Peritoneal interposition flap reduces symptomatic lymphocele following transperitoneal robot-assisted radical prostatectomy and pelvic lymph node dissection: An updated meta-analysis
Bibliographic record
Abstract
Abstract Background Robot-assisted radical prostatectomy with intraoperative pelvic lymph node dissection is the criterion standard for surgical treatment of nonmetastatic intermediate- and high-risk prostate cancer. However, this method is associated with symptomatic lymphocele (SLC), which is an important morbidity factor. To overcome this complication, several modifications of the technique have been developed, including the peritoneal interposition flap (PIF). We performed an updated systematic review and meta-analysis to investigate the efficacy and safety of this technique for preventing SLC and lymphocele (LC) formation. Materials and methods Searches were performed using databases and references from included studies and previous systematic reviews. Only randomized controlled trials and nonrandomized cohorts were included. Primary outcomes were the incidence of SLC and LC formation, and safety outcomes were defined as operation time, estimated blood loss, length of hospital stay, and urinary incontinence. Quality assessment was performed using the Newcastle-Ottawa Scale and Cochrane Collaboration's tool. Pooled treatment effects were estimated using odds ratios with 95% confidence intervals (CIs) for binary endpoints. Heterogeneity was examined using Cochran's Q test and I 2 statistics; p values < 0.10 and I 2 > 25% were considered significant for heterogeneity. We used Mantel-Haenszel fixed-effect models in the analyses with low heterogeneity. Otherwise, the DerSimonian and Laird random-effects model was used. Results The initial search yielded 510 results. After the removal of duplicate records and application of the exclusion criterion, 9 studies were fully reviewed for eligibility. Three randomized controlled trials and 5 retrospective cohorts met all the inclusion criteria, comprising 2261 patients, of whom 1073 (47.4%) underwent PIF. Six studies reported a significant reduction in SLC in the PIF group, and 3 of the 4 studies reported LC formation yielded significant results in preventing this complication. The incidence of SLC and LC formation in a follow-up of ≥3 months was significantly different between the PIF and no PIF group (odds ratio, 0.34 [95% CI, 0.16–0.74; p = 0.006] and 0.48 [95% CI, 0.31–0.74; p = 0.0008]), respectively. The safety outcomes did not differ significantly between the 2 groups. Conclusions These results suggest that PIF is an effective and safe technique for preventing LC and SLC in patients undergoing transperitoneal robot-assisted radical prostatectomy and pelvic lymph node dissection.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.029 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".