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Construction of Risk Prediction Model for Alzheimer’s Disease Based on Meta-Analysis

DOI: 10.4236/oalib.1105731, PP. 1-10

Keywords: Alzheimer’s Disease, Risk Prediction Model, Risk Factors, Logistic Regression, Meta-Analysis

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Abstract:

Objective: Construction of risk prediction model for Alzheimer’s disease based on Meta-analysis. Method: Documenting such as CNKI, WanFang database and VIP database, which were published in China from 2010 to 2018 and had data on risk factors for Alzheimer’s disease. Meta-analysis of standards compliant literature using RevMan5.3 software and then combine the results to obtain a comprehensive risk for each risk factor, the risk prediction model is established based on the natural logarithmic trans-formation value of the comprehensive risk. Result: A total of 28 articles were included in the literature. There are 7 risk factors entering the model through data screening and they were family history of dementia, ApoE, education level, brain trauma, drinking history, family history of dementia and gender and smoking history, a total of 2,229,980 patients were included. Conclusion: Ultimately the model will be used to effectively control risk factors and slow the progression of the disease.

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