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Record W2067689694 · doi:10.1097/sla.0b013e3181a77bcd

The More the Better?

2009· article· en· W2067689694 on OpenAlexaffabout
Paul J. Karanicolas, Luc Dubois, Patrick Colquhoun, Carol J. Swallow, Stephen D. Walter, Gordon Guyatt

Bibliographic record

VenueAnnals of Surgery · 2009
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Surgical Treatments
Canadian institutionsUniversity of TorontoWestern University
Fundersnot available
KeywordsMedicineDiverticular diseaseColorectal cancerOdds ratioMalignancyMortality ratePerioperativeColorectal surgeryLogistic regressionResectionSurgeryGeneral surgeryInternal medicineCancerAbdominal surgery

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the in-hospital mortality rates for patients undergoing colorectal resection for malignant or benign conditions, and to identify risk factors for in-hospital death, particularly the relationships with surgeon and hospital volume. BACKGROUND: Although there is strong evidence that complex cancer operations are best performed at specialized high-volume centers and by high-volume surgeons, the relationship between surgeon and hospital volume and perioperative outcomes is less well defined for more common procedures such as colorectal resections, particularly for benign diseases. METHODS: We obtained data from the Canadian Institute for Health Information Discharge Abstract Database on all adult patients who underwent colorectal resection between April 1, 2005 and March 31, 2006. We performed a logistic regression to identify variables associated with a higher likelihood of in-hospital death. RESULTS: Twenty-one thousand seventy-four patients underwent colorectal resection, with the majority being elective (59.4%). Malignancy represented the most common indication for resection (56.8%), followed by diverticular disease (16.2%) and inflammatory bowel disease (7.1%). The overall in-hospital mortality rate among patients undergoing colorectal resection was 5.3%. Increased age (adjusted Odds Ratio [OR]: 1.97 per 10 years, P < 0.001), urgent operation (OR: 2.63, P < 0.001), indication for resection (P < 0.001), nature of the surgery (P < 0.001), and several comorbidities were all independently associated with an increased risk of death. Surgeons with higher volumes of colorectal resections achieved significantly lower mortality rates (OR: 0.92 per 20 cases/y, P = 0.003), corresponding to an adjusted mortality rate of 5.6% for surgeons in the bottom decile (1 case per year) compared with 4.5% for surgeons in the top decile (greater than 43 cases per year). Hospital volume was not associated with mortality (OR: 1.00 per 10 cases, P = 0.504). CONCLUSIONS: This large, population-based study suggests that surgeons who perform high volumes of colorectal resections achieve lower in-hospital mortality rates than surgeons with low volumes, whereas the hospital volume does not influence mortality.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.804
Threshold uncertainty score0.138

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.233
GPT teacher head0.389
Teacher spread0.156 · 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

Citations70
Published2009
Admission routes2
Has abstractyes

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