Guidelines for Perioperative Care in Cytoreductive Surgery (CRS) with or without hyperthermic IntraPEritoneal chemotherapy (HIPEC): Enhanced recovery after surgery (ERAS®) Society Recommendations — Part I: Preoperative and intraoperative management
Bibliographic record
Abstract
BACKGROUND: Enhanced recovery after surgery (ERAS) pathways have been shown to considerably reduce complications, length of stay and costs after most of surgical procedures by standardised application of best evidence-based perioperative care. The aim was to elaborate dedicated recommendations for cytoreductive surgery (CRS) ± hyperthermic intraperitoneal chemotherapy (HIPEC) in a two-part series of guidelines based on expert consensus. The present part I of the guidelines highlights preoperative and intraoperative management. METHODS: The core group assembled a multidisciplinary panel of 24 experts involved in peritoneal surface malignancy surgery representing the fields of general surgery (n = 12), gynaecological surgery (n = 6), and anaesthesia (n = 6). Experts systematically reviewed and summarized the available evidence on 72 identified perioperative care items, following the GRADE (grading of recommendations, assessment, development, evaluation) system. Final consensus (defined as ≥50%, or ≥70% of weak/strong recommendations combined) was reached by a standardised 2-round Delphi process, regarding the strength of recommendations. RESULTS: Response rates were 100% for both Delphi rounds. Quality of evidence was evaluated high, moderate low and very low, for 15 (21%), 26 (36%), 29 (40%) and 2 items, respectively. Consensus was reached for 71/72(98.6%) items. Strong recommendations were defined for 37 items, No consensus could be reached regarding the preemptive use of fresh frozen plasma. CONCLUSION: The present ERAS recommendations for CRS±HIPEC are based on a standardised expert consensus process providing clinicians with valuable guidance. There is an urgent need to produce high quality studies for CRS±HIPEC and to prospectively evaluate recommendations in clinical practice.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".