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Record W4402374926 · doi:10.1093/bjs/znae197.336

FP1.3 - SPEC MDT in Aneurin Bevan University Health Board

2024· article· en· W4402374926 on OpenAlexaff
Ayako Niina, M. Elnaghi, Usman Khan, H Jones

Bibliographic record

VenueBritish journal of surgery · 2024
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsRoyal Ottawa Mental Health Centre
Fundersnot available
KeywordsMedicineSpec#Health boardNursing

Abstract

fetched live from OpenAlex

Abstract Aims The SPEC (significant polyp and early cancer) multi-disciplinary team (MDT) meeting was started in ABUHB in 2022 to discuss complex colonic and rectal polyp cases, such as polyps >20mm, likely to be sessile, or difficult to remove endoscopically. The aim was to evaluate the effectiveness and clinical role of the SPEC MDT. Methods Data for patients discussed in SPEC MDT since its conception in January 2022 until September 2023 was retrospectively collected from the SPEC MDT database, a prospectively collected database. This included patient demographics, reason for referral, polyp characteristics and MDT outcomes. Results In 21 months, there have been 38 SPEC MDTs, with 355 cases discussed (average of 9 cases per MDT). There was at least one laparoscopic colorectal surgeon, gastroenterologist and a histopathologist in every MDT in accordance with BSG guidelines. Main referral reasons included endoscopy findings (72%) and re-discussion post-procedure (22%). Twenty-three patients had adenocarcinomas and three had NETs. MDT outcomes were EMR (23%), endoscopic surveillance (21%), clinic to discuss (no) surgery (19%), TAMIS (16%), urgent endoscopy (13%) or other (8%). Conclusion As the busiest Health Board in Wales for Colorectal Cancers, the formation of SPEC MDT has been an important step in improving the detection and treatment of advanced polyps and early cancers. Although too early to measure the impact on early cancer detection rates and improved decision making for these patients, formalising the MDT process in line with BSG guidelines has been an important step in improving the service offered to patients.

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)0.004
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation 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 score0.489
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.140
GPT teacher head0.379
Teacher spread0.238 · 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 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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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