Screening asymptomatic siblings for vesicoureteral reflux: sound science or religious rhetoric?
Bibliographic record
Abstract
INTRODUCTION: Many urologists endorse the concept of screening asymptomatic siblings of children known to have vesicoureteral reflux. Others oppose screening until there is better evidence to justify the cost and potential morbidity of adopting a widespread screening program. METHODS: A literature review of the following topics was carried out: 1) screening programs in general; 2) reflux in general; 3) familial reflux; and 4) screening for familial reflux. RESULTS: The evidence supporting our traditional surgical and medical management strategies for reflux is weak. The evidence supporting screening is lacking. Public Health organizations do not address the issue of screening for this condition. Despite this, there is a significant body of peer reviewed literature and compelling expert opinion, in support of screening. Possible reasons for this are explored. CONCLUSIONS: A randomized controlled trial to definitively assess the utility of screening would be larger and more challenging to perform than any ever done in the history of this condition. Until such time that high quality evidence exists, screening of asymptomatic siblings will continue to be based upon our individual clinical experience and teachings, the morbidity of the index case, and socioeconomic factors. We must continue to re-evaluate our management strategies for this condition in light of new information as it accrues.
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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 | 0.032 | 0.093 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.014 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.006 |
| 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".