COLLAGEN INJECTION FOR TREATMENT OF URINARY INCONTINENCE IN CHILDREN
Bibliographic record
Abstract
PURPOSE: We assess the success rate of periurethral collagen injection in children with neurogenic bladder dysfunction secondary to myelomeningocele. MATERIALS AND METHODS: From 1992 to 1998, 15 male and 5 female patients with spina bifida (age 13.3 +/- 3.8 years) underwent endoscopic collagen injection for the treatment of urinary incontinence secondary to sphincter deficiency. Mean followup was 4.2 years. Pretreatment urodynamic study showed a stable compliant bladder with an average leak point pressure of 52 cm. H2O (range 23 to 100). Concurrent medical management included anticholinergics in 15 cases, agonists in 3, and clean intermittent catheterization in 16. Five patients had undergone previous ileocystoplasty. RESULTS: Collagen injections were given with the patient under general anesthesia. The number of injections was 1 in 5 cases, 2 in 11, 3 in 3, and 4 in 1. Average collagen volume injected per treatment was 6.6 cc (range 2 to 13). All patients were evaluated on a subjective continence scale of no change (wet), improved or completely dry at the time of assessment. Of the 20 patients, 16 had no change, 3 showed improvement and 1 was dry. Initial improvement in the first 2 months after injection deteriorated thereafter in 16 cases. CONCLUSIONS: The previously reported high success rate of collagen injection is not supported by this study. With long-term followup collagen injection is rarely effective for treating urinary incontinence in children with neurogenic sphincter deficiency.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".