Related Experiment Video
Updated: Jul 21, 2025
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Optimal cut-off MoCA score for screening for mild cognitive impairment in elderly individuals in China: A systematic
Rui Sun1, Binqian Ge2, Shiyu Wu1
1International Medical Services, Peking Union Medical College Hospital, Beijing, China.
Aim:
To evaluate the optimal cut-off MoCA score for elderly individuals with MCI.
Design:
A systematic review and meta-analysis.
Method:
Articles were retrieved from PubMed, Ovid, Embase, The Cochrane Library, PsycINFO, CBM, CNKI, WanFang and CQVIP and were assessed by using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). Figures of the assessment were made by using Review Manager 5.3, and a meta-analysis of the data was conducted by using Bivariate Random-effects Meta-Analysis (BRMA) via Stata 14.0.
Results:
Seventeen articles were retrieved from the database, and when the cut-offs were 24/25 and 25/26, they represented the same diagnostic value; in addition, the AUC was 0.96, which demonstrated high predictive validity for mild cognitive impairment screening. However, the sensitivity was higher with 25/26 (se=0.95, sp=0.80), whereas the specificity was higher with 24/25 (se=0.92, sp=0.89).
