Impact of early screening for reflux in siblings on the detection of renal damage
Bibliographic record
Abstract
OBJECTIVE: To assess the impact of screening siblings after detecting significant vesico-ureteric reflux (VUR) and renal scarring, as such screening might identify patients with VUR before urinary tract infections develop, but might also detect clinically insignificant VUR. PATIENTS AND METHODS: We used a previously reported screening protocol to assess the clinical characteristics of patients, including the incidence of renal scarring, and their siblings, and compared the results. In all, 123 children were screened and 44 (36%) had VUR on voiding cystography. The median (range) age at screening was 9 (1-90) months. RESULTS: The grades of VUR detected were < III in 61% and > or = III in 39%; VUR was bilateral in 48%. In all, 37 siblings with VUR were assessed by ultrasonography; 70% were normal, including 12 (32%) children with VUR of grade > or = III. When used, renal scintigraphy was normal in 74% of siblings, vs 18% of index patients. However, when screened after 2 years old, siblings had twice the risk of already having renal damage on renal scintigraphy (P = 0.04). CONCLUSION: Early screening (< or = 2 years) appears to be more protective for avoiding renal damage than screening older patients. Thus we propose early screening in asymptomatic siblings to detect VUR before it becomes clinically significant.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".