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Long-term outcomes of percutaneous coronary intervention versus coronary artery bypass grafting in women with severe coronary artery disease

2024· article· en· W4403805763 on OpenAlexafffundabout
Kevin R. An, Dominique Vervoort, Feng Qiu, Derrick Y. Tam, Rodolfo V. Rocha, Lamia Harik, Sameer Hirji, Stephen E. Fremes, Harindra C. Wijeysundera, Mario Gaudino

Bibliographic record

VenueEuropean Heart Journal · 2024
Typearticle
Languageen
FieldMedicine
TopicAcute Myocardial Infarction Research
Canadian institutionsInstitute for Clinical Evaluative SciencesUniversity of Toronto
FundersWeill Cornell Medical CollegeCanadian Cardiovascular Society
KeywordsMedicinePercutaneous coronary interventionBypass graftingCardiologyInternal medicineCoronary artery diseaseArteryPercutaneousMyocardial infarction

Abstract

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Abstract Background The optimal revascularization strategy for severe coronary artery disease (CAD) in women remains controversial. Despite differences between women and men in the development of CAD, there remains a paucity of comparative real-world observational evidence comparing percutaneous coronary intervention (PCI) to coronary artery bypass grafting (CABG) in women. Purpose We evaluated short and long-term outcomes of PCI and CABG in women with severe CAD. Methods We conducted a propensity score-matched retrospective cohort study using linked clinical and administrative databases in Ontario, Canada to obtain records of women with left main, 3-vessel disease, or 2-vessel disease with proximal left anterior descending artery involvement undergoing PCI or CABG from April 1st, 2012 to December 31st, 2021. Patients who were >80 years of age and patients who underwent urgent or emergent procedures were excluded for the primary analysis. The primary outcome was a composite of myocardial infarction, stroke, repeat revascularization, and death (MACCE). Secondary outcomes included the individual components of MACCE and a composite of readmission for MI, heart failure, and stroke. Following multiple imputation and propensity score-matching, the Cox proportional hazards model and Fine-Gray sub-distribution hazard model with robust variance estimators accounting for death as a competing risk were used to evaluate long-term outcomes. Results In the primary cohort, 2469 patients underwent PCI and 3,721 patients underwent CABG. After propensity score matching, including by coronary disease territory, 2,033 well-balanced pairs were identified, with standardized mean differences <0.10 for all covariates. In-hospital death and stroke were significantly lower with PCI than with CABG (0.7% vs 1.5%, p=0.036) and (<0.2% vs 1.4%, p<0.001), respectively, and there was no difference in perioperative MI between PCI and CABG (1.1% vs 0.6%, p=0.121). At a median (IQR) of 5.1 (2.9-7.5) years, major adverse cardiac and cerebrovascular events (MACCE) was higher with PCI compared with CABG (37.7% vs 23.3%, HR 1.79, [95% CI: 1.66-1.91], p<0.001) (Figure 1). All-cause mortality was higher with PCI compared with CABG (17.8% vs 13.4%, HR 1.33, [95% CI: 1.21-1.45], p<0.001) (Figure 2). The composite readmission outcome (MI, heart failure, stroke) was higher with PCI compared with CABG (16.2% vs 11.2%, HR 1.42, [95% CI: 1.37-1.48], p<0.001). Conclusion In women with severe CAD, CABG appears to be associated with a long-term reduction in MACCE and mortality compared with PCI. Our findings provide evidence to suggest women with severe CAD may derive greater long-term benefit from CABG compared to PCI and suggest that the treatment recommendation should shift towards CABG in appropriately selected women.Figure 1.MACCE free survivalFigure 2.Overall survival

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)0.003
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 score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.330
Teacher spread0.287 · 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".

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Citations1
Published2024
Admission routes3
Has abstractyes

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