Zhongguo quanke yixue (Apr 2024)
A Study on the Factors Influencing the Comprehensive Risk of Cardiovascular Disease in Elderly Patients with Chronic Disease in Primary Care
Abstract
Background Cardiovascular disease is the primary cause of death and Disease burden of Chinese residents, and the situation of prevention and control is grim. Management of risk factors for cardiovascular disease is an important foundation for preventing cardiovascular disease. However, there is currently limited research on the influencing risk factors of cardiovascular disease risk in elderly patients with chronic disease in primary care using single lead wearable electrocardiogram devices both domestically and internationally, and previous studies have not ranked the importance of variables containing different quantities of risk in patients from a holistic perspective. Objective The aim of this study is to analyze the influencing factors of the comprehensive risk of cardiovascular disease in elderly patients with chronic disease aged 65 and above in primary care in Ningxia, and to provide objective basis and assistance for the comprehensive prevention and control of cardiovascular disease in primary care. Methods From December 2021 to September 2022, totally 3 039 patients over 65 years old with hypertension, diabetes and coronary heart disease, including at least one chronic disease, from 26 primary care health center in Ningxia were selected as the research subjects. According to the analysis of the 72 hour electrocardiogram, there were 632 cases in the normal group and 2 407 cases in the risk group. Analyze the basic information of two groups of patients to determine the best λ Value, draw a model, and use LASSO regression and multivariate Logistic regression to analyze the comprehensive risk factors of cardiovascular disease in elderly patients with chronic diseases; and rank the variables that affect the overall risk of cardiovascular disease and include different numbers of risks among patients. Results The differences in age, gender, BMI, education level, occupation, urban-rural distribution, smoking, exercise, coronary heart disease combined with diabetes, hypertension combined with coronary heart disease and diabetes between the two groups of patients were statistically significant (P<0.05) ; optimum λvalue was 0.015 685 31. LASSO regression and multivariate logistic regression model analysis showed that age, BMI, urban-rural distribution, smoking Hypertension combined with coronary heart disease and diabetes is a influencing factor for cardiovascular disease (P<0.05). Auc was 0.650 (95%CI=0.627-0.673, P<0.001) The top five variables that affect comprehensive risk and different types of risk are age, BMI, urban-rural distribution, tea drinking, and exercise; Age, hypertension combined with coronary heart disease, gender, urban-rural distribution, smoking; Age, hypertension combined with coronary heart disease, gender, BMI, urban-rural distribution; Diabetes combined with coronary heart disease, age, hypertension combined with coronary heart disease, hypertension combined with coronary heart disease and diabetes, hypertension combined with diabetes. Conclusion Age, BMI, urban and rural distribution, smoking, hypertension with coronary heart disease and diabetes are the influencing factors of cardiovascular disease risk in patients over 65 years old with chronic diseases. In addition to age, BMI and lifestyle habits have a significant impact on the overall risk of cardiovascular disease. As the number of comorbidities increases, the impact of chronic diseases, especially chronic disease comorbidities, increases. Primary care medical teams should regularly conduct comprehensive CVD risk management for elderly patients with multiple chronic diseases using single lead wearable devices. This not only enables efficient and low-cost implementation of primary and secondary prevention and health management of CVD risks, but also accelerates the transformation of primary medical services from inconsistent diagnosis and treatment services to full process health management.
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