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Record W7117459041 · doi:10.1093/bjs/znaf270.199

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

2025· article· en· W7117459041 on OpenAlexaff
P Singh, Fiona Huddy, Sivesh Kamarajah, Jennifer Redfern, Leo R. Brown, Richard Skipworth, Geoffrey Roberts, Sheraz R. Markar, James Gossage, Denny Levett, Mike Grocott, Javed Sultan

Bibliographic record

VenueBritish journal of surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicNutrition and Health in Aging
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsAuditGuidelineDelphi methodParenteral nutritionMEDLINEDelphiStatement (logic)Quality (philosophy)Clinical nutrition

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.095
GPT teacher head0.368
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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