 years of age, and vaginal irritation or changed discharge in women. None of these three symptoms was significantly associated with UTI in their respective subgroups (data not shown). The concentration of C-reactive protein in serum and leukocyte count in blood did not differ significantly between patients with and without UTIs ( P values were 0.95 and 0.69, respectively). The same applied to the proportion of patients with positive blood cultures when comparing both groups ( P = 0.31).

Signs and symptoms of 381 patients with and without UTIs

iQ200 parameters.

The difference in distribution of white blood cells in urine between cases and controls was obvious. Most cases had a count of >20 leukocytes/μl (97%), while most controls had a count of ≤20 leukocytes/μl (69%) ( P < 0.01). A somewhat similar result was found for the concentration of bacteria. The iQ200 analysis reported a bacterial score of 2 or more for 61% of the cases and <2 for 85% of the controls ( P < 0.01). ROC curves were plotted for iQ200 parameters and are shown in Fig. 1 . The count of white blood cells per microliter (WBC/μl) had the largest area under curve (AUC, 0.91; CI, 0.87–0.94) and the highest discriminative value compared to those of the other parameters. Optimal cutoff values were calculated for WBC/μl, bacterial score, and ASP/μl and are shown in Table 4 .

Receiver operating characteristic curves of different iQ200 parameters predicting UTI. On the y axis, sensitivity; on the x axis, 1 − specificity. AUC, area under the receiver operating characteristic curve; CI, 95% confidence interval. ···, WBC/μl (AUC, 0.91; CI, 0.87 to 0.94); – –, bacteria (AUC, 0.79; CI, 0.73 to 0.85); - - -, ASP/μl (AUC, 0.77; CI, 0.71 to 0.82); - - - ·- - - ·, red blood cells (RBC)/μl (AUC, 0.72; CI, 0.66 to 0.79); —, reference line.

Cutoff values of iQ200 parameters and corresponding sensitivity and specificity

Because of the high discriminative value of WBC/μl, this parameter was subsequently divided into 3 categories, using the cutoffs of 50 and 150. The first cutoff, 50, was selected by prioritizing sensitivity over specificity while maintaining a good tradeoff between both of them (sensitivity, 91%; specificity, 79%). The second cutoff, 74, was the optimal calculated cutoff (sensitivity, 86%; specificity, 82%), and the third cutoff, 150, was selected by approximately reducing the number of false negatives by half (sensitivity, 69%; specificity, 89%). Cutoffs were rounded to increase clinical applicability.

Establishment of a scoring tool.

Logistic regression analysis was performed. Symptoms significantly associated with UTI were entered into the model, together with the categorized concentration of WBC/μl (using the two selected cutoff values from Table 4 ) and the iQ200 parameter “bacteria.” We did not use ASP/μl in our model because we aimed to establish a clinically applicable model, and this parameter is nonspecific for measurement of bacteria. A scoring tool was developed to confirm or rule out the diagnosis of UTI ( Table 5 ). Points were attributed based on β coefficients, with 1 point being given to the parameter with the smallest coefficient ( 14 , 15 ). The maximum possible score was 7.

Variables retained after logistic regression analysis of factors independently associated with UTI and attribution of points based on β coefficients

ROC curves of the scoring tool (AUC, 0.95; CI, 0.93 to 0.98) and of its separate components, iQ200 analysis (AUC, 0.90; CI, 0.86 to 0.93) and clinical (AUC, 0.80; CI, 0.73 to 0.88) variables, are shown in Fig. 2 . As expected, the scoring tool had a higher sensitivity and specificity in predicting UTI compared to the separate iQ200 and clinical parameters as derived from the model, as well as the single iQ200 parameters ( Fig. 1 ). Different cutoff scores and corresponding characteristics of the scoring tool are displayed in Table 6 . When using a single threshold, a score of <4 has the optimal tradeoff between sensitivity (86%) and specificity (92%), which are both remarkably high, given the complexity of the study population. Using this cutoff, 7 patients would incorrectly be scored as negative (14% of cases), while 23 patients would incorrectly be scored as positive (8% of controls). If two cutoffs were to be used, three categories are formed, as follows: UTI likely, UTI possible, or UTI unlikely ( Table 7 ). By using one threshold of below 3 and one of 5 or more, both false negatives and false positives are reduced by more than half compared to those when using a single threshold of 4. However, 19% of all patients would be classified as possibly having a UTI.

Receiver operating characteristic curves of the scoring tool and its separate components (iQ200 and clinical variables) predicting UTI. On the y axis, sensitivity; on the x axis, 1 −specificity. AUC area under the receiver operating characteristic curve; CI, 95% confidence interval. ···, combined score (AUC, 0.95; CI, 0.93 to 0.98); – –, WBC/μl and bacteria (AUC, 0.90; CI, 0.86 to 0.93); - - - ·- - - ·, dysuria and frequent micturion/increased urge (AUC, 0.80; CI, 0.73 to 0.88); —, reference line.

Possible thresholds for the scoring tool and corresponding characteristics

Number of patients with and without UTI in each score group and predictive values using two cutoffs

Our study defined cutoff values for parameters measured by an automated urine analysis system, the IRIS iQ200, for prediction of the clinical diagnosis of urinary tract infection in a heterogeneous, academic population of adult patients. In contrast to previous research on automated urine analysis by the iQ200 ( 6 , 7 , 10 ), we did not solely use a positive urine culture as the “gold” standard, but focused on clinical symptoms and course of disease in combination with culture results. This clinical assessment allowed exclusion of false-positive urine cultures of patients without urinary symptoms and with a diagnosis other than UTI, limiting unnecessary treatment of UTI. Prudent use of antibiotics has become increasingly relevant because of the problem of antibiotic resistance, which currently has become one of the most serious and growing threats to public health ( 16 ).

We found that urinary white blood cell count had the highest discriminative value for UTI (AUC, 0.91) compared to the other individual parameters, bacterial score and ASP/μl. The calculated optimal cutoff for WBC/μl was 74, with a sensitivity of 86% and specificity of 82%. For development of the scoring tool, we choose to use a lower cutoff of 50 WBC/μl, with a higher sensitivity of 91% and acceptable specificity of 79% (AUC, 0.85), to reduce the amount of false-negative results.

The finding that only 3% of the cases had a concentration of ≤20 WBC/μl in urine corresponds with findings of previous research using conventional urine analysis ( 17 , 18 ). The role of the count of ASP/μl in UTI diagnosis by iQ200 remains to be determined. One study reported that ASP/μl has a better test performance than bacterial score at certain cutoffs ( 8 ), but our findings confirm the observation of Parta et al., who did not find ASP count to contribute in ruling out UTIs ( 8 , 10 ).

The optimal scoring tool for diagnosis of UTI obtained by multivariable analysis included the iQ200 parameters “WBC/μl” and “bacteria” and the clinical symptoms “dysuria” and “frequent micturition/increased urge.” The test characteristics of the scoring tool depend on the chosen threshold(s). Through the selection of different cutoff criteria, the score can be adapted to different clinical situations, depending on the relative benefits of maximizing sensitivity or specificity.

While a high sensitivity is important to minimize the number of false negatives, specificity might be of equal importance to minimize the number of false positives and limit inappropriate antibiotic use.

Obviously, the selection of the best cutoff depends on the setting, the clinical condition and individual characteristics of the patient, and the risk of delaying antibiotic treatment. In the case of a febrile patient with suspected invasive UTI, a threshold of <2 seems appropriate to rule out UTI and search for an alternative diagnosis, whereas in the case of suspected cystitis, the threshold of 4 could be used to withhold antibiotics. Therefore, the use of three categories (UTI likely [≥5], UTI possible [3 to 4] or UTI unlikely [ls<3]) is probably most useful for application in patient care, leaving room for interpretation and risk analysis by the clinician.

Previous research on automated urine analysis showed that its findings correspond well with those of conventional urine sedimentation ( 5 ). Most research on analysis by the IRIS iQ200 aimed to predict a positive urine culture in order to reduce laboratory workload and associated costs ( 6 , 8 , 10 ). One of these articles also took clinical data into account, which led to a reduction of cases considered to be false positive using only urine culture as the gold standard ( 10 ). Since the purpose of this study by Parta was to evaluate the iQ200 as a screening tool to decrease unnecessary urine culture, a low cutoff for WBC (≥6/μl) was chosen to achieve high sensitivity, resulting in a poor specificity of 67 to 70%.

Luciano developed a risk score, combining both dipstick and iQ200 sediment reading results with age, which improved UTI diagnosis in a pediatric population ( 19 ).

Similar studies were performed on different commercial systems using flow cytometry, e.g., the Sysmex UF-1000i (Sysmex, Japan) to define optimal cutoff points for WBC/μl or bacterial score for ruling out bacterial UTI, but these data cannot be extrapolated directly to the iQ200 because both systems work differently. The UF-1000i is laser based and uses fluorescent dye, which the iQ200 does not ( 7 , 9 , 20 , 21 ).

The strengths of our study are the particular academic population and its reflection of a real-world situation, which includes a very heterogeneous group of both inpatients and outpatients, of whom some had renal transplants, had a fever, were already treated with antibiotics, had contaminated urine samples, or were difficult to classify as either having a UTI or not.

The present study has its limitations. First, data from electronic patient files was obtained retrospectively and might not always have been complete. Second, the entire available data set was used for the prediction score, which as a result could not be validated in a different patient set. Validation is therefore required before the score can be implemented in clinical use. Third, the diagnosis of UTI lacks a gold standard. However, we feel that assessment by two independent blinded experts who take clinical data and conventional sediment analysis, as well as culture results, into account is the best reference test currently available. Finally, the study population was too small to distinguish between uncomplicated cystitis and invasive UTIs and to determine if cutoff values of iQ200 parameters would be different for certain subgroups, such as patients with neutropenia or renal transplants ( 2 , 22 ).

Further research should prospectively validate the scoring tool for diagnosis of UTI on a new set of data and in different subgroups of patients and demonstrate potential benefits, such as reduction in the unnecessary use of antibiotics.

In conclusion, although the diagnosis of UTI can be challenging in an adult academic patient population, the combination of a simple survey and the results of the iQ200 could rule out infection in the majority of patients and therefore improve antibiotic stewardship in suspected UTI cases.

ACKNOWLEDGMENTS

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

We report that we have no conflicts of interest.

• Open access
• Published: 03 September 2024

Association of phthalates exposure and sex steroid hormones with late-onset preeclampsia: a case-control study

• Xiaomin Zhao 1 , 2   na1 ,
• Anjian Xu 1   na1 ,
• Xinyue Lu 1 ,
• Baoyi Chen 1 ,
• Ying Hua 1 &
• Yanyan Ma 1  

BMC Pregnancy and Childbirth volume  24 , Article number:  577 ( 2024 ) Cite this article

Metrics details

This study aimed to investigate the relationship between phthalates exposure and estrogen and progesterone levels, as well as their role in late-onset preeclampsia.

A total of 60 pregnant women who met the inclusion and exclusion criteria were recruited. Based on the diagnosis of preeclampsia, participants were divided into two groups: normotensive pregnant women ( n  = 30) and pregnant women with late-onset preeclampsia ( n  = 30). The major metabolites of phthalates (MMP, MEP, MiBP, MBP, MEHP, MEOHP, MEHHP) and sex steroid hormones (estrogen and progesterone) were quantified in urine samples of the participants.

No significant differences were observed in the levels of MMP, MEP, MiBP, MBP, MEHP, MEOHP, and MEHHP between women with preeclampsia and normotensive pregnant women ( P >  0.05). The urinary estrogen showed a negative correlation with systolic blood pressure (rs= -0.46, P  < 0.001) and diastolic blood pressure (rs= -0.47, P  < 0.001). Additionally, the urinary estrogen and progesterone levels were lower in women with preeclampsia compared to those in normotensive pregnant women ( P  < 0.05). After adjusting for confounding factors, we observed a significant association between reduced urinary estrogen levels and an increased risk of preeclampsia (aOR = 0.09, 95%CI = 0.02–0.46). Notably, in our decision tree model, urinary estrogen emerged as the most crucial variable for identifying pregnant women at a high risk of developing preeclampsia. A positive correlation was observed between urinary progesterone and MEHP (rs = 0.36, P  < 0.05) in normotensive pregnant women. A negative correlation was observed between urinary estrogen and MEP in pregnant women with preeclampsia (rs= -0.42, P  < 0.05).

Conclusions

Phthalates exposure was similar in normotensive pregnant women and those with late-onset preeclampsia within the same region. Pregnant women with preeclampsia had lower levels of estrogen and progesterone in their urine, while maternal urinary estrogen was negatively correlated with the risk of preeclampsia and phthalate metabolites (MEP).

Trial registration

Registration ID in Clinical Trials: NCT04369313; registration date: 30/04/2020.

Peer Review reports

Introduction

Preeclampsia (PE) is a pregnancy-specific disorder, characterized by the new-onset hypertension and either proteinuria or multiple maternal system dysfunctions occurring after 20 weeks of gestation [ 1 ]. It represents a major contributor to maternal morbidity and mortality worldwide [ 2 ]. Therefore, it is imperative to elucidate the etiology and pathogenesis of PE, which still remains unclear at present. Previous studies have demonstrated that placental dysfunction and angiogenic response disruption may be involved in the pathogenesis of PE [ 3 ]. Environmental factors including exposure to endocrine-disrupting chemicals, like phthalates, may also play a role in the development PE [ 4 ].

Phthalates, a class of plasticizers, are widely used in our daily products [ 5 ]. Exposure to phthalates can take place through inhalation, ingestion, skin absorption and contaminated surfaces contact [ 5 ]. It has been reported that phthalates can enter amniotic fluid and fetal circulation though the fetal-placental barrier [ 6 ]. Despite their usefulness, however, phthalates can interfere with and disrupt the endocrine system, potentially leading to the elevated blood pressure and an increased risk of cardiovascular diseases [ 7 ]. Recently, researchers have found that the presence of phthalate metabolites in the urine of pregnant women is significantly associated with an increase in blood pressure, and those who are exposed to phthalates have a higher risk of developing PE [ 8 ].

Estrogen and progesterone, mainly synthesized by the placenta after 10 weeks of gestation, are essential for maintaining pregnancy. Estrogen can regulate angiogenic processes by altering the concentration of vascular endothelial growth factor (VEGF) and increasing placental blood perfusion [ 2 ]. Progesterone can reduce vascular resistance by reducing the sensitivity to angiotensin, exerting a protective effect on vascularization [ 9 ]. A recent research has found that the serum concentrations of estradiol and progesterone are significantly lower in pregnant women with PE compared to those in healthy pregnant women [ 10 ]. MEE-NA PARK et al. revealed that the expression of estrogen receptor-1 (ESR1) was reduced in the placenta of pregnant women with PE [ 11 ]. Thus, the changes in estrogen and progesterone levels may be closely associated with the development of PE.

It has been revealed that maternal phthalate metabolites disrupt the balance of these steroid hormones [ 12 ]. For example, the increased levels of phthalates in maternal cord blood were associated with a significant reduction in estriol and estradiol levels [ 13 ]. Phthalate metabolites in the human body could interfere with estrogen and progesterone activities, like mono-phthalate monobutyl (MBP) and mono-phthalate monomethyl (MMP) [ 5 ]. Therefore, we hypothesize that alterations in estrogen and progesterone levels resulting from exposure to phthalates may underlie the development of PE.

The objectives of our study are to investigate the association between exposure to phthalates and alterations in estrogen and progesterone levels, as well as to explore the role of this relationship in late-onset PE.

Materials and methods

Study design and population.

This was an observational study conducted in the Second Affiliated Hospital of Wenzhou Medical University from March 1, 2021 to March 1, 2022 (Registration ID in Clinical Trials: NCT04369313; registration date: 30/04/2020). The study was supported by the Research Ethics Committee of our hospital (NO. LCKY2019-288). Pregnant women with PE were recruited as the study group. Normotensive pregnant women during the same period were included as the control group, matched with those in the study group based on baseline characteristics, including maternal age, body mass index (BMI) at delivery, gravidity, parity, and gestational age. The ratio of women in the study group to the control group was 1:1, and the majority of women with PE enrolled in our study were at or near full term without severe complications. All the participants provided written consent.

Eligibility criteria for participants included singleton pregnancies, 18–40 years old, and intention to give birth at our hospital. The exclusion criteria were as follows: (1) women with chronic hypertension before pregnancy, gestational hypertension, eclampsia, or chronic hypertension with superimposed PE during pregnancy; (2) women took medicine before or during pregnancy, such as hormones or antidiabetic drugs; (3) women with pregnancy complications including placenta previa, diabetes or gestational diabetes, cardiac or renal disease, intrahepatic cholestasis of pregnancy and others; (4) women with early-onset PE (< 34 weeks); (5) women who declined to participate in this study.

Data collection

Participants completed questionnaires and provided urine samples before delivery. A face-to-face interview based on structured questions was performed to collect information including maternal age, gravidity, parity, occupation, regular exercise, supplementation of folate, and medication history. We obtained data on gestational age and blood pressure at delivery, BMI at delivery, neonatal birth weight and sex of infants from computerized medical records.

BMI (in kg/m 2 ) was calculated as weight (in kg) divided by the square of height (in m). PE was defined as a systolic blood pressure ≥ 140 mmHg or diastolic blood pressure ≥ 90 mmHg, along with the presence of proteinuria after 20 weeks of gestation or multiple maternal system dysfunctions (including thrombocytopenia, defined as platelet count < 100,000/mm 3 ; renal insufficiency, defined as serum creatinine concentration > 1.1 mg/dl or doubling of serum creatinine concentration without other renal diseases; impaired liver function, defined as elevated liver transaminases to 2×normal or severe persistent right upper quadrant/epigastric pain unresponsive to medication; pulmonary edema, diagnosed by physical examination/chest x-ray; neurological signs, defined as new-onset headache unresponsive to medication/not accounted for by alternative diagnoses/visual symptoms; fetal growth restriction, defined as estimated fetal weight<10th percentile) in the absence of proteinuria [ 1 ].

Urine collection and analysis

Urine samples were collected from pregnant women in the morning on an empty stomach, centrifuged for 10 min at a force of approximately 3000r, and then the supernatant liquid was stored at -80 degrees Celsius.

Estrogen and progesterone levels were detected using an available enzyme-linked immunosorbent assay (ELISA) kits (ExCell Biotech, China) according to the manufacturer’s protocols. Briefly, 50uL of standards and thawed urine samples were added to the ELISA plate, followed by conjugate reagent. The plate was then incubated at 37 degrees Celsius for one hour. After incubation, each well was washed with scrubbing solution for 30 s, repeated five times. Subsequently, chromogenic agent and stop solution were sequentially added to each well, and the absorbance at 450 nm was measured within 15 min.

The other urine samples were sent to a professional company (Metabo-Profile Biotechnology (Shanghai) Co., LTD ) to measure the metabolites of phthalates by high performance liquid chromatography (HPLC). Firstly, 40µL of β-glucuronidase solution was added to 1.0 mL of thawed urine sample and shaken well, then the mixture was placed in a water bath at 37 ℃ for enzymatic hydrolysis hermetically for 120 min, after then 1.0 mL phosphate buffer was added to mix and purify. Phthalate was dissolved in acetonitrile and diluted into a series of concentration samples (0.5 to 100 µg/mL) to obtain the standard curve. The purified urine samples were detected by liquid chromatography (Shimadzu LC-20AD) combined with triple tandem quadrupole mass spectrometry; finally, the concentrations of seven major phthalates metabolitesthe concentrations (in ng/mL) of seven major phthalates metabolites were obtained: matrix metalloproteinase (MMP), monoethyl phthalate (MEP), monoisobutyl phthalate (MiBP), monobutyl phthalate (MBP), mono-2-ethylhexyl phthalate (MEHP), mono-2-ethyl-5-oxy-hexyl phthalate (MEOHP) and mono-2-ethyl-5-hydroxy-hexyl phthalate (MEEHP).

Sample size estimation

Firstly, we recruited a total of 10 normotensive pregnant women and 10 women with PE based on inclusion and exclusion criteria in an initial experiment. They were matched to ensure a balanced baseline in terms of maternal age, gestational age, parity, gravidity, and BMI at delivery. In this preliminary experiment, measurements of estrogen and progesterone concentrations, as well as phthalate metabolite concentrations, were obtained. Subsequently, the mean and standard deviation of these measurements were calculated for both groups − 10 normotensive pregnant women and 10 women with PE. The PASS software (Power Analysis and Sample Size) was used to estimate the sample size required for this study. After setting the “Alpha error” at 0.05 and “power (1-beta)” at 0.9, we determined that a sample size of n  = 28 was needed for each group based on the results obtained from the preliminary experiment: pregnant women with PE group ( n  = 28) and normotensive pregnant women group ( n  = 28).

Statistical analysis

We conducted a descriptive analysis using SPSS 26.0 software to examine the overall situation and characteristics of the data. Additionally, we utilized SPSS 26.0 software to perform 1:1 Case Control Matching through Propensity Score Matching. After assessing normality assumptions by Kolmogorov-Smirnov test, continuous variables with normal distributions were reported as mean ± standard deviation, while those with non-normal distributions were reported as median (interquartile range). Student t-test was employed for analyzing normally distributed continuous variables, whereas Mann-Whitney U test was used for non-normally distributed continuous variables. Correlation analysis was performed to explore the relationship between sex steroid hormones and the metabolites of phthalates, as well as between sex steroid hormones and blood pressure in pregnant women. Logistic regression analysis was applied to investigate the impact of sex steroid hormones on PE after adjusting for confounding factors. Odds ratio (OR) and 95% confidence interval (CI) were utilized to present logistic regression results. In the decision tree model, the dependent variable was grade data representing the presence of PE in pregnant women (0 = normotensive pregnant women, 1 = pregnant women with PE). The independent variables included confounding factors that may affect PE: maternal age, gestational weeks, gravidity, parity, BMI at delivery, phthalate metabolites, and steroid hormones. A p -value < 0.05 was considered statistically significant.

In this study, a total of 305 pregnant women with PE and 3147 women with normal pregnancies were enrolled in our institution from March 1, 2021 to March 1, 2022. After applying exclusion criteria and Propensity Score Matching, a total of 60 pregnant women were included in the final analysis (as detailed in Fig.  1 ). They were divided into two groups: the control group consisted of normotensive pregnant women ( n  = 30), and the study group comprised pregnant women with late-onset PE ( n  = 30), among whom 28 presented mild PE, while 2 presented severe PE (characterized by blood pressure ≥ 160/110 mmHg without any severity features).

Flowchart of the study (ELISA: enzyme-linked immunosorbent assay; HPLC: high performance liquid chromatography; MMP: matrix metalloproteinase; MEP: monoethyl phthalate; MiBP: monoisobutyl phthalate; MBP: monobutyl phthalate; MEHP: mono-2-ethylhexyl phthalate; MEOHP: mono-2-ethyl-5-oxy-hexyl phthalate; MEEHP: mono-2-ethyl-5-hydroxy-hexyl phthalate)

The demographic and clinical characteristics of the enrolled women were summarized in Table  1 . There were no significant differences in maternal age, gestational age, gravidity, parity, maternal weight and BMI at delivery, and newborn infant sex ratio between the two groups ( P >  0.05). However, the neonatal weights of normotensive pregnant women were higher than those of women with PE ( P  < 0.05). The systolic and diastolic blood pressure of women with PE was significantly higher than that of normotensive pregnant women ( P  < 0.001). And the median urinary protein of women with PE was 0.95 g/24 h.

As shown in Table  2 , there were no significant differences in the concentrations of phthalate metabolites (MMP, MEP, MiBP, MBP, MEHP, MEOHP and MEEHP) in urine between pregnant women with PE and normotensive women ( P >  0.05).

The negative correlations between urinary estrogen and systolic blood pressure, diastolic blood pressure, as well as the negative correlation between progesterone and diastolic blood pressure were presented in Table  3 ( P  < 0.05). In addition, Table  4 showed that the levels of maternal estrogen and progesterone in urine were significantly lower in pregnant women with PE compared to normotensive women ( P  < 0.05). Moreover, after adjusting for age, gestational weeks, gravidity, parity, BMI at delivery, estrogen and progesterone, we observed a significant association between reduced urinary estrogen levels and an increased risk of PE (aOR = 0.09, 95%CI = 0.02–0.46) (Table  5 ).

The decision tree depicted in Fig.  2 illustrated the prediction of PE. It consisted of 5 nodes, including 3 terminal nodes, and had a depth of 2. Four rules were extracted from the decision tree: - Rule 1: If estrogen levels are > 4.16ng/mL, THEN classify as pregnant women with PE (24.3%). - Rule 2: If estrogen levels are ≤ 4.16ng/mL, THEN classify as pregnant women with PE (91.3%). - Rule 3: If estrogen levels are ≤ 4.16ng/mL and progesterone levels are ≤ 6.02ng/mL, THEN classify as pregnant women with PE (100%). - Rule 4: If estrogen levels are ≤ 4.16ng/mL and progesterone levels are > 6.02 ng/mL, THEN classify as pregnant women with PE (66.7%). In the decision tree model, the urinary estrogen was the most critical variable for identifying pregnant women who were at a risk of developing PE.

The decision tree model for identifying pregnant women at risk of preeclampsia

The correlation between sex steroid hormones and phthalate metabolites in the urine of pregnant women was presented in the Tables  6 and 7 . In the urine of normotensive pregnant women, there was a positive correlation between progesterone and MEHP (rs = 0.36, P  = 0.047), but there were no correlations between progesterone and MMP, MEP, MiBP, MBP, MEOHP or MEHHP ( P >  0.05). Besides, there were no correlations between estrogen and phthalate metabolites in the urine of normotensive pregnant women ( P >  0.05) (Table  6 ). In the urine of pregnant women with PE, there was a negative correlation between estrogen and MEP (rs= -0.42, P  = 0.02), but there were no correlations between estrogen and MMP, MiBP, MBP, MEHP, MEOHP, MEHHP ( P >  0.05); and there was no correlation between progesterone and phthalate metabolites ( P >  0.05) (Table  7 ).

Our study indicated that phthalate exposure was similar in normotensive pregnant women and those with late-onset PE within the same region, and both urinary estrogen and progesterone levels were lower in women with late-onset PE compared to those in normotensive pregnant women. Moreover, our study showed a negative correlation between urinary estrogen and blood pressure of pregnant women, as well as a significant association between reduced urinary estrogen levels and an increased risk of PE. Additionally, estrogen was negatively correlated with MEP in women with late-onset PE.

It has been reported that the toxicological effects are caused by the metabolites of phthalates, a class of endocrine disruptors, rather than the original parent compounds [ 4 ]. Previous studies have drawn inconsistent conclusions regarding the association between maternal phthalate exposure and PE. Cantonwide et al. conducted a study that analyzed prenatal urine samples for nine phthalate metabolites and found that these metabolites, particularly MEHP, were significantly associated with the risk of PE [ 7 ]. The similar results have been shown in some cohort studies [ 8 , 14 ]. However, Philips et al. found no association between prenatal exposure to phthalates and changes in maternal blood pressure, gestational hypertensive disorders, or placental hemodynamics [ 15 ]. This result was consistent with our findings, which showed no difference in phthalate metabolite concentrations between pregnant women with normal blood pressure and those with PE. These conflicting results may be due to the differences in geographic locations, demographic profiles, and the degree of PE severity.

The findings of a study on Chinese phthalate exposure revealed regional disparities in the levels of phthalate exposure, with higher exposures observed in northeastern and southern provinces compared to those in central provinces [ 16 ]. Our study population was all recruited from the Wenzhou area, so the levels of phthalate exposure in normotensive pregnant women was comparable to those in women with PE. In addition, the research design ensured a well-balanced distribution of clinical characteristics between the study group and the control group, thereby facilitating further investigation. Consequently, the pregnant women with PE in our study were primarily comprised of near or full term singleton pregnancies with mild PE. In contrast, the population of the previous study consisted of pregnant women who were at a high risk of PE, including those with severe or early onset PE. Therefore, further investigations are warranted to elucidate the association between geographical factors, the severity of PE and maternal exposure to phthalates.

Phthalates can act as endocrine disruptors, potentially inducing alterations in hormone levels within the human body [ 5 ]. Interestingly, although there was no statistically significant difference in the levels of phthalate metabolites in the urine between the two groups, pregnant women with PE had significantly lower levels of estrogen and progesterone in the urine compared to those in normotensive women. Relevant studies have also indicated an association between decreased levels of estrogen and progesterone and the occurrence of PE [ 10 ]. The rat model demonstrated that estradiol treatment effectively reduced blood pressure and alleviated symptoms of preeclampsia, such as urinary protein excretion [ 17 ].

Furthermore, administering progesterone supplements to women at higher risk for pregnancy during the gestational period from 6 to 20 weeks has been shown to effectively reduce the incidence of PE [ 18 ]. Placental insufficiency and ischemia may constitute the primary etiology of PE [ 3 ]. It has been reported that progesterone possesses the ability to reduce the resistance of the uterine spiral artery and lower vascular resistance in uteroplacental blood flow [ 19 ]. This mechanism is likely attributed to the potent immunomodulatory functions exerted by progesterone, which promote the expansion or differentiation of regulatory T cells at the maternal-fetal interface and induce pro-angiogenic neutrophils that facilitate homeostatic placental T cell function [ 20 , 21 , 22 ]. Therefore, the improvement of PE symptoms by progesterone may be associated with its enhancement of uteroplacental blood flow and immunomodulatory function. Based on these findings, the preliminary conclusion would seem to be that changes in estrogen and progesterone levels are closely involved in the development of PE.

Limited research has been conducted on the mechanism underlying the decreased levels of estrogen and progesterone in pregnant women with PE. Recent studies indicated that this mechanism may be related to endocrine disrupting chemicals, placental ischemia-reperfusion injury and increased oxidative stress response [ 3 , 7 , 23 ]. For hypothesizing, the phenomenon we observed may be attributed to maternal exposure to endocrine disruptors in the surrounding environment. Our study investigated the correlation between prenatal exposure to phthalates and estrogen and progesterone levels in the urine. The correlation analysis conducted in our study revealed a significant negative association between estrogen levels and phthalate metabolites (MEP), with this relationship being particularly pronounced among pregnant women diagnosed with PE. Estrogen has also been found to be inversely associated with levels of phthalates in maternal cord blood [ 12 ]. Furthermore, the levels of serum estrogen and progesterone were significantly lower in mice exposed to 0.05 mg/kg/day DEHP (a dosage relevant to human exposure) compared to those in the control group [ 24 ]. Therefore, the decreased levels of estrogen in pregnant women with PE may be closely associated with prenatal exposure to phthalates.

As is known, the enzymes 3-beta-hydroxysteroid dehydrogenase 1 (HSD3B1) and cytochrome P450 family 19 subfamily A member 1 (CYP191a1) play pivotal roles in the synthesis and secretion of estrogen and progesterone [ 25 ]. An in vitro experiment indicated that phthalates and their metabolites decreased levels of progesterone and estradiol by inhibiting the activity of HSD3B1 and CYP191a1 [ 26 ]. Placental trophoblast cells can express peroxisome proliferator-activated receptor gamma (PPARG), a ligand-dependent transcription factor that is involved in human hormone secretion [ 27 ]. Besides, the results of an in vitro experiment have confirmed that MEHP exhibited anti-estrogenic effects through direct receptor activity [ 28 ]. Thus, these findings suggested that exposure to phthalates may lead to a decrease in estrogen and progesterone levels by inhibiting the synthesis and secretion of estrogen and progesterone, as well as antagonizing estrogen activity.

Furthermore, researchers are paying more attention to placental epigenetics, including DNA methylation, histone modification, and small RNA-mediated control. It has been reported that placental epigenetics are sensitive to environmental conditions such as endocrine disruptors (e.g., phthalates) [ 29 ]. The team led by Machtinger et al. identified and quantified a total of 87 long noncoding RNAs (lncRNAs) derived from the placental tissue. Their findings revealed strong correlations between phthalates and the majority of these lncRNAs [ 30 ]. A study conducted by Grindler et al. aimed to determine the epigenome-wide DNA methylation marks and gene expression associated with phthalates exposure in placenta. The results showed that most of the genes with significantly altered methylation were negatively correlated with high levels of phthalate exposure [ 31 ].

Thus, the sensitivity to phthalate exposure varies among pregnant women due to placental epigenetics. Individual epigenetic differences may make women with PE more susceptible to environmental phthalate exposure compared to normotensive pregnant women living in the same area. Therefore, we postulated that those pregnant women who were more sensitive to phthalate exposure may show lower levels of estrogen and progesterone, potentially leading to the development of PE, despite comparable exposure to phthalates in total pregnant women.

Strengths and limitations

This study had several notable strengths, with the most significant being its pioneering investigation into the correlation between phthalates and sex steroid hormones in PE. Secondly, urine samples were utilized for estrogen/progesterone analysis instead of blood samples to ensure consistency with the measurement of phthalate metabolites in urine, thereby mitigating potential errors arising from sample variation. One limitation is that we did not measure the levels of estrogen and progesterone in maternal serum, as well as their corresponding receptors in the placenta. This choice was made considering the ease of obtaining urine samples compared to the invasive nature of acquiring blood samples. Another limitation of this study is that its results were based on a single spot antepartum urine sample from pregnant women, rather than continuous dynamic testing. Those limitations may be addressed in a future extended study.

Phthalate exposure levels were comparable between normotensive pregnant women and those with PE within the same geographical region. Urinary estrogen and progesterone levels were lower in women with PE compared to those in normotensive pregnant women, and the negative correlations were observed between urinary estrogen levels and the risk of PE, as well as both systolic and diastolic blood pressure, in addition to phthalate metabolites (MEP) among pregnant women with PE.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

• Preeclampsia

Vascular endothelial growth factor

Estrogen receptor-1

Matrix metalloproteinase

Monoethyl phthalate

Monoisobutyl phthalate

Monobutyl phthalate

Mono-2-ethylhexyl phthalate

Mono-2-ethyl-5-oxy-hexyl phthalate

Mono-2-ethyl-5-hydroxy-hexyl phthalate

Enzyme-linked immunosorbent assay

High performance liquid chromatography

3β-hydroxysteroid dehydrogenase − 1

P450 aromatase

Peroxisome-proliferator activated receptor gamma

Long noncoding RNAs

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Acknowledgements

The authors would like to thank the pregnant women of this study to participate in investigation and survey.

This work was supported by Wenzhou Key Laboratory of Precision General Practice and Health Management and the Obstetrics and gynecology of combine traditional Chinese and Western medicine of Zhejiang Province (2017-XK-A42).

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Xiaomin Zhao and Anjian Xu contributed equally to this work.

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Department of Obstetrics and Gynecology, the Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, 325027, China

Xiaomin Zhao, Anjian Xu, Xinyue Lu, Baoyi Chen, Ying Hua & Yanyan Ma

Department of Obstetrics and Gynecology, Shaoxing Maternity and Child Health Care Hospital, Shaoxing, China

Xiaomin Zhao

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ZXM and XAJ wrote the main manuscript; LXY and CBY prepared Tables 1, 2, 3, 4, 5, 6 and 7; HY and MYY prepared Fig. 1 and polished the manuscript. All authors reviewed the manuscript.

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Correspondence to Ying Hua or Yanyan Ma .

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This study was approved by the Research Ethics Committee of the Second Affiliated Hospital of Wenzhou Medical University (NO. LCKY2019-288). Informed consent was obtained from all the participants.

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Zhao, X., Xu, A., Lu, X. et al. Association of phthalates exposure and sex steroid hormones with late-onset preeclampsia: a case-control study. BMC Pregnancy Childbirth 24 , 577 (2024). https://doi.org/10.1186/s12884-024-06793-5

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Received : 15 June 2024

Accepted : 28 August 2024

Published : 03 September 2024

DOI : https://doi.org/10.1186/s12884-024-06793-5

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