Diagnosis and management of community-acquired urinary tract infection in infants and children
Bibliographic record
Abstract
Urinary tract infection (UTI) is the most common bacterial disease in childhood worldwide and may have significant adverse consequences, particularly for young children. In this guideline, we provide the most up-to-date information for the diagnosis and management of community-acquired UTI in infants and children aged over 90 days up to 14 years. The current recommendations given by the American Academy of Pediatrics Practice guidelines, Canadian Pediatric Society guideline, and other international guidelines are considered as well as regional variations in susceptibility patterns and resources. This guideline covers the diagnosis, therapeutic options, and prophylaxis for the management of community-acquired UTI in children guided by our local antimicrobial resistance pattern of the most frequent urinary pathogens. Neonates, infants younger than three months, immunocompromised patients, children recurrent UTIs, or renal abnormalities should be managed individually because these patients may require more extensive investigation and more aggressive therapy and follow up, so it is considered out of the scope of these guidelines. Establishment of children-specific guidelines for the diagnosis and management of community-acquired UTI can reduce morbidity and mortality. We present a clinical statement from the Saudi Pediatric Infectious Diseases Society (SPIDS), which concerns the diagnosis and management of community-acquired UTI in children.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".