402 Association of Upper Gi Surgery of Gb&i (Augis)/Perioperative Quality Initiative (Poqi) Consensus Statement on Optimisation of Nutrition in Patients Undergoing Oesophagogastric Resections
Bibliographic record
Abstract
Abstract Aim A recent National Oeosphagogastric Nutrition Audit in the UK concluded there was a lack of confidence to provide nutritional support at the ‘front end’ of the pathway, a large variation of resource allocation and raised concerns over funding and staffing resource. This multidisciplinary collaborative study aimed to use best available evidence to produce guideline statements and recommendations on optimisation of nutrition in patients undergoing OG resections. Method A modified Delphi process, previously developed by the Peri-Operative Quality Initiative, was employed to develop consensus statements regarding the optimisation of nutrition in patients undergoing elective OG resections for cancer. The POQI board provided approval and independent supervision of the POQI process and meetings. Results Following a multicentre survey, thirty-nine consensus statements were agreed upon over the course of three online POQI conferences. A total of 30 participants took part in the POQI consensus process. The consensus statements covered four subgroups: 1. Nutrition Assessment, 2. Pre-Operative Nutrition Optimisation, 3. Post-Operative Nutrition Optimisation and 4. Nutrition Optimisation in Long Term Survivors. The level of evidence to support each statement was considered and recorded. Areas where evidence was limited, but felt to be critical for further optimisation, were identified as recommendations for research. Conclusions Consensus guidelines to optimise nutrition in patients undergoing OG cancer resections have been developed and refined. These guidelines will facilitate the multidisciplinary team in their goal to improve outcomes for patients undergoing OG resections.
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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 | 0.075 | 0.108 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".