Outcomes before and after Implementation of the ERAS (Enhanced Recovery after Surgery) Protocol in Open and Laparoscopic Colorectal Surgery: A Comparative Real-World Study from Northern Italy
Bibliographic record
Abstract
Enhanced Recovery After Surgery (ERAS) protocols have changed perioperative care, aiming to optimize patient outcomes. This study assesses ERAS implementation effects on postoperative complications, length of hospital stay (LOS), and mortality in colorectal cancer (CRC) patients. A retrospective real-world analysis was conducted on CRC patients undergoing surgery within a Northern Italian Cancer Registry. Outcomes including complications, re-surgeries, 30-day readmission, mortality, and LOS were assessed in 2023, the year of ERAS protocol adoption, and compared with data from 2022. A total of 158 surgeries were performed, 77 cases in 2022 and 81 in 2023. In 2023, a lower incidence of postoperative complications was observed compared to that in 2022 (17.3% vs. 22.1%), despite treating a higher proportion of patients with unfavorable prognoses. However, rates of reoperations and readmissions within 30 days post-surgery increased in 2023. Mortality within 30 days remained consistent between the two groups. Patients diagnosed in 2023 experienced a statistically significant reduction in LOS compared to those in 2022 (mean: 5 vs. 8.1 days). ERAS protocols in CRC surgery yield reduced postoperative complications and shorter hospital stays, even in complex cases. Our study emphasizes ERAS' role in enhancing surgical outcomes and recovery.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".