Children's UTIs in the new millennium. Diagnosis, investigation, and treatment of childhood urinary tract infections in the year 2001.
Bibliographic record
Abstract
OBJECTIVE: To provide an effective approach for family physicians treating children presenting with urinary tract infections (UTIs). QUALITY OF EVIDENCE: The information presented, and articles quoted, are drawn from both review of the literature and recent consensus guidelines. Data and recommendations come from prospective multicentre trials; retrospective reviews; expert consensus statements; and some smaller trials, commentaries, and editorials. MAIN MESSAGE: Urinary tract infections are often seen in family practice. Diagnosis requires suspicion and a realization that children, especially those younger than 2 years, often have very few, nonspecific signs of infection. Obtaining a proper urine sample is vital, because true infections require radiographic studies. Antibiotic prophylaxis is promoted because of the link between vesicoureteral reflux, recurrent UTIs, and renal scarring and hypertension. We generally provide prophylaxis until children are 3 or 4 years, when risk of damage from reflux is lessened and timely urine samples are easier to obtain for prompt therapy. Surgical opinion is sought only when medical management has failed. Failure is defined as either recurrent infections and pyelonephritis or poor renal growth. CONCLUSION: To diagnose UTIs in children, physicians must suspect them, obtain proper urine samples, order appropriate investigations to rule out underlying anatomic abnormalities, and treat with appropriate antibiotics considering both organism sensitivities and length of therapy.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".