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Abstract 122: Characteristics of Patients with Multivessel Coronary Disease Treated with Percutaneous Intervention Versus Bypass Surgery and Preliminary Mortality Outcomes: A Province-wide Field Evaluation

2014· article· en· W1869954900 on OpenAlexaffabout
Laurie Lambert, Nataliya Dragieva, François Reeves, Yves Langlois, Michel Nguyen, Luc Bilodeau, Pierre Voisine, Michel Carrier, Michel Pellerin, Jean Morin, Peter Bogaty

Bibliographic record

VenueCirculation Cardiovascular Quality and Outcomes · 2014
Typearticle
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsMontreal Heart InstituteHôtel-Dieu de MontréalHôpital FleurimontRoyal Victoria HospitalInstitut universitaire de cardiologie et de pneumologie de QuébecInstitut National d'Excellence en Santé et en Services Sociaux
Fundersnot available
KeywordsConventional PCIMedicinePercutaneous coronary interventionInterquartile rangeCardiogenic shockMyocardial infarctionCardiologyInternal medicineRevascularizationCoronary artery diseaseCoronary artery bypass surgerySurgeryArtery

Abstract

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Introduction: Wide variation in choice of revascularization treatment for patients with multivessel coronary disease has been observed and outcomes of percutaneous coronary intervention (PCI) versus coronary artery bypass surgery (CABG) are increasingly examined. Our publicly funded cardiology evaluation unit was mandated by the Quebec Ministry of Health to evaluate the practice of multivessel revascularization and its outcomes across Quebec’s 8 tertiary cardiac centers offering both PCI and CABG. Methods: Hospital records were used to identify all multivessel (≥2 myocardial territories) interventions by PCI and isolated CABG in each center in 2010-12. Primary PCI patients were excluded. A maximum of 300 patients treated with CABG and 300 patients treated with PCI in each center were randomly selected for chart review by our evaluation unit. Results: The study cohort included 2018 PCI patients and 2274 isolated CABG patients. Median age was 66 years for both PCI (interquartile range, IQR: 59-76) and CABG (IQR: 59-72) and prevalence of most risk factors and comorbidities was very similar. However, compared to CABG patients, there were more females in the PCI group (27% vs 17%), more cardiogenic shock (2.2% vs 0.6%), more patients with previous PCI (27% vs 16%) and previous valve surgery (1.2% vs 0.1%), and more patients with interventions in only 2 myocardial territories (89% vs 31%). The PCI group was more likely than the CABG group to have acute myocardial infarction (AMI) (32% vs 18%) but less likely to have heart failure on admission (9% vs 18%). Almost 1 in 5 (19%) PCI patients were treated for left main disease. Diabetes was present in 29% of PCI patients vs 37% of CABG patients. Compared to CABG, PCI patients had a shorter median delay between admission and intervention (0 vs 2 days) as well as between intervention and discharge (1 vs 6 days) and were more likely to be transferred out to another hospital (37% vs 14%). However, mortality before discharge or transfer from tertiary cardiac centers was higher for PCI than CABG patients both with AMI (3.1% vs 0.7%) and without AMI (1.0% vs 0.5%). The differences of all reported comparisons were statistically significant (p< 0.001) except for in-hospital mortality without AMI (p=0.25). Conclusions: Patients with multivessel disease who were treated with PCI were more likely to present with acute symptoms, have more cardiogenic shock and more previous valve surgery but have less extensive coronary disease, less diabetes and less heart failure. Age and other risk factors and comorbidities were very similar in the 2 groups. Crude mortality during the index surgical hospital admission was higher for PCI despite a shorter length of stay. To gain more insight into these results, it will be important to link to medico-administrative data to examine 30-day and 1-year mortality and to adjust appropriately for potential confounders.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.040
Threshold uncertainty score0.764

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.047
GPT teacher head0.309
Teacher spread0.262 · 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".

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Citations0
Published2014
Admission routes2
Has abstractyes

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