Podium Session 3: Incontinence, Reconstruction, ED: Postprostatectomy Issues
Bibliographic record
Abstract
Introduction and Objective:A new surgical technique of pelvic reconstruction using a transvaginal mesh, the Prolift system, attempts to improve the high recurrence and complication rate of conventional surgical treatments for pelvic organ prolapse (POP).The objective of the study was to report our experience on the implantation of the Prolift system. Materials and Methods:The population of the study included 56 patients operated from July 29, 2005, to August 29, 2008, by one surgeon (LMT).The patients have all undergone the implantation of a transvaginal mesh, the Prolift system, for the treatment of recurrent or high-grade multiple compartment POP (Baden-Walker stage 3 or 4).A concomitant antiincontinence surgery was performed in 38 patients (68%).Results: The population had a mean age of 68.1 (46-88), a body mass index (BMI) of 27 (21-40) and a parity average of 3.3 (1-16).Previous POP repair had been performed in 17 patients (30%) and a hysterectomy in 43 (77%).High-grade genital prolapse was present in the anterior vaginal wall in 71% (40/56), apical wall in 45% (25/56) and posterior wall in 48% (27/56).Operating time was on average 98 (70-135) minutes, blood loss 81 (50-300) mL and hospital stay 2.9 (1-10) days.With a median follow-up of 17 months, the cure rate for pelvic organ prolapse was 91% (48/53) and the dry rate was 76% (40/53).Perioperative complications included 1 anterior rectal wall laceration that required primary repair and removal of the entire mesh, as well as 1 prolonged bleeding that required embolisation of the left internal iliac artery.Short-term postoperative complications comprised 10 episodes of transient urinary retention that required immediate tape release in 4 patients, 2 cases of postoperative pain that lasted a maximum of 2 weeks and 1 episode of transient fever.Long-term complications included 5 POP recurrences that required revision in 1 case.Conclusion: The Prolift system appears to be a safe and effective treatment option for the treatment of recurrent or high-grade multiple compartment POP, because of a low number of complications and a high midterm cure rate.However, long-term follow-up is still needed in order to confirm the safety and effectiveness of the procedure.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.061 | 0.013 |
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".