文章摘要
王玉珍.都匀市1994~1998年冷饮食品监测结果分析[J].中华流行病学杂志,1999,20(5):268
都匀市1994~1998年冷饮食品监测结果分析
Multi-state model in the evaluation of outcome on mild cognitive impairment to Alzheimer's disease
收稿日期:1999-05-21  出版日期:2014-09-18
DOI:
中文关键词: 阿尔茨海默病|轻度认知损害|多状态模型|转归
英文关键词: Alzhcimer's disease|Mild cognitive impairment|Malti—state model|Outcome
基金项目:国家自然科学基金(30972545);山西省留学回国人员科技活动择优项目;山西医科大学科技创新项目
作者单位
王玉珍 贵州省都匀市食品卫生监督检验所,558000 
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中文摘要:
      为切实加强对冷饮食品的卫生管理,防止肠道传染病的发生,我们于1994~1998年对全市冷饮食品进行了抽样监测,结果报告如下。
英文摘要:
      Objective The aim of this study was to introduce the multi—slate Markov modelfor the prediction of mild cognitive impairment(MCI)to AIzheimer’S diseaselAD)and to find out the related factors for AD preventionan dearly in tervention among tile elderly.Methods MCI.moderate to severe cognitive impairment.and AD were defined as state 1.2 and 3,respectively.A three—state homogeneous model with discrete states and discrete times from data six follow—up visits was constructed to explore factors for various progressive stages from MCI to AD.Transition probability and survival curve were madeafter the model fit as sessment.Results At the level of 0.05,data from the multivariate analysis showed that gender(HR=1.23,95%c,:1.12一1.38).age(HR=l.37,95%G/:L071~72), hypertension (HR=1.54,95%C/:1.3一2. 19) were statistically significant for the transition from state I to state 2. while age(HR=O.78,95%C1:0.69—0.98).education level(HR=1.35. 95%Cl:1.09一lr86)and reading(HR=1.20,95%c,:1.01一1.41)were:statistically significant for transition from state 2 to state l,and gander(HR=1.59,95%C/:1.33一1.89), age(HR=1.33,95%C/:1.02-1.64), hypertension(HR=1.22,95%C/:1.1l一1.43).diabetes(HR=1.52,95%CI:1.12—2. 00),ApoEe4(HR=1.44. 95%CI:1.09—1.68)were statistically significant for transition from statc 2 to slate 3.Based 0n the fired modeI,the three-yeart ransition probabilities during each state at average covariate Ievel were estimated.Conclusion To delay the disease progression of MCI.phase by phase prevention measures could be adopted based On the main factors of each stage.Multi-state Markov model could imitate the naturalhistory of disease and showed great advantage in dynamically evaluating the development of chronic diseases with multi-states and multi-factors.
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