Review: antibiotic treatment for 7–14 days reduces treatment failure in children with urinary tract infection
Bibliographic record
Abstract
Keren R, Chan E. A meta-analysis of randomized, controlled trials comparing short- and long-course antibiotic therapy for urinary tract infections in children. Pediatrics2002 ; 109 : e70 . [OpenUrl][1][Abstract/FREE Full Text][2] QUESTION: In children with urinary tract infection (UTI), is a long course (LC) of antibiotic treatment more effective than a short course (SC) for preventing treatment failure or reinfection? Studies were identified by searching Medline and the Cochrane Library (all up to April 2001), reviewing bibliographies of relevant articles, and contacting experts in the field for any other published or unpublished studies. Studies published in English were selected if they were randomised controlled trials (RCTs) comparing SC with LC outpatient antibiotic treatment for acute UTI in children 0–18 years of age. Studies that were restricted to children with recurrent UTI or that included children with asymptomatic bacteriuria were excluded from the review. 2 reviewers independently extracted data on setting, sample size, … [1]: {openurl}?query=rft.jtitle%253DPediatrics%26rft.stitle%253DPediatrics%26rft.aulast%253DKeren%26rft.auinit1%253DR.%26rft.volume%253D109%26rft.issue%253D5%26rft.spage%253De70%26rft.epage%253De70%26rft.atitle%253DA%2BMeta-analysis%2Bof%2BRandomized%252C%2BControlled%2BTrials%2BComparing%2BShort-%2Band%2BLong-Course%2BAntibiotic%2BTherapy%2Bfor%2BUrinary%2BTract%2BInfections%2Bin%2BChildren%26rft_id%253Dinfo%253Adoi%252F10.1542%252Fpeds.109.5.e70%26rft_id%253Dinfo%253Apmid%252F11986476%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/ijlink?linkType=ABST&journalCode=pediatrics&resid=109/5/e70&atom=%2Febnurs%2F6%2F1%2F15.atom
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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 | 0.005 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.007 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".