How Well Do MCI Criteria Predict Progression to Severe Cognitive Impairment and Dementia?

被引:11
作者
Ganguli, Mary [1 ,2 ,4 ]
Lee, Ching-Wen [1 ]
Snitz, Beth E. [2 ]
Hughes, Tiffany F. [1 ]
McDade, Eric M. [2 ]
Chang, Chung-Chou H. [3 ,5 ]
机构
[1] Univ Pittsburgh, Sch Med, Dept Psychiat, Pittsburgh, PA USA
[2] Univ Pittsburgh, Sch Med, Dept Neurol, Pittsburgh, PA 15261 USA
[3] Univ Pittsburgh, Sch Med, Dept Med, Pittsburgh, PA 15213 USA
[4] Univ Pittsburgh, Grad Sch Publ Hlth, Dept Epidemiol, Pittsburgh, PA USA
[5] Univ Pittsburgh, Grad Sch Publ Hlth, Dept Biostat, Pittsburgh, PA 15261 USA
关键词
mild cognitive impairment; dementia; prediction; Winblad criteria; CART; epidemiology; community; MINI-MENTAL-STATE; ALZHEIMERS-DISEASE; POPULATION; RISK; METAANALYSIS; CONVERSION;
D O I
10.1097/WAD.0000000000000018
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Background: The International Working Group (IWG) criteria for mild cognitive impairment have variable utility in predicting progression to dementia, partly depending on the setting. We explored an empiric approach to optimize the criteria and cutoff points in a population study. Methods: In a cohort of adults aged 65 years or older, we identified 1129 individuals with normal or only mildly impaired cognition by cognitive classification, and 1146 individuals without dementia (Clinical Dementia Rating <1). Operationally defining the IWG criterion set, we examined its sensitivity and specificity for the development of severe cognitive impairment and dementia (Clinical Dementia Rating >= 1) over 4 years. We then disaggregated the criteria and used Classification and Regression Tree analyses to identify the optimal predictive model. Results: The operational IWG criteria had 49% sensitivity and 86% specificity for the outcome of severe cognitive impairment, and 40% sensitivity and 84% specificity for the outcome of dementia. Classification and Regression Tree modeling improved sensitivity to 82% for the cognitive outcome and 76% for the dementia outcome; specificity remained high. Memory scores were the most important predictors for both outcomes. The optimal cutoff points were around 1.0 SD below the age-education mean. The best fit was observed when prediction was modeled separately for each age-education group. Conclusions: Objective cognitive measurements contributed more to the prediction of dementia than subjective and functional measures. Those with less education only required memory testing, whereas those with more education required assessment of several cognitive domains. In cases in which only overall norms are available, the appropriate threshold will vary according to the individual's age and education.
引用
收藏
页码:113 / 121
页数:9
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