ArticleCMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne2021
Derivation and validation of predictive indices for 30-day mortality after coronary and valvular surgery in Ontario, Canada.
Article in CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Impact of renal-replacement therapy strategies on outcomes for patients with chronic kidney disease: a secondary analysis of the STARRT-AKI trial.Intensive care medicine · 2022Trial
- Mortality After Cardiovascular Surgery and Procedures During the COVID-19 Pandemic in Ontario, Canada: A Retrospective Cohort Study.CJC open · 2026Article
- Time-varying comparative effectiveness of surgical or percutaneous revascularization on patient-centred outcomes.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2025Article
- The impact of the COVID-19 pandemic on longitudinal trends of surgical mortality and inpatient quality of care in Ontario, Canada.Journal of advanced nursing · 2025Article
- Early menopause as an independent risk factor for postoperative atrial fibrillation in women undergoing coronary artery bypass grafting: a retrospective cohort study.BMC women's health · 2025Article
- Article
- Comparison of Multidimensional Frailty Instruments for Estimation of Long-term Patient-Centered Outcomes After Cardiac Surgery.JAMA network open · 2022Article
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Authors and funding
13 authors.
Funding
Abstract
backgroundCoronary artery bypass grafting (CABG) and surgical aortic valve replacement (AVR) are the 2 most common cardiac surgery procedures in North America. We derived and externally validated clinical models to estimate the likelihood of death within 30 days of CABG, AVR or combined CABG + AVR.
methodsWe obtained data from the CorHealth Ontario Cardiac Registry and several linked population health administrative databases from Ontario, Canada. We derived multiple logistic regression models from all adult patients who underwent CABG, AVR or combined CABG + AVR from April 2017 to March 2019, and validated them in 2 temporally distinct cohorts (April 2015 to March 2017 and April 2019 to March 2020).
resultsThe derivation cohorts included 13 435 patients who underwent CABG (30-d mortality 1.73%), 1970 patients who underwent AVR (30-d mortality 1.68%) and 1510 patients who underwent combined CABG + AVR (30-d mortality 3.05%). The final models for predicting 30-day mortality included 15 variables for patients undergoing CABG, 5 variables for patients undergoing AVR and 5 variables for patients undergoing combined CABG + AVR. Model discrimination was excellent for the CABG (c-statistic 0.888, optimism-corrected 0.866) AVR (c-statistic 0.850, optimism-corrected 0.762) and CABG + AVR (c-statistic 0.844, optimism-corrected 0.776) models, with similar results in the validation cohorts.
interpretationOur models, leveraging readily available, multidimensional data sources, computed accurate risk-adjusted 30-day mortality rates for CABG, AVR and combined CABG + AVR, with discrimination comparable to more complex American and European models. The ability to accurately predict perioperative mortality rates for these procedures will be valuable for quality improvement initiatives across institutions.
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