1. Risk factors based vessel‐specific prediction for stages of coronary artery disease using Bayesian quantile regression machine learning method: Results from the PARADIGM registry
- Author
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Hyung‐Bok Park, Jina Lee, Yongtaek Hong, So Byungchang, Wonse Kim, Byoung K. Lee, Fay Y. Lin, Martin Hadamitzky, Yong‐Jin Kim, Edoardo Conte, Daniele Andreini, Gianluca Pontone, Matthew J. Budoff, Ilan Gottlieb, Eun Ju Chun, Filippo Cademartiri, Erica Maffei, Hugo Marques, Pedro de A. Gonçalves, Jonathon A. Leipsic, Sanghoon Shin, Jung H. Choi, Renu Virmani, Habib Samady, Kavitha Chinnaiyan, Peter H. Stone, Daniel S. Berman, Jagat Narula, Leslee J. Shaw, Jeroen J. Bax, James K. Min, Woong Kook, and Hyuk‐Jae Chang
- Subjects
cardiovascular risk factors ,Prevention ,Bayes Theorem ,Coronary Artery Disease ,General Medicine ,Cardiorespiratory Medicine and Haematology ,Coronary Angiography ,Cardiovascular ,Atherosclerosis ,Coronary Vessels ,Angina Pectoris ,Machine Learning ,Heart Disease ,Cardiovascular System & Hematology ,Risk Factors ,Humans ,Registries ,Cardiology and Cardiovascular Medicine ,Heart Disease - Coronary Heart Disease - Abstract
Background and hypothesisThe recently introduced Bayesian quantile regression (BQR) machine-learning method enables comprehensive analyzing the relationship among complex clinical variables. We analyzed the relationship between multiple cardiovascular (CV) risk factors and different stages of coronary artery disease (CAD) using the BQR model in a vessel-specific manner.MethodsFrom the data of 1,463 patients obtained from the PARADIGM (NCT02803411) registry, we analyzed the lumen diameter stenosis (DS) of the three vessels: left anterior descending (LAD), left circumflex (LCx), and right coronary artery (RCA). Two models for predicting DS and DS changes were developed. Baseline CV risk factors, symptoms, and laboratory test results were used as the inputs. The conditional 10%, 25%, 50%, 75%, and 90% quantile functions of the maximum DS and DS change of the three vessels were estimated using the BQR model.ResultsThe 90th percentiles of the DS of the three vessels and their maximum DS change were 41%-50% and 5.6%-7.3%, respectively. Typical anginal symptoms were associated with the highest quantile (90%) of DS in the LAD; diabetes with higher quantiles (75% and 90%) of DS in the LCx; dyslipidemia with the highest quantile (90%) of DS in the RCA; and shortness of breath showed some association with the LCx and RCA. Interestingly, High-density lipoprotein cholesterol showed a dynamic association along DS change in the per-patient analysis.ConclusionsThis study demonstrates the clinical utility of the BQR model for evaluating the comprehensive relationship between risk factors and baseline-grade CAD and its progression.
- Published
- 2023