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The Mini‐Mental State Examination: Identifying the Most Efficient Variables for Detecting Cognitive Impairment in the Elderly
Author(s) -
Braekhus Anne,
Laake Knut,
Engedal Knut
Publication year - 1992
Publication title -
journal of the american geriatrics society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.992
H-Index - 232
eISSN - 1532-5415
pISSN - 0002-8614
DOI - 10.1111/j.1532-5415.1992.tb01804.x
Subject(s) - medicine , logistic regression , univariate , cognitive impairment , mini–mental state examination , univariate analysis , recall , multinomial logistic regression , cognition , statistics , mathematics , multivariate analysis , psychiatry , psychology , multivariate statistics , cognitive psychology
Objectives To study how well the scoring on each item of the MMSE relates to the sum‐score when the purpose is to identify persons with cognitive impairment, and to identify an equally effective subset of MMSE items for predicting cognitive impairment. Design Retrospective survey of MMSE data for 850 elderly. Setting: A variety of clinical settings. Participants Mean age 82 years (range 54 to 99), 74% women. The subjects were of three different categories: geriatric in‐patients, patients living under supervision, and elderly people living independently at home. Results Five of the binomial (“State,” “Town,” “Name a pencil,” “Name a watch,” “Read and obey”) and one of the polychotomous MMSE variables (“Learn three words and repeat immediately”) had low sensitivity and gave high percentages of misclassifications versus the sumscore dichotomized at the cut‐point 23/24. Univariate logistic regression indicated that the three remaining polychotomous variables (“Spell backwards,” “Recall three words,” and “Three‐stage command”) can be scored binomially. Two factors were identified on factor analysis. Logistic regression analysis showed that 12 of the original 20 items predicted the sumscore dichotomized at 23/24 with only 3% misclassifications. Validation against the psychogeriatrician's diagnosis showed that this 12‐item MMSE derivative performs as well as the full MMSE. Conclusions Six of the 20 MMSE variables perform poorly regarding sensitivity and misclassifications versus the sum‐score at cut‐point 23/24. Two additional items did not contribute to the prediction of a low/high sumscore. The remaining 12 MMSE items can all be scored binomially and produce a sumscore which is equally as effective as the sumscore of the full MMSE when the purpose is to identify elderly patients with cognitive impairment.