Third-generation cephalosporin-resistant urinary tract infections in children presenting to the paediatric emergency department
Bibliographic record
Abstract
BACKGROUND: The incidence of antibiotic-resistant urinary tract infections (UTIs) in children is increasing. The purpose of this study was to describe the incidence, clinical characteristics, and risk factors for third-generation cephalosporin-resistant UTIs presenting to the paediatric emergency department (ED). METHODS: This was a retrospective cohort study conducted at British Columbia Children's Hospital. Children aged 0 to 18 years old presenting to the ED between July 1, 2013 and June 30, 2014 and were found to have UTI due to Enterobacteriaceae and Pseudomonas species were included. Patient demographics, clinical features, laboratory findings, and outcomes were compared using standard statistical analyses. Risk factors for resistant UTIs were analyzed using multiple logistic regression analysis. RESULTS: There were 294 eligible patients. The median age was 27.4 months. A third-generation cephalosporin-resistant organism was identified in 36 patients (12%). Patients with resistant UTI had lower rates of appropriate empiric antibiotic therapy (25% versus 95.3%, P<0.05), higher rates of hospitalization (38.9% versus 21.3%, P<0.05), higher rates of undergoing a voiding cystourethrogram (19.4% versus 5.0%, P<0.05), and higher rates of UTI recurrence within 30 days (13.9% versus 4.7%, P<0.05). In multivariate analysis, recent hospitalization (odds ratio [OR] 4.3, confidence interval [CI] 1.2 to 16) and antibiotic therapy (OR 3.5, CI 1.5 to 8.5) within the previous 30 days were risk factors for resistant UTI. CONCLUSIONS: Third-generation cephalosporin-resistant organisms account for a significant proportion of community-acquired paediatric UTIs. Recent hospitalization and antibiotic use are associated with increased risk of resistant UTI.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".