Influence of steep Trendelenburg position on postoperative complications: a systematic review and meta-analysis
Bibliographic record
Abstract
Intraoperative physiologic changes related to the steep Trendelenburg position have been investigated with the widespread adoption of robot-assisted pelvic surgery (RAPS). However, the impact of the steep Trendelenburg position on postoperative complications remains unclear. We conducted a meta-analysis to compare RAPS to laparoscopic/open pelvic surgery with regards to the rates of venous thromboembolism (VTE), cardiac, and cerebrovascular complications. Meta-regression was performed to evaluate the influence of confounding risk factors. Ten randomized controlled trials (RCTs) and 47 non-randomized controlled studies (NRSs), with a total of 380,125 patients, were included. Although RAPS was associated with a decreased risk of VTE and cardiac complications compared to laparoscopic/open pelvic surgery in NRSs [risk ratio (RR), 0.59; 95% CI 0.51-0.72, p < 0.001 and RR 0.93; 95% CI 0.58-1.50, p = 0.78, respectively], these differences were not confirmed in RCTs (RR 0.92; 95% CI 0.52-1.62, p = 0.77 and RR 0.93; 95% CI 0.58-1.50, p = 0.78, respectively). In subgroup analyses of laparoscopic surgery, there was no significant difference in the risk of VTE and cardiac complications in both RCTs and NRSs. In the meta-regression, none of the risk factors were found to be associated with heterogeneity. Furthermore, no significant difference was observed in cerebrovascular complications between RAPS and laparoscopic/open pelvic surgery. Our meta-analysis suggests that the steep Trendelenburg position does not seem to affect postoperative complications and, therefore, can be considered safe with regard to the risk of VTE, cardiac, and cerebrovascular complications. However, proper individualized preventive measures should still be implemented during all surgeries including RAPS to warrant patient safety.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.030 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".