Creation of an Enhanced Recovery After Surgery (ERAS) Guideline for neonatal intestinal surgery patients: a knowledge synthesis and consensus generation approach and protocol study
Bibliographic record
Abstract
INTRODUCTION: Enhanced Recovery After Surgery (ERAS) guidelines integrate evidence-based practices into multimodal care pathways designed to optimise patient recovery following surgery. The objective of this project is to create an ERAS protocol for neonatal abdominal surgery. The protocol will identify and attempt to bridge the gaps between current practices and best evidence. Our study is the first paediatric ERAS protocol endorsed by the International ERAS Society. METHODS: A research team consisting of international clinical and family stakeholders as well as methodological experts have iteratively defined the scope of the protocol in addition to individual topic areas. A modified Delphi method was used to reach consensus. The second phase will include a series of knowledge syntheses involving a rapid review coupled with expert opinion. Potential protocol elements supported by synthesised evidence will be identified. The Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) system will be used to determine strength of recommendations and the quality of evidence. The third phase will involve creation of the protocol using a modified RAND/UCLA Appropriateness Method. Group consensus will be used to rate each element in relation to the quality of evidence supporting the recommendation and the appropriateness for guideline inclusion. This protocol will form the basis of a future implementation study. ETHICS AND DISSEMINATION: This study has been registered with the ERAS Society. Human ethics approval (REB 18-0579) is in place to engage patient families within protocol development. This research is to be published in peer-reviewed journals and will form the care standard for neonatal intestinal surgery.
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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 | 0.416 | 0.365 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.024 | 0.006 |
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".