Journal of Alzheimer’s Disease 43 (2015) 1403–1412 DOI 10.3233/JAD-141278 IOS Press

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Optimal Cutoff Scores for Dementia and Mild Cognitive Impairment of the Montreal Cognitive Assessment among Elderly and Oldest-Old Chinese Population Ji-ping Tana,1 , Nan Lib,1 , Jing Gaoc,∗ , Lu-ning Wanga,∗ , Yi-ming Zhaob , Bao-cheng Yud , Wei Due , Wen-jun Zhangf , Lian-qi Cuig , Qing-song Wangh , Jian-jun Lii , Jin-sheng Yangj , Jian-min Yuk , Xiang-nan Xial and Pei-yi Zhoum a Department

of Geriatric Neurology, Chinese PLA General Hospital, Beijing, P.R. China Center of Clinical Epidemiology, Peking University Third Hospital, Beijing, P.R. China c Department of Neurology, Peking Union Medical College Hospital, Beijing, P.R. China d Department of Gerontology, Bethune International Peace Hospital, Shijiazhuang, P.R. China e Department of Neurology, Chinese PLA 201 Hospital, Dalian, P.R. China f Department of Gerontology, Changhai Hospital, Shanghai, P.R. China g Department of Neurology, Chinese PLA 401 Hospital, Qingdao, P.R. China h Department of Neurology, General Hospital of Chengdu Military Command, Chengdu, P.R. China i Department of Neurology, Chinese PLA 323 Hospital, Xi’an, P.R. China j Department of Neurology, General Hospital of Lanzhou Military Command, Lanzhou, P.R. China k Department of Neurology, Chinese PLA 107 Hospital, Yantai, P.R. China l First Cadre Department, Fuzhou General Hospital of Nanjing Military Command, Fuzhou, P.R. China m Forth Cadre Department, General Hospital of Guangzhou Military Command, Guangzhou, P.R. China b Research

Accepted 1 August 2014

Abstract. Background: All versions of the Montreal Cognitive Assessment (MoCA) lack population-based data of 80-plus individuals. The norms and cut-off scores for mild cognitive impairment (MCI) and dementia of the MoCA are different among five Chinese versions. Objective: To provide the cut-off scores in detecting MCI and dementia of the Peking Medical Union College Hospital version of the MoCA (MoCA-P). Methods: In a cross-sectional survey, Chinese veterans aged ≥60 years completed the MoCA-P and the Mini-Mental State Examination (MMSE).

1 These

authors contributed equally to this manuscript. to: Jing Gao, Department of Neurology, Peking Union Medical College Hospital, No.1 Shuaifuyuan Wangfujing, Dongcheng District, Beijing 100730, P.R. China. Tel.: +86 10 69156371; Fax: +86 10 69156371; E-mail: [email protected]; Lu-ning Wang, Department of Geriatric Neurology, Chinese PLA General Hospital, 28 Fuxing road, Haidian District, Beijing 100853, P.R. China. Tel.: +86 10 66876268; Fax: +86 10 68229325; E-mail: lnw [email protected]. ∗ Correspondence

ISSN 1387-2877/15/$27.50 © 2015 – IOS Press and the authors. All rights reserved

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Results: Among 7,445 elderly veterans, 5,085 (68.30%) were aged ≥80 years old, 2,621 (35.20%) had 6 years of education or less, 6,847 (91.97%) were male, and 2,311 (31.04%) and 984 (13.22%) veterans were diagnosed as having MCI and dementia, respectively. Adding two points and one point to the MoCA scores for the primary and middle school groups, respectively, can fully adjust for the notable impact of education but cannot compensate for the effect of age. In the three age groups (60–79, 80–89, and ≥90 years old), the optimal MoCA-P cut-off scores for detecting MCI were ≤25, ≤24, and ≤23, respectively, and for detecting dementia were ≤24, ≤21, and ≤19, respectively, which demonstrated relatively high sensitivities and specificities. The areas under the curves for the MoCA-P for detecting MCI and dementia (0.937 and 0.908, respectively) were greater than those for the MMSE (0.848 and 0.892, respectively). Conclusion: Compared with the MMSE, the MoCA-P is significantly better for detecting MCI in the elderly, particularly in the oldest old population, and it also displays more effectiveness in detecting dementia. Keywords: Dementia, elderly, mild cognitive impairment, Mini-Mental State Examination, Montreal Cognitive Assessment, oldest old

INTRODUCTION The Montreal Cognitive Assessment (MoCA) has been widely accepted and utilized as an effective screening tool for the detection of mild cognitive impairment (MCI) and early dementia [1, 2]. There are five Chinese versions of MoCA, and the modifications of the original English version are not consistent between these Chinese versions [3]. Previous studies have demonstrated that merely “adding one point” cannot completely adjust the MoCA scores for the notable impact of education [4, 5] due to the relatively low educational level of Chinese elderly population (the average level of education is only 4.65 years) [6]. Moreover, some items such as naming, delayed recall, and sentence repetition task in the Chinese versions of MoCA may need further modifications, because literally translating these items from the original English version without any culture-specific adaptations could increase its difficulty for Chinese elderly, thus leading to low internal consistency [4, 5]. Since sample size and important demographic characteristics including age, gender, and education were various among different researches, the norms and cut-off scores for the Chinese versions are not only different among the different versions [4, 7–11], but also among different studies in the same version [4, 12]. Furthermore, different MCI diagnostic criteria and neuropsychological batteries applied in different researches, as well as the threshold to define abnormality in cognitive tests resulted in various measured MCI rates, and thus led to conflicting results of the validity and reliability of short screening cognitive tests such as the MoCA and the Mini-Mental State Examination (MMSE) [13]. Concerning the comparison between the Beijing version of the MoCA (MoCA-BJ) and the MMSE in screening MCI, for example, the study conducted by Yu et al. indicated that MoCA-BJ may not be better than the

Chinese version of MMSE [4], whereas another study conducted by Hu et al. displayed an opposite result, partly because in the latter one, the neuropsychological batteries adopted to diagnose MCI were more comprehensive and the cut-off level for memory impairment of MCI was less stringent—1.5 standard deviation (SD) below the mean for education-matched groups [14]. In addition, all of the versions in different languages of the MoCA lack population-based data of the elderly aged ≥80 years [1, 4, 5, 7–12, 15]. Therefore, with the permission of the author of the original English version, researchers from the Department of Neurology, Peking Union Medical College Hospital (PUMCH), modified the original version based on Chinese cultural and linguistic characteristics and created a revised Chinese version of the MoCA (the PUMCH version of the MoCA, MoCA-P). Additionally, using detailed clinical data from long-term follow-ups of elderly Chinese veterans, we evaluated the application of MoCA-P in elderly veterans to establish the norm for the MoCA-P in the elderly and the oldest old (≥80 years old) populations and to identify the optimal cut-off scores for MCI and dementia. MATERIALS AND METHODS Modifications of the MoCA-P The structure of the original English version was retained: 8 cognitive domains were assessed with 11 sub-items, including attention, concentration, executive functions, memory, language, visuoconstructional skills, conceptual thinking, calculations, and orientation [1–3]. The items that were expected to be remarkably affected by culture and language were modified based on Chinese cultural and linguistic characteristics. These items were as follows: (1) The English alphabet letters “A-E” were replaced with

J.-P. Tan et al. / Cutoff Scores of Montreal Cognitive Assessment

the Chinese nominal sequential words “Jia-Wu” in the alternating trail-making test; (2) “Rhinoceros” is rarely seen in China and the naming task with a picture of “rhinoceros” of Chinese version showed a low internal consistency [4]. Therefore, the picture of a “rhinoceros” in the naming domain was replaced with “buffalo”, which is more familiar to Chinese people; (3) In the English version, of the five words in the memory domain, “red”, “face”, and “church” are high-frequency words, while “velvet” and “daisy” are low-frequency words. Unfamiliarity with the words “church”, “velvet”, and “daisy” by Chinese elderly caused low scores in delayed recall task of MoCAChinese version [4], so these words were replaced with “hotel (high-frequency word in Chinese)” and “silk” and “chrysanthemum (low-frequency words in Chinese)”, while the words “red” and “face”, also high-frequency in Chinese, were retained; (4) The English alphabet letters in the vigilance test in the attention domain were replaced with Arabic numerals. For example, “Clap hands when you hear A” was revised as “Knock on the table when you hear one”; (5) Previous study showed that the literal translation of sentences from the original version resulted in awkward Chinese sentence structure [4, 5], which makes the sentence repetition task so difficult that only twenty percent of the study population could successfully repeat it [4]. Therefore, these sentences were replaced by two sentences from the Aphasia Battery of Chinese (ABC) developed by Peking University First Hospital. The normative value for repetition of the ABC was available and used as the diagnostic criterion for repetition impairment in MoCA-P [16]; (6) An animal category fluency task was used in place of the phonemic letter fluency task in verbal fluency, and the reference values from the different age groups were used as the diagnostic criteria [17]; (7) The sub-item scores and the total score of the MoCA-P were recorded. The modification for education level in the English version, namely adding one point for participants with less than 12 years of education, was not adopted in this study. Study areas and sampling This research was accomplished with the help of the Chinese Veteran Clinical Research (CVCR) Platform for the assessment of Non-communicable diseases. Only the study design relevant to this paper is introduced here. Additional details regarding the CVCR Platform design were presented in our previous article [18]. This study conducted a multi-center, twophase, cross-sectional survey using stratified cluster

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sampling because the major demographic characteristics of the veterans in communities, such as age and gender, are similar. The sample size for cities with a centralized distribution of veteran communities is 500 to 1,000 people and 100 to 300 people for those cities with a smaller distribution. The participants were veterans aged ≥60 years who had lived in veteran communities for more than one month and worked in the army system before retirement. The investigators were uniformly trained and qualified medical staff from the departments of neurology and geriatrics. The study began after the research protocol was approved by the Institutional Review Board of the Chinese People’s Liberation Army General Hospital and after written informed consent was obtained from all of the participants or their legal representatives. The survey was conducted in the following 18 cities: Beijing, Shanghai, Guangzhou, Tianjin, Qingdao, Dalian, Fuzhou, Shijiazhuang, Yantai, Baoding, Wuhan, Xi’an, Chengdu, Harbin, Lanzhou, Taiyuan, Hohhot, and Guiyang, where 277 veteran communities were selected and 9,676 Chinese veterans meeting the inclusion criteria were recruited into the CVCR Platform. Diagnostic procedures All participants were screened with the Chinese version of the MMSE [19] and the MoCA-P. A systematic neuropsychological battery was performed to assess memory, language, visuospatial perception, calculation, abstract reasoning, and executive function. The neuropsychological instruments included paired associate word learning of The Clinical Memory Test [20], episodic memory of modified Wechsler Memory Scale [21], category verbal fluency [17, 22, 23], the Clock Drawing Test [24, 25], the trail-making test A of Halstead-Reitan neuropsychological battery for adults [26], the symbol-digit modalities test, similarity and calculations of the Wechsler Adult Intelligence Scale [27], and imitation of ABC [16]. We also selected the spontaneous speech, auditory comprehension, repetition, and naming subtests from ABC as language evaluations [16]. Because the number of tests we adopted varies in different cognitive domains, one test scaled below norms in domains of memory, calculation, abstract reasoning reaches the definition of impairment, while in the domains of executive, language, and visuospatial domains, at least two tests scaled below norms is necessary for defining impairment. A 20-item Chinese version of the Activities of Daily Living (ADL), evaluating the personal ADL

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(PADL) and the instrumental ADL (IADL), was used to estimate the functional dependency of the elderly [28]. The Center for Epidemiological Studies Depression Scale [29, 30], the Hachinski Ischemic Score [31, 32], and the Neuropsychiatric Inventory [33–35] were completed to distinguish different dementing disorders. The Global Deterioration Scale (GDS) [34, 36] was used to classify severity of cognitive impairment. All these tests we chosen had been validated in Mandarin language and the normative data for Chinese population is available. Clinical diagnoses were made based on the results of the patient’s history, systematic neuropsychological tests, physical examinations in internal medicine and neurology, head CT or MRI, routine blood tests, examination of hepato-renal function, folic acid and vitamin B12 levels, thyroid function test, and syphilis antibody test. Diagnostic criteria A diagnosis of MCI was made according to the core clinical criteria as recommended by the National Institute on Aging and the Alzheimer’s Association workgroup [37] and included all the following: (i) cognitive decline compared with the participant’s previous level (obtained from the subject or an informant), (ii) impairment in one or more cognitive domains (the cutoff scores of neuropsychological tests were 1.5 SD below norms), (iii) preservation of independence in functional abilities (ADL score 6

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and ≤12 years (middle school group), and >12 years (higher than middle school group) of education. The differences in the MoCA-P total scores were compared before and after the adjustment. After the age factor was controlled with a partial correlation analysis, the coefficient of partial correlation between educational level and the MoCA-P total score was not statistically significant, which verified that adding two points and one point to the MoCA-P total scores for the primary school and the middle school groups, respectively, can fully adjust for the impact of educational level on the MoCA-P score. Previous studies have suggested that using 26 as the cut-off score for MCI, which is recommended by the original MoCA, is not suitable for the Chinese elderly population [4, 7–12]. However, the cut-off scores for MCI and dementia provided by these studies differed remarkably, and the impact of age and educational level were not completely adjusted due to the limitation of the sample size [4, 7–12]. The lack of data for the advanced elderly and community populations also limited the application of the MoCA. This study fully adjusted for the effects of education and gender on the MoCA score based on a large sample of communitydwelling veterans. The optimal cut-off scores for the groups with veterans aged 60–79 years old, 80–89 years old, and ≥90 years old in screening for MCI were identified as ≤25, ≤24, and ≤23, respectively, and the optimal cut-off scores for dementia were ≤24, ≤21, and ≤19, respectively. The cut-off scores for MCI and dementia of the population aged ≥80 years compensates for the shortcomings of previous studies. Some studies indicate that the ability of the MoCABJ to detect MCI is not as good as that of the MMSE [4] and that the specificity is relatively low [39, 40]. However, our study demonstrated not only the excellence of the MoCA-P in detecting MCI and dementia, but also the fact that it has greater ability to detect MCI than to detect dementia, which is in accord with the original purpose of designing it. Furthermore, the ability of the MoCA-P to detect MCI was significantly higher than that of the MMSE. Moreover, the sensitivities of the cut-off scores for MCI and dementia detection in the different age groups were excellent (all >80%), and the specificities were higher than 74%; in particular, the specificity for detecting MCI in individuals ≥80 years old was over 96%. The above data suggest that the MoCA-P has a high level of sensitivity and enhanced specificity. Therefore, the MoCA-P can be utilized as an effective screening instrument for MCI and dementia in the Chinese elderly population, especially among the oldest old.

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The following factors may be related to the discrepancy between our study and previous ones. Firstly, previous studies have indicated that in order to improve the applicability and effectiveness of the MoCA-BJ in MCI screening among the Chinese population, several items of it need further modifications to minimize the impact of linguistic and cultural difference [4, 5]. With the Chinese-specific modifications we made, the MoCA-P displayed improved diagnostic accuracy for detecting MCI and dementia. Secondly, studies have shown that differences in the MCI diagnostic criteria and operational methodology within established criteria of MCI have impact on the measured MCI rates and thus the performance of the MoCA and the MMSE [13]. There is a possibility of missing individuals with subtle cognitive declines or over-diagnosing MCI for those cognitively normal ones, if the diagnosis of MCI only bases on very limited cognitive tests or staging-based rating scales [41]. AUCs were generally higher for the MoCA than the MMSE for detecting MCI where subjective memory complaint was not required, and more stringent cut-offs such as 1.5 or 2 SD below the norms or as multiple-domain impairment for MCI definition usually resulted in higher AUC [13]. The diagnosis of MCI in previous studies was mainly according to the Clinical Dementia Rating (CDR) scale, GDS, and ADL, merely supplemented by limited cognitive tests such as the World Health Organization-University of California Los Angeles Auditory Verbal Learning test [12] or even nothing [4]. However, in our study, we diagnosed MCI on the basis of comprehensive neuropsychological tests covering cognitive domains of memory, language, visuospatial perception, calculation, abstract reasoning, and executive function, and in order to avoid missed diagnosis, we also set a relatively strict threshold (1.5SD below norms) to define abnormality in each test. These differences contributed to the higher measured rate of MCI in our study (31.04%) than previous ones (11.5%, 20.06%) and the better performance of the MoCA-P in detecting MCI and dementia than the MoCA-BJ [4, 12]. Finally, the MoCA score was significantly influenced by the education level of study samples [4, 5, 7–12, 15]. The MoCA-BJ was found to be slightly more sensitive in screening MCI than the MMSE in a sub-sample with higher education [4]. In addition, the decreased cut-off scores for the Chinese elderly with low education can improve the sensitivity and specificity of the MoCA-BJ for detecting MCI and dementia [12]. The relatively high education level of veterans and thorough adjustment to the significant effect of

educational level on the MoCA-P score in our study may also be a reason for the better diagnostic ability of MoCA-P than that of the MoCA-BJ. The limitations of this study should be considered when using the MoCA-P. The research data were based on urban, community-dwelling veterans, and data from the rural elderly population and ethnic minority groups are lacking. Future studies should focus on participants from rural and urban communities, different ethnic minority groups and different dialect areas to fully validate the application of the MoCA-P in clinical settings. ACKNOWLEDGMENTS This study was supported by Special Research Project on Health Care, Health Sector of the General Logistics Department of People’s Liberation Army (Project Number: 07BJZ04; 10BJZ19; 11BJZ09; 12BJZ46); The national science and technology support program (Project Number: 2013BAI09B14). We are grateful for the support and help of Dr. Ziad S. Nasreddine to this study. Medical staff from all of the participating hospitals contributed to acquisition of data, including staff members from the following: the Neurology Departments of the General Hospital of Lanzhou Military Region, the General Hospital of the Chengdu Region, the Wuhan General Hospital of the Guangzhou Region, the PLA 107, 210, 401, 323, 451, and 211 Hospitals; the Geriatric Department of the Bethune International Peace Hospital and Changhai Hospital, the first Cadre Department of Fuzhou General Hospital of the Nanjing Military Region, the fourth Cadre Department of the General Hospital of the Guangzhou Military Region, the third Cadre Department from the PLA 254 Hospital; the Cadre Department from the Beijing Armed Police General Hospital and the PLA 252 Hospital; the Neurology Department and the Cadre Department from the PLA 253 and 264 Hospitals; and the third Internal Medical Department of the PLA 44 Hospital. Authors’ disclosures available online (http://www.jalz.com/disclosures/view.php?id=2483). REFERENCES [1]

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Optimal cutoff scores for dementia and mild cognitive impairment of the Montreal Cognitive Assessment among elderly and oldest-old Chinese population.

All versions of the Montreal Cognitive Assessment (MoCA) lack population-based data of 80-plus individuals. The norms and cut-off scores for mild cogn...
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