Urine Testing in Children with Respiratory or Other Viral Illness Symptoms: a National Analysis of Ambulatory Encounters
Bibliographic record
Abstract
Abstract Corresponding Author: Rachel L. Wattier, 550 16th St, 4th Floor, San Francisco, CA 94143-0434, email: rachel.wattier@ucsf.edu, phone: 415-514-0509 Alternate Corresponding Author: Adam L. Hersh, 295 Chipeta Way, Salt Lake City, UT 84108, email: adam.hersh@hsc.utah.edu, phone: 801-587-7418 Financial Support: SVK receives research support from NIH and AHRQ, ALH receives research support from CDC, PCORI, and AHRQ Conflict of Interest: None of the authors have conflicts of interest. Background The incidence of pediatric urinary tract infection (UTI) diagnoses decreased unexpectedly during the coronavirus 2019 pandemic. There was no corresponding increase in severity of illness, thus the decrease was not likely to have been driven by avoidance of or delays in seeking care. One hypothesized explanation is that UTI may be misdiagnosed in patients with viral illnesses, many of which had decreased transmission during the pandemic. US and Canadian guidelines for UTI recommend testing patients with high pretest probability of UTI and avoiding testing if symptoms suggest another etiology. Our objective was to evaluate UTI testing patterns in children with respiratory or other common viral symptoms using national data. Methods We conducted a cross-sectional study using the National Ambulatory Medical Care Survey (NAMCS) and National Hospital Ambulatory Medical Care Survey (NHAMCS) from 2014-2019. These are annual, cross-sectional surveys administered by the National Center for Health Statistics at a nationally representative multistage probability sample of visits to offices and emergency departments (EDs). We included encounters in patients 2 months-17 years old for initial evaluation of a new problem. We excluded encounters leading to hospitalization or transfer, and encounters related to trauma, pregnancy, or altered mental status. Up to 5 reasons for visit (RFVs) are systematically captured in NAMCS and NHAMCS surveys based on the chief complaint and history of present illness. We defined testing as potentially avoidable if there was at least one symptom likely attributable to a viral illness (e.g., respiratory symptoms, diarrhea, rash) without a concomitant RFV localizing to the genitourinary tract. We estimated the frequency of urine testing in encounters with these symptoms. We defined testing as performance of a urinalysis and/or urine culture. We applied sampled visit weights to calculate national estimates. Results Of 71,328,000 (SD +/- 3,389,000) pediatric encounters per year that met inclusion criteria (N = 17,840 unweighted visit records), 43,728,000 (SD +/- 2,485,000), 61% (95% CI 59-63%) had RFV codes for possible viral illness symptoms, without genitourinary symptoms. Urine testing was performed in 5.3% (95% CI 3.7-7.6%) of these encounters and testing in patients with this symptom profile accounted for 38% (95% CI 30-47%) of overall urine testing. Testing in the setting of possible viral illness symptoms was more frequent in ED encounters than in clinic encounters (8.3% vs. 4.4%, p=0.03) and in encounters by children ≥2 years old than by children <2 years old (6.4% vs. 2.0%, p<0.001). Conclusions Potentially unnecessary urine testing occurs in at least 5% of ambulatory encounters by children with common viral symptoms not attributable to UTI. Despite their lower epidemiologic risk for UTI, older children were more likely to be tested. Our findings support the hypothesis around drivers of decreased UTI diagnoses during the pandemic. They can also guide efforts to improve diagnostic and antibiotic stewardship.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".