Implementation of a Multidisciplinary Enhanced Recovery After Surgery (ERAS) Program for Cytoreductive Surgery (CRS) With Hyperthermic Intraperitoneal Chemotherapy (HIPEC)
Bibliographic record
Abstract
ABSTRACT Background and Objectives Cytoreductive surgery with hyperthermic intraperitoneal chemotherapy (CRS/HIPEC) can be associated with prolonged hospital stays. A novel Enhanced Recovery After Surgery (ERAS) based on ERAS Society guidelines was designed and implemented. The primary outcome was ERAS compliance. Secondary outcomes included length of stay (LOS) and postoperative complications. Methods A retrospective study on patients who underwent CRS/HIPEC between 2018 and 2022, with ERAS implementation in 2022. Health records were reviewed. Statistical analysis included descriptive statistics, Wilcoxon tests, Student t ‐test, and χ 2 and binomial negative regression. Health Ethics Research Board approval was obtained. Results Eighty patients underwent CRS/HIPEC: 59 in the pre‐ERAS group and 21 in the post‐ERAS group. Groups were similar in age, comorbidities, and Peritoneal Carcinomatosis Index. ERAS compliance increased from 32.8% to 70.8% ( p < 0.001). Median LOS decreased from 14 to 9 days ( p < 0.001). Comparing pre‐ERAS to post‐ERAS showed no significant difference in the major morbidity rate (13.6% vs. 9.5%) or 30‐day readmission (9.4% vs. 4.8%) and no mortalities. Controlling for patient characteristics, the mean LOS decreased by 6.94 days ( p < 0.001). Conclusion Implementation of an ERAS CRS/HIPEC program is safe and allows for improved compliance to ERAS protocols and a significant reduction in LOS.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".