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Assessing the Gravity of the Situation :

October 2, 2019

In a recently released issue of Pediatrics (10.1542/peds.2019-0467), Dr. Nader Shaikh and colleagues ask an elegantly simple yet clinically important question: does urine specific gravity influence the accuracy of the urinalysis for detection of urinary tract infection (UTI)?

In a recently released issue of Pediatrics(10.1542/peds.2019-0467), Dr. Nader Shaikh and colleagues ask an elegantly simple yet clinically important question: does urine specific gravity influence the accuracy of the urinalysis for detection of urinary tract infection (UTI)? Haven’t you always kind of wondered whether dilute urine is misleading you into missing a UTI? Or alternately, have you wondered whether a very concentrated urine that accurately reflects dehydration also masks a UTI? I certainly have, and I love it that Dr. Shaikh and colleagues have given this question a deep dive. These authors performed a retrospective analysis of data from children ages 24 months or younger presenting to their Emergency Room (2007-2013) who underwent urine catheterization and had both an automated urinalysis and a urine culture; those with genitourinary anomalies were excluded. A total of 10,078 children were included, of whom 3,966 (39.4%) had concentrated urine, defined for this study as specific gravity (SG) ³1.015, and 617 (6.1%) had a UTI, defined as >100,000 CFU/mL on a clean catch specimen or >50,000 CFU/mL on a catheterized specimen. This definition of UTI aligns with the American Academy of Pediatrics Clinical Practice Guideline.1

The authors used a really interesting approach, since the question is not just “what does the data show”, but how the data might influence clinical decision making. First, for each component of the urinalysis alone, and then for all components together, the authors calculated the number of children who would have been “missed” (not treated for a UTI) or “over treated” (treated but no UTI) with and without considering SG in the process of clinical decision making. Then, using coefficients from these models, the authors calculated the probability of UTI for each child in their dataset. Jumping ahead a bit here since the authors’ explanation is very clear, ultimately they examined the impact of urinalysis components, with and without consideration of SG, on a hypothetical cohort of 1000 febrile children < 24 months of whom 7% would be expected to have UTI. Based on prior literature demonstrating that physicians would treat if the probability of UTI is between 5-25%, the authors used a “5% treatment threshold” in their analysis.

What did they find? Certain urinalysis components do vary with SG, and this is presented in an easy to read table (Table 2) which clinicians will want to check out. Interestingly, UTI was significantly more likely in those with dilute than concentrated urine (7.0% versus 4.8%) which is the opposite of what I would have expected. Make your own best guess about whether including or excluding SG in the predictive model ultimately led to a difference in treatment decision making, and then read this interesting article to learn the study result. Although many questions remain, this article is a definitely a “must read” for clinicians on the front line who have to make UTI treatment decisions every day.

References

1. Subcommittee on Urinary Tract Infection, Steering Committee on Quality Improvement and Management. Urinary Tract Infection: Clinical Practice Guideline for the Diagnosis and Management of the Initial UTI in Febrile Infants and Children 2 to 24 Months. Pediatrics 2011; 128: 595-610. DOI: 10.1542/peds.2011-1330

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