Impact of enhanced recovery protocols after pancreatoduodenectomy: meta-analysis
Bibliographic record
Abstract
BACKGROUND: This individual-patient data meta-analysis investigated the effects of enhanced recovery after surgery (ERAS) protocols compared with conventional care on postoperative outcomes in patients undergoing pancreatoduodenectomy. METHODS: The Cochrane Library, MEDLINE, Embase, Scopus, and Web of Science were searched systematically for articles reporting outcomes of ERAS after pancreatoduodenectomy published up to August 2020. Comparative studies were included. Main outcomes were postoperative functional recovery elements, postoperative morbidity, duration of hospital stay, and readmission. RESULTS: Individual-patient data were obtained from 17 of 31 eligible studies comprising 3108 patients. Time to liquid (mean difference (MD) -3.23 (95 per cent c.i. -4.62 to -1.85) days; P < 0.001) and solid (-3.84 (-5.09 to -2.60) days; P < 0.001) intake, time to passage of first stool (MD -1.38 (-1.82 to -0.94) days; P < 0.001) and time to removal of the nasogastric tube (3.03 (-4.87 to -1.18) days; P = 0.001) were reduced with ERAS. ERAS was associated with lower overall morbidity (risk difference (RD) -0.04, 95 per cent c.i. -0.08 to -0.01; P = 0.015), less delayed gastric emptying (RD -0.11, -0.22 to -0.01; P = 0.039) and a shorter duration of hospital stay (MD -2.33 (-2.98 to -1.69) days; P < 0.001) without a higher readmission rate. CONCLUSION: ERAS improved postoperative outcome after pancreatoduodenectomy. Implementation should be encouraged.
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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 | 0.023 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.073 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".