[Principal component analysis and integral methods of cerebral vascular hemodynamic parameters].

OBJECTIVE: To establish a predicting model for stroke according to cerebral vascular hemodynamic indexes and major risk factors of stroke. METHODS: Participants selected from a stroke cohort with 25,355 population in China. The first step was to carry out principal component analysis using CVHI. Logistic regression with principal component and main risk factors of stroke were then served as independent variables and stroke come on as dependent variables. The predictive model was established according to coefficient of regression and probability of each participant was also estimated. Finally, ROC curve was protracted and predictive efficacy was measured. RESULTS: The accumulative contribution rates of four principal components were 58.1%, 79.4%, 88.4% and 94.6% respectively. Seven variables were being selected into the equation with the first to fourth principal component as history of hypertension, age and sex. Area under ROC curve was 0.855 and optimal cut-off point was probability over 0.05. Sensitivity, specificity and accuracy of stroke prediction were 80.7%, 78.5% and 78.5% respectively. CONCLUSION: The model established by principal component and regression could effectively predict the incidence of stroke coming on.

Prevalence of dementia in China.

To obtain prevalence estimates of dementia in China, an analysis of 17 studies published in Chinese from 1990-1999 was carried out. The prevalence rates for the population aged 60 years and older were 1.26% for Alzheimer's disease (AD) and 0.74% for vascular dementia (VD). The prevalence of AD was 2.10% in women and 0.76% in men, while the prevalence of VD was 0.71 and 0.69%, respectively. The prevalence of AD among the three educational levels in our study (illiterate, primary school and high school) were 1.79, 0.45 and 0.15%, respectively, and those of VD were 0.26, 0.58 and 0.26%, respectively. Although the prevalence of AD (2.29%) was higher in urban than in rural areas (1.67%), the difference was not statistically significant. The difference between the prevalence of VD in urban (0.67%) and in rural areas (1.13%) was not significant either. The prevalence of AD increased with age, and gender was found to be associated with Alzheimer's disease. The prevalence of VD also increased with age, but there was no association between VD and gender.