Enhanced recovery after surgery for liver resection
Bibliographic record
Abstract
INTRODUCTION: Enhanced recovery after surgery (ERAS) reduces postoperative length of hospital stay and patient stress response to liver surgery. The aim of the present study was to evaluate the efficacy and feasibility of an ERAS programme for liver resection. METHODS: A multidisciplinary ERAS protocol was implemented for both open and laparoscopic liver resection in a tertiary hospital in Hong Kong. The clinical outcomes of patients who underwent liver resection and underwent the ERAS perioperative programme were compared with those who received a conventional perioperative programme between September 2015 and July 2016. Propensity score matching analysis was used to minimise background differences. RESULTS: A total of 20 patients who underwent liver resection were recruited to the ERAS programme. Their clinical outcomes were compared with another 20 patients who received hepatectomy under a conventional perioperative programme after propensity score matching. The ERAS programme was associated with a significantly shorter length of hospital stay (P=0.033) without an increase in complication rates in patients who underwent open liver resection. There was no such significant association in patients who underwent laparoscopic liver resection. No patients required readmission in this cohort. CONCLUSIONS: The ERAS perioperative programme for liver resection is safe and feasible. It significantly shortened the hospital stay after open liver resection but not after laparoscopic liver resection.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 teacher head, 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".