It’s Time to Add Electrocardiography and Echocardiography to CVD Risk Prediction Models: Results from a Prospective Cohort Study
In: Risk Management and Healthcare Policy, 2021-11-15
Online
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Zugriff:
Zhao Li,1 Yiqing Yang,1 Liqiang Zheng,2 Guozhe Sun,1 Xiaofan Guo,1 Yingxian Sun1 1Department of Cardiology, The First Hospital of China Medical University, Shenyang, 110001, Peopleâs Republic of China; 2Department of Clinical Epidemiology, Library, Department of Health Policy and Hospital Management, Shengjing Hospital of China Medical University, Shenyang, 110004, Peopleâs Republic of ChinaCorrespondence: Yiqing Yang; Yingxian Sun Tel +86 24 83282688Fax +86 24 83282346Email yangyiqing0725@163.com; yingxiansun123@163.comObjective: To develop and validate a new prediction model for the general population based on a large panel of both traditional and novel factors in cardiovascular disease (CVD).Design and Setting: We used a prospective cohort in the Northeast China Rural Cardiovascular Health Study (NCRCHS).Participants: A total of 11,956 participants aged ⥠35 years were recruited between 2012 and 2013, using a multistage, randomly stratified, cluster-sampling scheme. In 2015 and 2017, the participants were invited to join the follow-up study for incident cardiovascular events. The loss to follow-up number was 351. At the studyâs end, we obtained the CVD outcome events for 10,349 participants.Primary and Secondary Outcome Measures: The prediction model was developed using demographic factors, blood biochemical indicators, electrocardiographic (ECG) characteristics, and echocardiography indicators collected at baseline (Model 1). Framingham-related variables, namely age, sex, smoking, total and high-density lipoprotein cholesterol and diabetes status were used to construct the traditional model (Model 2).Results: For the observed population (n = 10,349), the median follow-up time was 4.66 years. The total incidence of CVD was 1.1%/year, including stroke (n = 342) and coronary heart disease (n = 175). The results of Model 1 indicated that in addition to the traditional risk factors, QT interval (p < 0.001), aortic root diameter (p < 0.001), and ventricular septal thickness (p < 0.001) were predictive factors for CVD. Decision curve analysis (DCA) showed that the net benefit with Model 1 was higher than that of Model 2.Conclusion: QT interval from electrocardiography and aortic root diameter and ventricular septal thickness from echocardiography should be included in the CVD risk prediction models.Keywords: CVD, predictive model, general cohort, QT interval, aortic root diameter, ventricular septal thickness
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It’s Time to Add Electrocardiography and Echocardiography to CVD Risk Prediction Models: Results from a Prospective Cohort Study
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Autor/in / Beteiligte Person: | Li, Zhao ; Guo, Xiaofan ; Yang, Yiqing ; Sun, Guozhe ; Sun, Yingxian ; Zheng, Liqiang |
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Zeitschrift: | Risk Management and Healthcare Policy, 2021-11-15 |
Veröffentlichung: | Dove Press, 2021 |
Medientyp: | unknown |
ISSN: | 1179-1594 (print) ; 8328-2688 (print) |
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