Use of Polyacrylamide Hydrogel for Vesicoureteral Reflux Treatment, a Review
Bibliographic record
Abstract
Purpose of the review: Vesicoureteral reflux (VUR) is a common pathology encountered in pediatric urology. If left untreated, this condition can lead to infectious complications, hypertension and loss of renal function by scars. There is a trend for minimally invasive procedures to minimise treatment-related complications. Endoscopic subureteral injection of bulking agent in the treatment of VUR is an example of minimally invasive options. Several bulking agents have been studied and the perfect agent has not yet been discovered. Polyacrylamide hydrogel is a relatively new agent used to treat VUR and its use will be reviewed. Recent findings: Three modern studies from a Canadian group have evaluated the use of polyacrylamide hydrogel for endoscopic injection to treat VUR. The first study reported a cure rate of 81.2% without major complication. In the second study, injection of polyacrylamide hydrogel was compared to dextranomer hyaluronic acid and no significant difference was observed, with overall success rate of 73.1% and 77.5% respectively. The third trial evaluated the long-term efficacy and safety of polyacrylamide hydrogel with a 36-month follow-up. Overall success at 3 months was 70.7% and no patient had de novo hydronephrosis or calcification of the agent at 36 months. Conclusion: Polyacrylamide hydrogel seems to be a safe and effective alternative bulking agent in the treatment of VUR. The contribution from other centers to validate those data would be valuable.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".