Effect of Hierarchical Classification Intervention on High-risk Population of Stroke
Objective To explore the effect of hierarchical classification intervention on the risk of stroke in community residents.Methods The stratified random sampling method was used to recruit volunteers from the physical examination population in a street in Shanghai from September 2020 to September 2021.According to the method of random grouping,the volunteers were divided into the experimental group and the control group,with 300 people in each group,and different intervention measures were taken for a one-year intervention,and the relevant information was collected through the baseline questionnaire and the Chinese cardiovascular disease risk prediction model.Results The high risk rate of stroke in 600 residents for 10 years before intervention was 12.33％,the lifetime high risk rate of morbidity was 11.03％.After intervention,the 10-year risk of stroke was 4.42 scores and the life-long risk of stroke was 16.33 scores in the experimental group,which were slightly lower than the average score before intervention(P＜0.05).After intervention,the 10-year risk reduction in the experimental group was 0.37,which was better than 0.25 in the control group,and the life-long risk reduction was 2.27,which was better than 2.01 in the control group by(P＜0.05).Conclusion The hierarchical classification management of high-risk population of stroke is superior to the current intervention measures in reducing the 10-year risk of stroke and the lifetime risk of stroke in residents.
StrokeRisk of morbidityHierarchical classification managementIntervention measures
万方数据
维普
