Abstract
BACKGROUND: We aimed to explore the benefits of the "Digital and Intelligent Patient-centered Integration of Treatment and Prevention for Cardiovascular Diseases in the Community" (DITP), which is a new model for managing cardiovascular disease risk factors in high-risk elderly stroke patients. METHODS: A total of 338 elderly high-risk stroke patients were included and subjected to a 6-month self-controlled DITP study. RESULTS: The five chronic diseases with the highest prevalence rates were hypertension (89.94%), dyslipidemia (73.37%), overweight (65.70%), diabetes (52.96%), and atrial fibrillation/valvular heart disease (2.07%). Moreover, 86.7% of patients had two or more simultaneous chronic diseases, and 27.22% had a history of smoking. After 6 months of intervention, (1) with respect to the control of multiple risk factors, there were improvements in blood pressure and blood lipid compliance rates. The blood glucose compliance rate (50.30% preintervention vs. 62.43% postintervention) and the optimal risk factor control rate (3.85% preintervention vs. 8.88% postintervention) were significantly improved (P < 0.05). (2) Regarding physiological indicators, fasting blood glucose (7.44 ± 2.37 mmol/L preintervention vs. 6.99 ± 2.15 mmol/L postintervention), cholesterol (5.56 ± 1.3 mmol/L preintervention vs. 5.20 ± 1.22 mmol/L postintervention), and low-density lipoprotein cholesterol levels significantly decreased (P < 0.05). (3) The proportions of patients with good medication adherence scores for hypoglycemic (6.76 ± 1.76 preintervention vs. 7.19 ± 1.24 postintervention), lipid-lowering (6.80% preintervention vs. 15.09% postintervention), and antiplatelet (4.73% preintervention vs. 7.69% postintervention) drugs significantly increased (P < 0.05). (4) The activation score and the proportion of the highest activation level significantly improved (P < 0.05). (5) Regarding major adverse cardiovascular events, 2 (0.59%) and 13 (3.85%) patients experienced myocardial infarction and cerebral vascular ischemia events, respectively. (6) Univariate analysis revealed that employment status, per capita monthly family income, hypertension status, diabetes status, family history of stroke, and hypoglycemic and lipid-lowering treatment had significant effects on the optimal risk factor control rate (P < 0.05). Multivariate logistic regression analysis revealed that employment status, nondiabetes status, a family history of stroke, and receiving lipid-lowering treatment were associated with better control. CONCLUSION: This DITP model will help actively improve the health of elderly high-risk stroke patients in the long term and should be further applied and promoted in primary healthcare in the future.