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Record W2022228654 · doi:10.1503/cmaj.111072

Determinants of variations in coronary revascularization practices

2011· article· en· W2022228654 on OpenAlexafffundvenueabout
Jack V. Tu, Dennis T. Ko, Helen Guo, Janice A. Richards, Nancy Walton, Madhu K. Natarajan, Harindra C. Wijeysundera, Derek So, David A. Latter, Christopher M. Feindel, Kori Kingsbury, Eric A. Cohen

Bibliographic record

VenueCanadian Medical Association Journal · 2011
Typearticle
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsInstitute for Clinical Evaluative SciencesMcMaster University Medical CentreHamilton Health SciencesToronto Metropolitan UniversityUniversity Health NetworkUniversity of TorontoUniversity of OttawaOntario Stroke NetworkSunnybrook Health Science CentreSt. Michael's Hospital
FundersCanadian Institutes of Health ResearchAbbott VascularInstitute for Clinical Evaluative SciencesEdwards LifesciencesEli Lilly and Company
KeywordsConventional PCIMedicinePercutaneous coronary interventionCardiac catheterizationCoronary artery diseaseRevascularizationCardiologyInternal medicineCohortPopulationPercutaneousRetrospective cohort studyConfidence intervalSurgeryMyocardial infarction

Abstract

fetched live from OpenAlex

BACKGROUND: The ratio of percutaneous coronary interventions to coronary artery bypass graft surgeries (PCI:CABG ratio) varies considerably across hospitals. We conducted a comprehensive study to identify clinical and nonclinical factors associated with variations in the ratio across 17 cardiac centres in the province of Ontario. METHODS: In this retrospective cohort study, we selected a population-based sample of 8972 patients who underwent an index cardiac catheterization between April 2006 and March 2007 at any of 17 hospitals that perform invasive cardiac procedures in the province. We classified the hospitals into four groups by PCI:CABG ratio (low [< 2.0], low-medium [2.0-2.7], medium-high [2.8-3.2] and high [> 3.2]). We explored the relative contribution of patient, physician and hospital factors to variations in the likelihood of patients receiving PCI or CABG surgery within 90 days after the index catheterization. RESULTS: The mean PCI:CABG ratio was 2.7 overall. We observed a threefold variation in the ratios across the four hospital ratio groups, from a mean of 1.6 in the lowest ratio group to a mean of 4.6 in the highest ratio group. Patients with single-vessel disease usually received PCI (88.4%-99.0%) and those with left main artery disease usually underwent CABG (80.8%-94.2%), regardless of the hospital's procedure ratio. Variation in the management of patients with non-emergent multivessel disease accounted for most of the variation in the ratios across hospitals. The mode of revascularization largely reflected the recommendation of the physician performing the diagnostic catheterization and was also influenced by the revascularization "culture" at the treating hospital. INTERPRETATION: The physician performing the diagnostic catheterization and the treating hospital were strong independent predictors of the mode of revascularization. Opportunities exist to improve transparency and consistency around the decision-making process for coronary revascularization, most notably among patients with non-emergent multivessel disease.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.313
Threshold uncertainty score0.623

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.298
Teacher spread0.270 · 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 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

Citations95
Published2011
Admission routes4
Has abstractyes

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