1. Diagnostic value of scoring model of treadmill exercise test combined with dynamic electrocardiogram for latent coronary heart disease.
- Author
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Wang W and Zhang Q
- Subjects
- Aged, Coronary Angiography, Electrocardiography, Humans, Risk Factors, Coronary Disease diagnosis, Exercise Test
- Abstract
Objective: To investigate the diagnostic value of scoring model of treadmill exercise test (TET) combined with dynamic electrocardiogram (DECG) for latent coronary heart disease (LCHD)., Materials and Methods: Using coronary angiography, the diagnostic values of TET and DECG alone or combination for LCHD of 200 eligible patients were compared. The effects of different clinical features and DECG indices on the positive detection rate of TET combined with DECG were compared. Multivariate logistic regression analysis was performed for factors influencing diagnostic accuracy, and nomogram prediction model was established using screened independent risk factors., Results: Serial and parallel combinations of TET and DECG had superior sensitivity, specificity, positive and negative predictive values and accuracy than those of single detection. Patients with an age > 65 years, smoking, hypertension, diabetes mellitus, hyperlipidemia, family history of CHD and positive DECG indicators had higher positive detection rate, as independent risk factors for accuracy. The diagnostic accuracy of TET combined with DECG predicted by the nomogram model was 82.9%. The actual concordance index (C-index) for model evaluation was 0.817, the C-index after internal validation was 0.811, and the C-index after external validation was 0.802, indicating a good concordance of the model., Conclusions: TET combined with DECG has high diagnostic accuracy for LCHD, and the scoring model constructed by DECG indicators can prominently improve the accuracy of combined diagnosis. Therefore, TET combined with DECG is significantly better than TET or DECG alone, which is of great diagnostic value for LCHD., Competing Interests: Declaration of Competing Interest None., (Copyright © 2021. Published by Elsevier Inc.)
- Published
- 2021
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