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Risk factor combination for predicting dementia risk and dementia risk score prediction model constructed by risk factor combination

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  • Title:
    Risk factor combination for predicting dementia risk and dementia risk score prediction model constructed by risk factor combination
  • Author: REN LINA ; WANG YONGJUN ; DAI XIJIAN ; LIU BIXIA
  • Subjects: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA ; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS ; PHYSICS
  • Description: The invention discloses a risk factor combination for predicting a dementia risk and a dementia risk score prediction model constructed by the risk factor combination. According to the risk factor combination and the dementia risk score prediction model, an optimal potential predictive factor is screened out by using minimum absolute contraction and selection operator (LASSO) regression and forward and backward step-by-step multivariable Cox regression, and an optimal risk prediction model is developed. The risk scoring model developed by the invention is used for performing individual prediction on the dementia risk in the next five years, nine years and thirteenth years, individuals can be divided into different dementia risk grades, and the model has a good clinical application prospect. 本发明公开了一种预测痴呆风险的风险因素组合及其构建而成的痴呆风险评分预测模型。本发明使用最小绝对收缩和选择算子(LASSO)回归和前向和后向逐步多变量Cox回归来筛选出最佳潜在预测因子，并开发出最佳风险预测模型。本申请开发的风险评分模型，用于对未来5年、9年和13年的痴呆风险进行个体预测，可将个体分为不同的痴呆风险等级，具有良好的临床应用前景。
  • Creation Date: 2022
  • Language: Chinese;English
  • Source: esp@cenet
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