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Record W7117461642 · doi:10.1093/bjs/znaf270.035

397 Structural Characteristics Associated with Improved Outcomes in Gastrointestinal Cancer Surgery: A Systematic Review

2025· article· en· W7117461642 on OpenAlexaff
Sarah Epton, Nikhil Patel, Min Hae Park, Jesper Lagergren, David Cromwell, Prem Chana, James Gossage

Bibliographic record

VenueBritish journal of surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicEnhanced Recovery After Surgery
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsCentralisationDemographicsGastrointestinal cancerCancer surgeryCancerMEDLINEHealth care

Abstract

fetched live from OpenAlex

Abstract Background Centralisation of gastrointestinal (GI) cancer surgical services has corresponded with improvements in post-operative outcomes over the last two decades. However, centralisation has been variably implemented, and the specific structural factors that confer benefit remain unclear. This systematic review aimed to summarise current evidence on the structural characteristics associated with quality outcomes following surgery for cancers of the GI tract. Method A systematic search of the Embase, MEDLINE, and Cochrane databases was performed to identify studies that evaluated the importance of structure, or individual structural characteristics, in GI cancer surgery. These were categorised into one of: volume/centralisation, hospital infrastructure, personnel/staffing, or standardised care protocols. Outcomes of interest included mortality, morbidity, length of hospital stay, failure to rescue, readmission and cost. Results Sixty studies were included in the review. Greater hospital, surgeon and anaesthetic operative volume were each associated with improved outcomes. Protocols such as enhanced recovery after surgery contributed to faster peri-operative recovery and shorter hospital length of stay. While evidence on optimal post-operative care team composition was limited, geriatric co-management, physiotherapy, and dietetic input were each found to be important. Conclusions Although increased operative volume following centralisation is associated with improved surgical outcomes, definitions of ‘high-volume’ are variable and operation-specific volume thresholds have yet to be defined. Additional research to establish the ideal demographics of the peri-operative care team is also needed. This likely comprises surgeons, peri-operative physicians, specialist anaesthetists, dieticians, and physiotherapists, with additional on-site support from specialties such as interventional radiology and gastroenterology.

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)0.002
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
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 head0.017
GPT teacher head0.270
Teacher spread0.254 · 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.

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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