Evaluating the benefits of antimicrobial prophylaxis to prevent urinary tract infections in children: a systematic review.
Bibliographic record
Abstract
BACKGROUND: The recurrence rate for urinary tract infections in children is estimated at between 30% and 40%. The use of low doses of antibiotics as prophylaxis for recurrent urinary tract infections is common clinical practice. However, prolonged antimicrobial therapy has the potential to contribute to problems of bacterial resistance and antimicrobial side effects. The aim of this review was to systematically examine the available evidence for the effectiveness of this intervention. METHODS: We conducted a literature search of 3 electronic databases for the period 1966 to 1999. We also searched bibliographies from conference proceedings and contacted content experts to ensure completeness of our database. Each trial was evaluated on the basis of the following inclusion criteria: target population (children), intervention (antibiotic v. no antibiotic), outcome (number of urinary tract infections) and study design (randomized controlled trial). Quality was assessed for the studies that met these criteria. RESULTS: Most of the studies identified were case series and cohort studies. Only 6 randomized trials fulfilled the inclusion criteria. All were of low quality (median 2, range 0 to 2 [maximum quality score 5]). Three trials dealt with children who had anatomically normal urinary tracts, and three included children with neurogenic bladder. The rate of infections for patients with normal urinary tracts ranged from 0 to 4.0 per 10 patient-years for the treatment groups and from 4.0 to 16.7 for the control groups. The recurrence rates for patients with neurogenic bladders in 2 trials were 2.9 and 17.1 per 10 patient-years for the treatment groups and 1.5 and 33.0 for the control groups. INTERPRETATION: The available evidence for using antimicrobial prophylaxis to prevent urinary tract infection in children with normal urinary tracts or neurogenic bladder is of low quality. This suggests that the magnitude of any benefit should at best be questioned. The surprising lack of data for children with reflux is of concern. Well-designed trials are needed to optimize the use of antimicrobials in children with recurrent urinary tract infection.
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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 | 0.010 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".