Clinical efficacy of enhanced recovery after surgery (ERAS) program in patients undergoing radical prostatectomy: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Enhanced recovery after surgery (ERAS) protocol has been identified to be beneficial in the amount of operations such as gastrointestinal surgery. However, the efficacy and safety in robot-assisted laparoscopic prostatectomy/laparoscopic radical prostatectomy (RALP/LRP) still remain controversial. METHOD: We searched randomized controlled trials and retrospective cohort studies comparing ERAS versus conventional care for prostate cancer patients who have undergone RALP/LRP. ERAS-related data were extracted, and quality of included studies was assessed using the Newcastle-Ottawa quality assessment scale and the Jadad scale. RESULT: As a result, seven trials containing 784 prostate cancer patients were included. ERAS was observed to be significantly associated with shorter length of hospital stay (SMD - 2.55, 95%CI - 3.32 to - 1.78, P < 0.05), shorter time to flatus (SMD - 1.55, 95%CI - 2.26 to - 0.84, P < 0.05), shorter time to ambulate (SMD - 6.50, 95%CI - 10.91 to - 2.09, P < 0.05), shorter time to defecate (SMD - 2.80, 95%CI - 4.56 to - 1.04, P < 0.05), and shorter time to remove drainage tube (SMD - 2.72, 95%CI - 5.31 to - 0.12, P < 0.05). Otherwise, no significant difference was reported in other measurements. CONCLUSIONS: In conclusion, ERAS can reduce length of hospital stay, time to flatus, time to defecate, time to ambulate, and time to remove drainage tube in prostate cancer patients who have undergone RALP/LRP compared with conventional care.
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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 | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.034 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| 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".