Comparison of different substances for subureteric injection in the management of vesicoureteric reflux in children.
Bibliographic record
Abstract
INTRODUCTION: Endoscopic techniques are becoming increasingly accepted for treatment of vesicoureteric reflux as alternatives to open surgical reimplantation. However, there is some debate about the ideal injectable material. Since we have accumulated experience with several substances, an opportunity existed to compare them. MATERIALS AND METHODS: From 1991 to 2003, 101 children with vesicoureteric reflux were treated by endoscopic subureteric injection either once (74) or twice (27) by either of two pediatric urologists. There were a total of 165 ureteral injections, 83 with polytetrafluoroethylene (Teflon), 73 with polydimethylsiloxane (Macroplastique), and 9 with collagen. Each child was evaluated pre-operatively and 3 months post-operatively with a nuclear cystogram and renal ultrasonography. RESULTS: The polytetrafluoroethylene and polydimethylsiloxane groups were not significantly different with respect to sex, age, indication for surgery, severity of reflux or prior surgeries. The collagen group overall did very poorly with only 3 of 9 refluxing ureters cured. The other two substances had much more success with 61% of ureters in the polytetrafluoroethylene group cured on first injection and 75% with polydimethylsiloxane, plus another 19% and 11% cured on second attempt, respectively (total 80% and 86%). CONCLUSIONS: Subureteric injections of polytetrafluoroethylene and polydimethylsiloxane are very effective at curing vesicoureteric reflux in children with little morbidity. When comparing individual cases, ureters, and all grades of reflux, polytetrafluoroethylene and polydimethylsiloxane have similar success rates. Collagen injections were less successful, and patients with neurogenic bladders had poor results.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".