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Surgical Swine Model of Chronic Cardiac Ischemia Treated by Off-Pump Coronary Artery Bypass Graft Surgery
Published on: March 27, 2018
A quality assurance model of operative mortality in coronary artery surgery
F H Edwards1, R A Albus, R Zajtchuk
1Department of Cardiothoracic Surgery, Walter Reed Army Medical Center, Washington, DC 20307-5001.
Insights
Comparing coronary artery bypass grafting (CABG) mortality requires risk adjustment. A validated risk model demonstrated that our hospital's CABG outcomes aligned with national standards, proving raw data is misleading for quality assurance.
Area of Science:
- Cardiovascular Surgery
- Health Services Research
- Biostatistics
Background:
- Quality assurance in coronary artery bypass grafting (CABG) necessitates comparing operative mortality against established standards.
- Raw mortality statistics are insufficient for accurate interinstitutional comparisons; risk factor analysis is crucial but often inadequately demonstrated.
- Previous reports have not sufficiently illustrated the principle of risk-adjusted mortality analysis in CABG.
Purpose of the Study:
- To develop a validated risk model for coronary artery bypass grafting (CABG) mortality.
- To demonstrate the appropriate application of a risk model in assessing coronary artery surgery outcomes.
- To highlight the limitations of raw mortality data in quality assurance.
Main Methods:
- A Bayesian analysis was performed on 6,630 patients from the Coronary Artery Surgery Study (CASS) registry to derive the risk model.
- The model incorporated patient factors including age, sex, ventricular function, prior myocardial infarction, extent of coronary artery disease, unstable angina, and surgical priority.
- The developed risk model was applied to 840 isolated CABG patients from a single institution (1984-1987) for risk stratification.
Main Results:
- Initial comparison of raw mortality data showed a significant difference between the institution's 3.9% (33/840) and the CASS registry's 2.3% (153/6,630) mortality (p < 0.001).
- After applying the CASS risk stratification model, the institution's CABG mortality was found to conform to the CASS experience.
- The study identified a fallacy in using unadjusted mortality statistics for comparing surgical outcomes between different institutions.
Conclusions:
- Risk-adjusted analysis is fundamental for effective quality assurance in coronary artery bypass grafting (CABG) surgery.
- The developed risk model effectively stratifies CABG patients, enabling appropriate comparison of institutional outcomes.
- Raw mortality data is misleading and should not be used for interinstitutional quality comparisons in CABG.
Abstract:
Quality assurance in coronary artery bypass grafting (CABG) surgery requires a comparison of operative mortality against an accepted standard of care. Raw mortality statistics are unacceptable in this context, and risk factor analysis is essential. However, this principle has not been adequately demonstrated in previous reports. Our goal in this study was to develop a risk model of accepted CABG mortality and illustrate its proper use in coronary artery surgery. The model was derived from a Bayesian analysis of 6,630 patients undergoing CABG in the Coronary Artery Surgery Study (CASS) registry. Age, sex, ventricular function, previous myocardial infarction, extent of coronary artery disease, unstable angina, and surgical priority were used by the model to sort patients into risk categories. From January 1984 through December 1987, 840 patients underwent isolated CABG at our hospital. With raw mortality data, the 3.9% (33/840) mortality of our patients was significantly different from the 2.3% (153/6,630) CASS mortality (p less than 0.001). When our patients were entered into the CASS model for risk stratification, however, our CABG mortality conformed to the CASS experience. These results illustrate the fallacy of using raw mortality statistics for interinstitutional comparisons. This type of risk model is a fundamental element of CABG quality assurance.
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