Bibliographic record
Abstract
Background: Urinary stress incontinence is a health condition affecting millions of women globally with an incidence reaching 35%. The initial management is usually of conservative nature in the form of pelvic floor muscle training. If this fails then surgical management is offered. There are different methods of managing urinary stress incontinence like mid-urethral tape (MUT) insertion, colposuspension or the use of urethral bulking agents. In our unit, MUT insertion has been the conventional method of surgical management. Methods: The data were obtained from retrospective auditing of our practice in our Trust that was conducted on three different phases over 4 years (2011 to 2015). The source of information was the database and clinical notes. Results: A total of 221 patients underwent MUT insertion. Thirty-five procedures were performed by urologists and 185 by gynecologists. Twenty-three surgeries were performed by gynecologic trainees under senior supervision. All the MUT insertions performed by urologists were performed by consultants. Fifty patients (22.6%) experienced urinary retention, 18 had to use clean intermittent catheterization (CISC) (8%), and 41 patients (13%) developed symptoms of over-active bladder. There have been four bladder perforations (1.8%) all associated with tension-free vaginal tape (TVT) procedures and two cases of tape erosions (1%). Four patients (5%) complained of groin pain post-operatively; all of them had undergone tension-free obturator tape (TVT-O) procedure. There have been no buttonhole injuries, pelvic hematomata, or bleeding complications. In addition to that there have been no post-operative infections. Conclusions: Our complication rates have been concomitant with those described in literature. A surgical database proves helpful not only in auditing surgical effectiveness but also in comparing the surgical managements between different surgeons and departments. J Clin Gynecol Obstet. 2019;8(2):44-47 doi: https://doi.org/10.14740/jcgo544
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".