Explore the risk factors for predicting the progressess

 
   Lead Investigator:    Ji Zhaohua
   Institution      :    Fourth Military Medical University
   E-Mail           :    hellojzh@msn.com
   Proposal ID      :    965



   Proposal Description:
   In China, Alzheimer's Disease  is becoming a serious public problem because the   the aging of population. But the long time follow-up corhort studies of           Alzheimer's Disease  were rare and the progression data based on the Chinese      cohort is lacking. The patient's family wanted to know what the patient's         cognition, composite scores and language would be after several years and be      prepared for the situations.                                 We assume that the patient's progress was related to the general                  characteristics of the patient and other disease history in the case of good      care. The patient's general characteristics and other disease information, such   as, Gender, age, education level, presence versus absence of hypertension,        hypercholesterolemia, heart disease, stroke, and family dementia history, and     so on.  The progression included the MMSE, Composite scores and Test language,    and so on.                                                                         We would try some statistic model to predict the progression of Alzheimer's       Disease.  For example, predict the MMSE score of the patient five year later      with the gender, age, education level, presence versus absence of hypertension,   hypercholesterolemia, heart disease, stroke, and family dementia history with     the BP and RBF Neural Network. So the baseline data of the patient (gender,       age, education level, presence versus absence of hypertension,                    hypercholesterolemia, heart disease, stroke, and family dementia history, MMSE    score) and the data of the first year, year 3, year 5, year 20 follow-up MMSE     scores  were preferred.