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Record W2588464909 · doi:10.5489/cuaj.4387

Continuous antibiotic prophylaxis in the setting of prenatal hydronephrosis and vesicoureteral reflux

2017· review· en· W2588464909 on OpenAlexaffvenue
Nathan C. Wong, Martin A. Koyle, Luis H. Braga

Bibliographic record

VenueCanadian Urological Association Journal · 2017
Typereview
Languageen
FieldMedicine
TopicPediatric Urology and Nephrology Studies
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of TorontoMcMaster University
Fundersnot available
KeywordsMedicineVesicoureteral refluxAntibiotic prophylaxisObservational studyRandomized controlled trialAntibioticsPediatricsUrinary systemHydronephrosisIntensive care medicineInternal medicineRefluxDisease

Abstract

fetched live from OpenAlex

Continuous antibiotic prophylaxis (CAP) has traditionally been offered for children with recurrent urinary tract infections (UTIs) or those at risk, including children diagnosed with prenatal hydronephrosis (HN) and vesicoureteral reflux (VUR). However, indications for antibiotic prophylaxis are controversial, data on who should benefit from this therapy is conflicting and, thus, guidelines are unable to provide conclusive recommendations. In the setting of prenatal HN, although randomized trials are currently underway, most evidence is derived from low- to moderate-quality observational studies. Although there is no benefit in those with low-grade HN, a systematic review of the available studies showed that high-grade HN patients on prophylaxis experienced fewer infections with an estimated number needed to treat of 7. On the other hand, there are eight randomized trials that have investigated the use of antibiotic prophylaxis in the setting of VUR. Although four of the studies have demonstrated some value of prophylaxis and the other four have not, meta-analysis has shown an overall benefit of antibiotic prophylaxis in preventing infections. The observed differences are likely due to different inclusion criteria and study heterogeneity. Although generalizing results of meta-analyses to all children is tempting, an individualized approach, by determining which patients best behave like those of the included studies, is recommended.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.720
Threshold uncertainty score0.831

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.035
GPT teacher head0.304
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations13
Published2017
Admission routes2
Has abstractyes

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