Prospective Study of Polydimethylsiloxane vs Dextranomer/Hyaluronic Acid Injection for Treatment of Vesicoureteral Reflux
Bibliographic record
Abstract
PURPOSE: Endoscopic injection of a bulking agent is becoming a first-line treatment for low grade vesicoureteral reflux. We prospectively compared the efficacy of 2 such products commercially available in Canada. MATERIALS AND METHODS: A total of 275 patients with documented grade I to V vesicoureteral reflux were prospectively enrolled in a comparative study between April 2005 and February 2011 to be randomly treated endoscopically with either polydimethylsiloxane (Macroplastique®) or dextranomer/hyaluronic acid copolymer (Deflux®). Of the ureters 202 were treated with polydimethylsiloxane and 197 with dextranomer/hyaluronic acid copolymer. Patients were followed with voiding cystourethrography at 3 months and renal ultrasonography at 3 months and at 1 year. Median followup was 4.3 years. The primary outcome was surgical success (resolution vs nonresolution), and secondary outcomes included occurrence of adverse events. RESULTS: Vesicoureteral reflux was fully corrected in 182 of 202 ureters (90%) treated with polydimethylsiloxane, compared to 159 of 197 (81%) treated with dextranomer/hyaluronic acid copolymer (p <0.05). Obstruction was found in 5 ureters. Univariate and multivariate analyses did not allow identification of any characteristics that could explain the significant difference in the success rates except for the type of product used. CONCLUSIONS: We present the largest known prospective evaluation comparing 2 bulking agents for the treatment of vesicoureteral reflux. Endoscopic injection of polydimethylsiloxane resulted in a better success rate than dextranomer/hyaluronic acid copolymer. The rate of resolution obtained with the latter is lower than those previously published due to the inclusion of high grade reflux.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".