Development and validation of a simple model to predict functionally significant coronary artery disease in Chinese populations: A two-center retrospective study
Wen-Qian Shen,
Guo-Qing Du,
Xin Duan,
Yi-Tong Li,
Shuang Chen,
Yu-Ming Huang,
Jun-Qing Yang,
Li-Wen Li,
Jing-Yi Xue,
Jia-Wei Tian
Affiliations
Wen-Qian Shen
Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Ultrasound Molecular Imaging Joint Laboratory of Heilongjiang Province, Harbin, China
Guo-Qing Du
Department of Ultrasound, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
Xin Duan
Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Ultrasound Molecular Imaging Joint Laboratory of Heilongjiang Province, Harbin, China
Yi-Tong Li
Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Ultrasound Molecular Imaging Joint Laboratory of Heilongjiang Province, Harbin, China
Shuang Chen
Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Ultrasound Molecular Imaging Joint Laboratory of Heilongjiang Province, Harbin, China
Yu-Ming Huang
Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences) Southern Medical University, Guangzhou, China
Jun-Qing Yang
Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences) Southern Medical University, Guangzhou, China
Li-Wen Li
Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences) Southern Medical University, Guangzhou, China
Jing-Yi Xue
Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences) Southern Medical University, Guangzhou, China; Corresponding author. Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences) Southern Medical University, Guangzhou, 510030, China.
Jia-Wei Tian
Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Ultrasound Molecular Imaging Joint Laboratory of Heilongjiang Province, Harbin, China; Corresponding author. Department of Ultrasound, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150086, China.
Objectives: This study sought to derive and validate a simple model combining traditional clinical risk factors with biomarkers and imaging indicators easily obtained from routine preoperative examinations to predict functionally significant coronary artery disease (CAD) in Chinese populations. Methods: We developed five models from a derivation cohort of 320 patients retrospective collected. In the derivation cohort, we assessed each model discrimination using the area under the receiver operating characteristic curve (AUC), reclassification using the integrated discrimination improvement (IDI) and net reclassification improvement (NRI), calibration using the Hosmer-Lemeshow test, and clinical benefit using decision curve analysis (DCA) to derive the optimal model. The optimal model was internally validated by bootstrapping, and external validation was performed in another cohort including 96 patients. Results: The optimal model including 5 predictors (age, sex, hyperlipidemia, hs-cTnI and LVEF) achieved an AUC of 0.807 with positive NRI and IDI in the derivation cohort. Moreover, the Hosmer-Lemeshow test showed a good fit, and the DCA demonstrated good clinical net benefit. The C-statistic calculated by bootstrapping internal validation was 0.798, and the calibration curve showed adequate calibration (Brier score = 0.179). In the external validation cohort, the optimal model performance was acceptable (AUC = 0.704; Brier score = 0.20). Finally, a nomogram based on this model was constructed to facilitate its use in clinical practice. Conclusions: A simple model combined clinical risk factors with hs-cTnI and LVEF improving the prediction of functionally significant CAD in Chinese populations. This attractive model may be a choice for clinicians to risk stratification for CAD.
