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Record W4404282127 · doi:10.1093/bjs/znae271.204

BN SO33 - The complex benign multi-disciplinary team meeting - a paradigm shift in decision making for benign oesophagogastric surgery

2024· article· en· W4404282127 on OpenAlexaff
Thomas Arkle, Sri Sivarajan, Petya Yordzheva, Nicholas Penney, Loveena Sreedharan, Bhaskar Kumar

Bibliographic record

VenueBritish journal of surgery · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsUniversity Hospital Foundation
Fundersnot available
KeywordsMedicineDisciplineGeneral surgerySurgery

Abstract

fetched live from OpenAlex

Abstract Background Decision making in benign OG pathology can be particularly challenging given the overlap with functional disorders, such as reflux hypersensitivity. A specialist benign oesophagogastric (OG) multidisciplinary team (MDT) may improve our ability to triage potential surgical candidates from those with functional conditions. Unlike in OG cancer, there is a paucity of evidence to support an MDT based approach in benign OG surgery. This study aims to report our experience of introducing a specialist benign OG MDT in an OG tertiary centre in the UK, examining the effect on decision making and an assessment of its acceptability and utility to clinicians. Method A review of consecutive cases discussed in the specialist benign OG MDT since inception in 2022 was undertaken. We reviewed indications, treatment plans and outcomes, any alteration in treatment pathway and final decisions. The primary outcome was the proportion of patients with a change in management as a result of MDT discussion. Where applicable, results were reported using descriptive statistics. A seven-item electronic questionnaire was also circulated to MDT members (OG surgeons, specialist gastroenterologists, GI radiographers, GI physiologists, and doctors in training), to assess the acceptability and perceived utility of the meetings. Results 74 patient cases were discussed (median age 57.5 (25-79) years). 71/74 (96.0%) of referrals were made by OG surgeons, most commonly to discuss anti-reflux procedures (53/74 (71.6%)). 34/74 (45.9%) patients had undergone previous surgery, most commonly laparoscopic fundoplication. MDT discussion led to a change in management in 43/74 (58.1%) case with recommendations of further investigation (23.0%), further OG clinic review (18.9%) and 21.6% listed for surgery. 12/74 (16.2%) were referred to other specialist services, including clinical psychology. Survey confirmed that all MDT members found their understanding of oesophageal physiology and subsequent decision-making ability in clinic was greatly enhanced. Conclusion Our results show that the complex benign MDT is an effective tool, demonstrating changes to management in over half of cases discussed, including recommending surgery less frequently following specialist review of physiology investigations. Such tests effectively identify functional disorders, such as rumination, highlighting a need for clear onward referral pathways involving specialist psychologists. The meetings have also proven to be valuable learning tools for all attendees of all grades. We strongly believe that adopting an MDT approach to benign OG conditions will enhance collaborative decision making, improve patient outcomes and therefore should be nationally mandated and recommended through AUGIS guidelines.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.076
GPT teacher head0.336
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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