Are older women more likely to receive surgical treatment for stress urinary incontinence since the introduction of the mid‐urethral sling? An examination of Hospital Episode Statistics data
Bibliographic record
Abstract
OBJECTIVE: To examine the trends in surgical treatment of stress urinary incontinence (SUI) in older women since the introduction of the mid-urethral sling. DESIGN: Analysis of data from Hospital Episode Statistics (HES) between 2000 and 2012. SETTING AND POPULATION: All surgical procedures for SUI in the National Health Service (NHS) in England. METHODS: Retrospective cohort analysis of Hospital Episode Statistics for England from 2000 to 2012. MAIN OUTCOME MEASURES: Number of invasive, less invasive, and urethral bulking procedures performed in women in three age groups. RESULTS: There was a 90% fall in the number of invasive surgical treatments for SUI and a four-fold increase in the number of mid-urethral slings over this time. The total number of surgical procedures for SUI increased from 8458 to 13 219. However, the rise in the number of procedures in women aged over 75 was more modest-a three-fold increase from a low start of 187-and these women now make up a smaller proportion of all women receiving a mid-urethral sling (MUS). CONCLUSIONS: Despite the development and wide availability of a less invasive, safe and effective operation for stress urinary incontinence in older women, they do not appear to have benefitted. The reasons for this require prospective investigation.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 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".