Prediction of obstructive coronary artery disease in patients undergoing heart valve surgery: A cross-sectional study in a tertiary care hospital.
Sy Van HoangHai Phuong Nguyen TranKha Minh NguyenPhong Thanh TranKhoa Le Anh HuynhNghia Thuong NguyenPublished in: Journal of cardiovascular and thoracic research (2023)
Introduction: Estimating the probability of obstructive coronary artery disease in patients undergoing noncoronary cardiac surgery should be considered compulsory. Our study sought to evaluate the prevalence of obstructive coronary artery disease in patients undergoing valvular heart surgery and to utilize predictive methodology of concomitant obstructive coronary artery disease in these patients. Methods: The retrospective study cohort was derived from a tertiary care hospital registry of patients undergoing coronary angiogram prior to valvular heart operations. Decision tree, logistic regression, and support vector machine models were built to predict the probability of the appearance of obstructive coronary artery disease. A total of 367 patients from 2016 to 2019 were analyzed. Results : The mean age of the study population was 57.3±9.3 years, 45.2% of the patients were male. Of 367 patients, 76 (21%) patients had obstructive coronary artery disease. The decision tree, logistics regression, and support vector machine models had an area under the curve of 72% (95% CI: 62% - 81%), 67% (95% CI: 56% - 77%), and 78% (95% CI: 68% - 87%), respectively. Multivariate analysis indicated that hypertension (OR 1.98; P =0.032), diabetes (OR 2.32; P =0.040), age (OR 1.05; P =0.006), and typical angina (OR 5.46; P <0.001) had significant role in predicting the presence of obstructive coronary artery disease. Conclusion: Our study revealed that approximately one-fifth of patients who underwent valvular heart surgery had concomitant obstructive coronary artery disease. The support vector machine model showed the highest accuracy compared to the other model.
Keyphrases
- coronary artery disease
- end stage renal disease
- patients undergoing
- chronic kidney disease
- newly diagnosed
- ejection fraction
- percutaneous coronary intervention
- heart failure
- peritoneal dialysis
- atrial fibrillation
- cardiovascular events
- prognostic factors
- deep learning
- cardiovascular disease
- minimally invasive
- cardiac surgery
- decision making
- acute coronary syndrome
- weight loss