To Clean or Not to Clean: Effect on Contamination Rates in Midstream Urine Collections in Toilet-Trained Children
Bibliographic record
Abstract
OBJECTIVE: Urinary tract infection is one of the most common bacterial infections among children. Difficulty in specimen collection and interpretation of inadequately collected specimens may contribute to misdiagnosis of urinary tract infection. Our objective was to assess the effect of perineal/genital cleaning on bacterial contamination rates of midstream urine collections in toilet-trained children. METHODS: We conducted a randomized trial in toilet-trained children who presented to a tertiary care pediatric emergency department between November 1, 2004, and October 1, 2005. All toilet-trained children who were between the ages of 2 and 18 years and had a midstream urine sample requested were eligible. Those whose parents consented were cluster-randomized by week to either cleaning or not cleaning the perineum with soap. The risk for a contaminated urine culture (defined as growth of < 10(8) colony-forming units per liter [< 10(5) colony-forming units per milliliter] of a single organism or a mix of > or = 2 organisms) and the risk for a positive urinalysis (defined as a positive leukocyte esterase and/or nitrites on dipstick or > or = 5 white blood cells per high-powered field on a standard microscopic examination) were analyzed by intention to treat. RESULTS: A total of 350 children were enrolled. The rate of contamination in the cleaning group was 14 (7.8%) of 179 vs 41 (23.9%) of 171 in the noncleaning group. Children who were randomly assigned to cleaning were less likely to have a positive urinalysis (37 of 179 [20.6%]) than those in the noncleaning group (63 of 171 [36.8%]). CONCLUSIONS: Urine contamination rates are higher in midstream urine that is collected from toilet-trained children when obtained without perineal/genital cleaning. Cleaning may reduce the risk for returning for repeat cultures and for receiving unnecessary antibiotic treatment and investigations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".