MoCA in five Indian languages: A brief screening tool to diagnose dementia and MCI in a linguistically diverse setting.

INTRODUCTION AND OBJECTIVES: Early dementia diagnosis in low and middle-income countries (LMIC) is challenging due to limited availability of brief, culturally appropriate, and psychometrically validated tests. Montreal Cognitive Assessment (MoCA) is one of the most widely used cognitive screening tests in primary and secondary care globally. In the current study, we adapted and validated MoCA in five Indian languages (Hindi, Bengali, Telugu, Kannada, and Malayalam) and determined the optimal cut-off points that correspond to screening for clinical diagnosis of dementia and MCI. METHODS: A systematic process of adaptation and modifications of MoCA was fulfilled. A total of 446 participants: 214 controls, 102 dementia, and 130 MCI were recruited across six centers. RESULTS: Across five languages, the area under the curve for diagnosis of dementia varied from 0.89 to 0.98 and MCI varied from 0.73 to 0.96. The sensitivity, specificity and optimum cut-off scores were established separately for five Indian languages. CONCLUSIONS: The Indian adapted MoCA is standardized and validated in five Indian languages for early diagnosis of dementia and MCI in a linguistically and culturally diverse population.

Picture-naming test for a linguistically diverse population with cognitive impairment and dementia.

BACKGROUND: Picture-naming tests (PNTs) evaluate linguistic impairment in dementia due to semantic memory impairment, impaired lexical retrieval or perceptual deficits. They also assess the decline in naming impairment at various stages of dementia and mild cognitive impairment (MCI) that occurs due to progressive cognitive impairment. With the increasing numbers of people with dementia globally, it is necessary to have validated naming tests and norms that are culturally and linguistically appropriate. AIMS: In this cross-sectional study we harmonized a set of 30 images applicable to the Indian context across five languages and investigated the picture-naming performance in patients with MCI and dementia. METHODS & PROCEDURES: A multidisciplinary expert group formed by the Indian Council of Medical Research (ICMR) collaborated towards developing and adapting a picture naming test (PNT) known as the ICMR-PNT in five Indian languages: Hindi, Bengali, Telugu, Kannada and Malayalam. Based on cross-cultural adaptation guidelines and item-wise factor analysis and correlations established separately across five languages, the final version of the ICMR-PNT test was developed. A total of 368 controls, 123 dementia and 128 MCI patients were recruited for the study. Psychometric properties of the adapted version of the ICMR-PNT were examined, and sensitivity and specificity were examined. OUTCOMES & RESULTS: The ICMR-PNT scores in all languages combined were higher in controls compared with patients with dementia and MCI (F2, 615 = 139.85; p < 0.001). Furthermore, PNT scores for MCI was higher in comparison with patients with dementia in all languages combined (p < 0.001). The area under the curve across the five languages ranged from 0.81 to 1.00 for detecting dementia. There was a negative correlation between Clinical Dementia Rating (CDR) and ICMR-PNT scores and a positive correlation between Addenbrooke's Cognitive Examination-III (ACE-III) and ICMR-PNT scores in control and patient groups. CONCLUSIONS & IMPLICATIONS: The ICMR-PNT was developed by following cross-cultural adaptation guidelines and establishing correlations using item-wise factor analysis across five languages. This adapted PNT was found to be a reliable tool when assessing naming abilities effectively in mild to moderate dementia in a linguistically diverse context. WHAT THIS PAPER ADDS: What is already known on this subject Picture-naming evaluates language impairment linked to naming difficulties due to semantic memory, lexical retrieval or perceptual disturbances. As a result, picture naming tests (PNTs) play an important role in the diagnosis of dementia. In a heterogeneous population such as India, there is a need for a common PNT that can be used across the wide range of languages. What this study adds to existing knowledge PNTs such as the Boston Naming Test (BNT) were developed for the educated, mostly English-speaking, Western populations and are not appropriate for use in an Indian context. To overcome this challenge, a PNT was harmonized in five Indian languages (Hindi, Bengali, Telugu, Kannada and Malayalam) and we report the patterns of naming difficulty in patients with MCI and dementia. The ICMR-PNT demonstrated good diagnostic accuracy when distinguishing patients with mild to moderate dementia from cognitively normal individuals. What are the potential or actual clinical implications of this work? With the growing number of persons suffering from Alzheimer's disease and other forms of dementia around the world, its critical to have culturally and linguistically relevant naming tests and diagnosis. This validated ICMR-PNT can be used widely as a clinical tool to diagnose dementia and harmonize research efforts across diverse populations.

Validation of Indian Council of Medical Research Neurocognitive Tool Box in Diagnosis of Mild Cognitive Impairment in India: Lessons from a Harmonization Process in a Linguistically Diverse Society.

BACKGROUND/AIMS: In a linguistically diverse country such as India, challenges remain with regard to diagnosis of early cognitive decline among the elderly, with no prior attempts made to simultaneously validate a comprehensive battery of tests across domains in multiple languages. This study aimed to determine the utility of the Indian Council of Medical Research-Neurocognitive Tool Box (ICMR-NCTB) in the diagnosis of mild cognitive impairment (MCI) and its vascular subtype (VaMCI) in 5 Indian languages. METHODS: Literate subjects from 5 centers across the country were recruited using a uniform process, and all subjects were classified based on clinical evaluations and a gold standard test protocol into normal cognition, MCI, and VaMCI. Following adaptation and harmonization of the ICMR-NCTB across 5 different Indian languages into a composite Z score, its test performance against standards, including sensitivity and specificity of the instrument as well as of its subcomponents in diagnosis of MCI, was evaluated in age and education unmatched and matched groups. RESULTS: Variability in sensitivity-specificity estimates was noted between languages when a total of 991 controls and 205 patients with MCI (157 MCI and 48 VaMCI) were compared due to a significant impact of age, education, and language. Data from a total of 506 controls, 144 patients with MCI, and 46 patients with VaMCI who were age- and education-matched were compared. Post hoc analysis after correction for multiple comparisons revealed better performance in controls relative to all-cause MCI. An optimum composite Z-score of -0.541 achieved a sensitivity of 81.1% and a specificity of 88.8% for diagnosis of all-cause MCI, with a high specificity for diagnosis of VaMCI. Using combinations of multiple-domain 2 test subcomponents retained a sensitivity and specificity of >80% for diagnosis of MCI. CONCLUSIONS: The ICMR-NCTB is a "first of its kind" approach at harmonizing neuropsychological tests across 5 Indian languages for the diagnosis of MCI due to vascular and other etiologies. Utilizing multiple-domain subcomponents also retains the validity of this instrument, making it a valuable tool in MCI research in multilingual settings.

Standardising Dementia Diagnosis Across Linguistic and Educational Diversity: Study Design of the Indian Council of Medical Research-Neurocognitive Tool Box (ICMR-NCTB).

OBJECTIVES: While the burden of dementia is increasing in low- and middle-income countries, there is a low rate of diagnosis and paucity of research in these regions. A major challenge to study dementia is the limited availability of standardised diagnostic tools for use in populations with linguistic and educational diversity. The objectives of the study were to develop a standardised and comprehensive neurocognitive test battery to diagnose dementia and mild cognitive impairment (MCI) due to varied etiologies, across different languages and educational levels in India, to facilitate research efforts in diverse settings. METHODS: A multidisciplinary expert group formed by Indian Council of Medical Research (ICMR) collaborated towards adapting and validating a neurocognitive test battery, that is, the ICMR Neurocognitive Tool Box (ICMR-NCTB) in five Indian languages (Hindi, Bengali, Telugu, Kannada, and Malayalam), for illiterates and literates, to standardise diagnosis of dementia and MCI in India. RESULTS: Following a review of existing international and national efforts at standardising dementia diagnosis, the ICMR-NCTB was developed and adapted to the Indian setting of sociolinguistic diversity. The battery consisted of tests of cognition, behaviour, and functional activities. A uniform protocol for diagnosis of normal cognition, MCI, and dementia due to neurodegenerative diseases and stroke was followed in six centres. A systematic plan for validating the ICMR-NCTB and establishing cut-off values in a diverse multicentric cohort was developed. CONCLUSIONS: A key outcome was the development of a comprehensive diagnostic tool for diagnosis of dementia and MCI due to varied etiologies, in the diverse socio-demographic setting of India.

Bilingualism and Its Implications for Neuropsychological Evaluation.

OBJECTIVE: In the background of a large population of bilinguals globally, the study aimed to develop standards of neuropsychological testing in the context of bilingualism. Because bilingualism is known to affect cognitive processes, bilinguals and monolinguals were compared on their performance on cognitive tests, to investigate the possibility of the need for separate normative data for the two groups. METHOD: A comprehensive neuropsychological test battery, standardized across five Indian languages: the Indian Council of Medical Research-Neuro Cognitive Tool Box (ICMR-NCTB) was administered to 530 participants (267 monolingual and 263 bilinguals matched for age and education). A systematic method of testing cognition in bilinguals was developed; to identify the appropriate language for testing, ensure language proficiency of examiner, and to interpret the bilingual responses. Additionally, the performance of bilinguals on the ICMR-NCTB was compared with monolinguals. RESULTS: Cognitive testing in the bilingual context was performed in the most proficient language of the participants, by examiners well versed with the language. Results from the language-based tests suggested that the frequent occurrence of borrowed- and language-mixed words required consideration while scoring. The reported bilingual effect on cognitive processes did not reflect as differences in the performance between bilinguals and monolinguals. CONCLUSIONS: Observations from the study provide robust recommendations for neuropsychological testing in the context of bilingualism. Results indicate that separate normative data may not be required for bilinguals and monolinguals. The study will be relevant and provide a reference framework to address similar issues in the large population of bilinguals in other societies.

Validation of ICMR Neurocognitive Toolbox for Dementia in the Linguistically Diverse Context of India.

Objectives: The growing prevalence of dementia, especially in low- and middle-income countries (LMICs), has raised the need for a unified cognitive screening tool that can aid its early detection. The linguistically and educationally diverse population in India contributes to challenges in diagnosis. The present study aimed to assess the validity and diagnostic accuracy of the Indian Council of Medical Research-Neurocognitive Toolbox (ICMR-NCTB), a comprehensive neuropsychological test battery adapted in five languages, for the diagnosis of dementia. Methods: A multidisciplinary group of experts developed the ICMR-NCTB based on reviewing the existing tools and incorporation of culturally appropriate modifications. The finalized tests of the major cognitive domains of attention, executive functions, memory, language, and visuospatial skills were then adapted and translated into five Indian languages: Hindi, Bengali, Telugu, Kannada, and Malayalam. Three hundred fifty-four participants were recruited, including 222 controls and 132 dementia patients. The sensitivity and specificity of the adapted tests were established for the diagnosis of dementia. Results: A significant difference in the mean (median) performance scores between healthy controls and patients with dementia was observed on all tests of ICMR-NCTB. The area under the curve for majority of the tests included in the ICMR-NCTB ranged from 0.73 to 1.00, and the sensitivity and specificity of the ICMR-NCTB tests ranged from 70 to 100% and 70.7 to 100%, respectively, to identify dementia across all five languages. Conclusions: The ICMR-NCTB is a valid instrument to diagnose dementia across five Indian languages, with good diagnostic accuracy. The toolbox was effective in overcoming the challenge of linguistic diversity. The study has wide implications to address the problem of a high disease burden and low diagnostic rate of dementia in LMICs like India.

Multimodality Neuroimaging in Mild Cognitive Impairment: A Cross-sectional Comparison Study.

BACKGROUND AND PURPOSE: Mild cognitive impairment (MCI) is a focus of considerable research. The present study aimed to test the utility of a logistic regression-derived classifier, combining specific quantitative multimodal magnetic resonance imaging (MRI) data for the early objective phenotyping of MCI in the clinic, over structural MRI data. METHODS: Thirty-three participants with cognitively stable amnestic MCI; 15 MCI converters to early Alzheimer's disease (AD; diseased controls) and 20 healthy controls underwent high-resolution T1-weighted volumetric MRI, diffusion tensor imaging (DTI), and proton magnetic resonance spectroscopy (1H MR spectroscopy). The regional volumes were obtained from T1-weighted MRI. The fractional anisotropy and mean diffusivity maps were derived from DTI over multiple white matter regions. The 1H MRS voxels were placed over posterior cingulate gyri, and N-acetyl aspartate (NAA)/creatine (Cr), choline (Cho)/Cr, myoinositol (mI/Cr), and NAA/mI ratios were obtained. A multimodal classifier comprising MR volumetry, DTI, and MRS was prepared. A cutoff point was arrived based on receiver operator characteristics analysis. Results were considered significant, if P < 0.05. RESULTS: The most sensitive individual marker to discriminate MCI from controls was DTI (90.9%), with a specificity of 50%. For classifying MCI from AD, the best individual modality was DTI (72.7%), with a high specificity of 87.9%. The multimodal classifier approach for MCI control classification achieved an area under curve (AUC) (AUC = 0.89; P < 0.001), with 93.9% sensitivity and 70% specificity. The combined classifier for MCI-AD achieved a highest AUC (AUC = 0.93; P < 0.001), with 93% sensitivity and 85.6% specificity. CONCLUSIONS: The combined method of gray matter atrophy, white matter tract changes, and metabolite variation achieved a better performance at classifying MCI compared to the application of individual MRI biomarkers.