Risk prediction model analysis of depression in elderly patients with cardiovascular disease
10.3969/j.issn.1006-2483.2022.06.034
- VernacularTitle:老年心血管疾病患者发生抑郁症的风险预测模型分析
- Author:
Xiao-bo LIAO
1
;
Peng XIAO
1
Author Information
1. Department of Cardiovascular Medicine , Chongqing Fuling Central Hospital , Chongqing 408000 , China
- Publication Type:Journal Article
- Keywords:
Community elderly cardiovascular disease;
Depressive symptoms;
Risk assessment
- From:
Journal of Public Health and Preventive Medicine
2022;33(6):144-147
- CountryChina
- Language:Chinese
-
Abstract:
Objective To analyze the risk of depression in elderly patients with cardiovascular disease in community, and to provide evidence for the prevention and treatment of depression in elderly patients with cardiovascular disease in community. Methods A total of 486 elderly community patients with cardiovascular disease who were treated in Fuling Central Hospital of Chongqing from August 2019 to August 2020 were selected. The depression status of the patients was assessed by GES-D scale. According to GES-D score, the patients were divided into depression group (GES-D score ≥16 points, n=91) and control group (GES-D score <16 points, n=395). Age, gender, cardiovascular disease and marital status of patients were collected. Logistic regression was used to analyze the possible influencing factors of depression in elderly patients with cardiovascular disease. The statistical clinical data were included in the multivariate logistic regression analysis, and the logistic regression model was established. According to the regression results, the risk prediction model of depression in elderly patients with cardiovascular disease in community was established. The ROC curve was used to predict the effectiveness of the model. Results Among 486 elderly patients with cardiovascular disease in community, 91 patients with cardiovascular disease were complicated with depression, and there was statistical significance in the incidence of depressive symptoms among different elderly patients with cardiovascular disease (P < 0.05). The incidence of CHD with depressive symptoms was significantly higher than that of hypertension, hyperlipidemia and arrhythmia (P < 0.05). The incidence of depressive symptoms in female patients was higher than that in male patients (P < 0.05). There were statistically significant differences between the two groups in gender, education level, drinking history, smoking history, sleep status, daily living ability and number of cardiovascular diseases (P < 0.05). Female, more than 3 kinds of cardiovascular disease, poor ability of daily living, and sleep disturbance were independent risk factors for depression in elderly community cardiovascular disease patients (P < 0.05). The risk prediction model of depression in elderly patients with cardiovascular disease in community was P=[1+e-(-0.471+0.482×（female）＋0.839×(combined cardiovascular disease species > 3)＋0.839×(sleep disorders)＋0.839×(daily life ability difference)］; ROC curve was used to analyze the predictive performance of the regression model. The results showed that the AUC of the community elderly cardiovascular disease risk prediction model to predict depression was 0.739, 95%CL (0.672 - 0.813). Conclusion The incidence of depressive symptoms in elderly community patients with cardiovascular disease is higher, and the risk of depression in elderly community patients with cardiovascular disease is higher in women, with more than 3 types of cardiovascular disease, poor daily living ability, and sleep disturbance. Therefore, attention should be paid to the depressive symptoms of patients, so as to facilitate early diagnosis and treatment.
