Urinary tract infections in infants and children: Diagnosis and management
Bibliographic record
Abstract
Recent studies have resulted in major changes in the management of urinary tract infections (UTIs) in children. The present statement focuses on the diagnosis and management of infants and children >2 months of age with an acute UTI and no known underlying urinary tract pathology or risk factors for a neurogenic bladder. UTI should be ruled out in preverbal children with unexplained fever and in older children with symptoms suggestive of UTI (dysuria, urinary frequency, hematuria, abdominal pain, back pain or new daytime incontinence). A midstream urine sample should be collected for urinalysis and culture in toilet-trained children; others should have urine collected by catheter or by suprapubic aspirate. UTI is unlikely if the urinalysis is completely normal. A bagged urine sample may be used for urinalysis but should not be used for urine culture. Antibiotic treatment for seven to 10 days is recommended for febrile UTI. Oral antibiotics may be offered as initial treatment when the child is not seriously ill and is likely to receive and tolerate every dose. Children <2 years of age should be investigated after their first febrile UTI with a renal/bladder ultrasound to identify any significant renal abnormalities. A voiding cystourethrogram is not required for children with a first UTI unless the renal/bladder ultrasound reveals findings suggestive of vesicoureteral reflux, selected renal anomalies or obstructive uropathy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".