Automatic urine cultures from catheter-obtained samples—time to implement a practice change to improve value
Bibliographic record
Abstract
Objectives: Urine cultures are often automatically obtained after urinary catheterization in young children, even in the absence of pyuria, to test for urinary tract infections (UTIs). Although this practice conflicts with some newer guidelines, it is frequently followed in busy emergency departments (EDs) to minimize the need for a repeat invasive procedure. To assess the implications of this longstanding practice, we aimed to describe the frequency and characteristics of children with normal urinalysis (UA) and positive urine culture obtained via catheterization, and to describe their clinical course. Methods: A single center, retrospective cohort study was performed for otherwise healthy children aged 6 to 24 months, presenting to a Pediatric ED between January and June 2019 who underwent UTI testing via a urine catheterization. The point-of-care (POC) UA and urine culture results along with any follow-up phone call documentation were reviewed and analyzed using descriptive statistics. Results: Of the 818 urine cultures obtained via catheterization during the 6-month study period, 131 (16%) cultures were reported as positive. Of these positive cultures, 14 (10.7%) of the patients meeting inclusion criteria had a normal POC UA. In follow-up phone calls after the ED visit, the majority of these 14 patients were asymptomatic without any antibiotic treatment and 3 (2.3%) patients were still febrile and classified as a potentially missed UTI. Conclusions: The routine practice of sending urine cultures from all catheterized urine samples in children 6 to 24 months, regardless of POC UA results, rarely detect missed UTIs. In alignment with more recent practice guidelines, this practice should be reconsidered in low-risk children seen in EDs to improve overall care quality and resource utilization.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".