Current role of injectable agents for female stress urinary incontinence.
Bibliographic record
Abstract
AIM: The current role of injectable agents in the management for female stress urinary incontinence is reviewed. MATERIALS AND METHODS: Published manuscripts for collagen, silicone microparticles, carbon beads, hyaluronic acid dextranomer and two investigational agents were evaluated. RESULTS: While injectable agents were used in the past for pure intrinsic sphincter deficiency there is good evidence that patients with hypermobility respond similarly. Collagen has been the most widely reported agent to date. Comparative studies with surgery have demonstrated inferior efficacy but a recent study showed a similar quality of life outcome. Newer agents have been designed for superior efficacy and durability. However, of the new agents carbon beads was not shown to be superior and the results of randomized trials of silicone microparticles and hyaluronic acid dextranomer compared to collagen have not yet been reported. All currently used agents appear to be very safe. CONCLUSIONS: Injectable agents have been shown to have efficacy in the management of stress incontinence in women and should be readily available as a treatment option. The definite superiority of one agent over another has not yet been established.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".