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Turana Y, Farina N, Theresia I, Fitri FI, Suswanti I, Jacobs R, Schneider M, Sani TP, Comas-Herrera A, Albanese E, Govia I, Ferri CP, Knapp M, Banerjee S. The dementia severity rating scale: A potential community screening tool for dementia in low- and middle-income countries. DEMENTIA 2024; 23:476-492. [PMID: 38096489 DOI: 10.1177/14713012231186837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
BACKGROUND The Dementia Severity Rating Scale (DSRS) is an informant report, dementia staging tool that is quick to administer and has previous been shown to differentiate between people with dementia and healthy controls. However, it is not clear how accurate the tool is screening against diagnostic criteria in middle-income settings. METHODS Embedded within the STRiDE programme, older adults (aged ≥65 years) and their informants were randomly recruited from four sites across Indonesia and South Africa. All informants were asked to complete DSRS. We report the tool's psychometric properties and accuracy against the 10/66 short diagnostic algorithm. RESULTS Between September and December 2021, data was collected from 2110 older adults in Indonesia and 408 in South Africa. Overall, the DSRS scores significantly differed between those with and without dementia, as identified on the 10/66 short algorithm (p < .05). The difference between groups remained significant after controlling for key factors related to older adult and informant demographics. A score >2 on the DSRS had the greatest agreement with the 10/66 short algorithm and had excellent discriminative properties in both Indonesia (Area Under Curve (AUC) = .75, 95% CIs = .72-.77) and South Africa (AUC = .82, 95% CIs = .76-.88). CONCLUSIONS The DSRS has potential as a screening tool for dementia in middle-income countries, with high sensitivity and specificity against a standardized diagnostic algorithm.
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Affiliation(s)
- Yuda Turana
- School of Medicine and Health Sciences, Atma Jaya Hospital, Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia
| | - Nicolas Farina
- Centre for Dementia Studies, Brighton and Sussex Medical School, Brighton, UK
- Faculty of Health, University of Plymouth, Plymouth, UK
| | | | - Fasihah Irfani Fitri
- Department of Neurology, Adam Malik General Hospital, Universitas Sumatera Utara, Medan Indonesia, Indonesia
| | - Ika Suswanti
- School of Medicine and Health Sciences, Atma Jaya Hospital, Atma Jaya Catholic University of Indonesia, Jakarta, Indonesia
| | - Roxanne Jacobs
- Alan J. Flisher Centre for Public Mental Health, University of Cape Town, Cape Town, South Africa
| | | | | | | | | | - Ishtar Govia
- Caribbean Institute for Health Research (CAIHR)-Epidemiology Research Unit, The University of the West Indies, Kingston, Jamaica
| | - Cleusa P Ferri
- Department of Psychiatry, Universidade Federal de São Paulo, Sao Paulo, Brazil
| | - Martin Knapp
- London School of Economics and Political Science, London, UK
| | - Sube Banerjee
- Centre for Dementia Studies, Brighton and Sussex Medical School, Brighton, UK
- Faculty of Health, University of Plymouth, Plymouth, UK
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Wang X, Li F, Tian J, Gao Q, Zhu H. Bayesian estimation for the accuracy of three neuropsychological tests in detecting Alzheimer's disease and mild cognitive impairment: a retrospective analysis of the ADNI database. Eur J Med Res 2023; 28:427. [PMID: 37821912 PMCID: PMC10568914 DOI: 10.1186/s40001-023-01265-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 08/03/2023] [Indexed: 10/13/2023] Open
Abstract
BACKGROUND The neuropathological confirmation serves as the gold standard for diagnosing Alzheimer's disease (AD), but it is usually not available to the living individuals. In addition, the gold standard for diagnosing Mild Cognitive Impairment (MCI) remains unclear yet. Neuropsychological testing, such as the Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE) and Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-cog), is commonly used tests in identifying AD and MCI, offering convenience, affordability, non-invasiveness, and accessibility in clinical settings. We aimed to accurately evaluate the discriminative ability of the three tests administrated at the same visit simultaneously in detecting AD and MCI due to AD in the absence of a gold standard. METHODS A total of 1289 participants aged over 65 were included from the baseline visits of Alzheimer's disease Neuroimaging Initiative. Bayesian latent class models, accounting for conditional dependence between MoCA and MMSE, were conducted to assess the diagnostic accuracy of the three tests for detecting AD and MCI. RESULTS In detecting AD, the ADAS-cog had the highest Youden's Index (0.829), followed by the MoCA(0.813) and MMSE(0.796). The ADAS-cog and MoCA showed similar sensitivity (0.922 vs 0.912) and specificity (0.907 vs 0.901), while the MMSE had lower sensitivity (0.874) and higher specificity (0.922). For MCI detection, the ADAS-cog had the highest Youden's Index (0.704) compared to the MoCA (0.614) and MMSE (0.478). The ADAS-cog exhibited the highest sensitivity, closely followed by the MoCA and MMSE (0.869 vs 0.845 vs 0.757), and the ADAS-cog also had good specificity (0.835 vs 0.769 vs 0.721). The estimated true prevalence of AD among individuals aged over 65 was 20.0%, and the estimated true prevalence of MCI due to AD was 24.8%. CONCLUSIONS The findings suggest that the ADAS-cog and MoCA are reliable tools for detecting AD and MCI, while the MMSE may be less sensitive in detecting these conditions. A large underdiagnosis of the MCI and Alzheimer's population still remains in clinical screening.
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Affiliation(s)
- Xiaonan Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No. 10, Xi Toutiao You Anmenwai, Beijing, 100069, People's Republic of China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, People's Republic of China
| | - Fengjie Li
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No. 10, Xi Toutiao You Anmenwai, Beijing, 100069, People's Republic of China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, People's Republic of China
| | - Jiang Tian
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No. 10, Xi Toutiao You Anmenwai, Beijing, 100069, People's Republic of China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, People's Republic of China
| | - Qi Gao
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, No. 10, Xi Toutiao You Anmenwai, Beijing, 100069, People's Republic of China.
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Capital Medical University, Beijing, People's Republic of China.
| | - Huiping Zhu
- Department of Maternal and Child Health, School of Public Health, Capital Medical University, No. 10, Xi Toutiao You Anmenwai, Beijing, 100069, People's Republic of China.
- Laboratory for Gene-Environment and Reproductive Health, Laboratory for Clinical Medicine, Capital Medical University, Beijing, People's Republic of China.
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Ashford JW, Schmitt FA, Bergeron MF, Bayley PJ, Clifford JO, Xu Q, Liu X, Zhou X, Kumar V, Buschke H, Dean M, Finkel SI, Hyer L, Perry G. Now is the Time to Improve Cognitive Screening and Assessment for Clinical and Research Advancement. J Alzheimers Dis 2022; 87:305-315. [DOI: 10.3233/jad-220211] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Alzheimer’s disease (AD) is the only cause of death ranked in the top ten globally without precise early diagnosis or effective means of prevention or treatment. Further, AD was identified as a pandemic [1] well before COVID-19 was dubbed a 21st century pandemic [2]. And now, with the realization of the prominent secondary impacts of pandemics, there is a growing, widespread recognition of the tremendous magnitude of the impending burden from AD in an aging world population in the coming decades [3]. This appreciation has amplified the growing and pressing need for a new, efficacious, and practical platform to detect and track cognitive decline, beginning in the preliminary (prodromal) phases of the disease, sensitively, accurately, effectively, reliably, efficiently, and remotely [4–7]. Moreover, the parallel necessity of clarifying and understanding risk factors, developing successful prevention strategies [8–17], and discovering and monitoring viable and effective treatments could all benefit from accurate and efficient screening and assessment platforms. Modern recognition of AD [18] as a common affliction of the elderly began in 1968 with a paper by Blessed, Tomlinson, & Roth [19] in which two tests, one a brief assessment of cognitive function and the other a measure of daily function, demonstrated impairment which was associated with the postmortem counts of neurofibrillary tangles, composed mainly of microtubule-associated protein-tau (tau), in the brain, though not to senile plaques, composed mainly of amyloid-β (Aβ). Even in more recent analyses, the tangles correspond with the severity of dementia more than the plaques [20, 21]. Since 1960, a plethora of cognitive tests, paper and pencil [22, 23], simple screening models [24], and computerized [25–27], have been developed to assess the dysfunction associated with AD. However, there has been limited application of Modern Test Theory, which includes Item Characteristic Curve Analysis, used in the technological development of such tools [28–31], along with widespread failure to understand the underlying AD pathological process to guide test development [32, 33]. The lack of such development has likely been a major contributor to the failure of the field to develop timely screening approaches for AD [34, 35], inaccurate assessment of the progression of AD [36], and even now, failure to find an effective approach to stopping AD.
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Affiliation(s)
- J. Wesson Ashford
- War Related Illness and Injury Study Center, VA Palo Alto HCS, Palo Alto, CA, USA
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Medical, Scientific, Memory Screening Advisory Board, Alzheimer’s Foundation of American (AFA), New York, USA
| | - Frederick A. Schmitt
- Medical, Scientific, Memory Screening Advisory Board, Alzheimer’s Foundation of American (AFA), New York, USA
- Departments of Neurology, Psychiatry, Neurosurgery, Psychology, Behavioral Science; Sanders-Brown Center on Aging, Spinal Cord & Brain Injury Research Center, University of Kentucky, Sanders-Brown Center on Aging, Lexington, KY, USA
| | | | - Peter J. Bayley
- War Related Illness and Injury Study Center, VA Palo Alto HCS, Palo Alto, CA, USA
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Medical, Scientific, Memory Screening Advisory Board, Alzheimer’s Foundation of American (AFA), New York, USA
| | | | - Qun Xu
- Health Management Center, Department of Neurology, Renji Hospital of Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaolei Liu
- Department of Neurology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
- Yunnan Provincial Clinical Research Center for Neurological Diseases, Yunnan, China
| | - Xianbo Zhou
- Center for Alzheimer’s Research, Washington Institute of Clinical Research, Vienna, VA, USA
- Zhongze Therapeutics, Shanghai, China
| | | | - Herman Buschke
- Medical, Scientific, Memory Screening Advisory Board, Alzheimer’s Foundation of American (AFA), New York, USA
- The Saul R. Korey Department of Neurology and Dominick P. Purpura Department of Neuroscience, Lena and Joseph Gluck Distinguished Scholar in Neurology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Margaret Dean
- Medical, Scientific, Memory Screening Advisory Board, Alzheimer’s Foundation of American (AFA), New York, USA
- Geriatric Division, Internal Medicine, Texas Tech Health Sciences Center, Amarillo, TX, USA
| | - Sanford I. Finkel
- Medical, Scientific, Memory Screening Advisory Board, Alzheimer’s Foundation of American (AFA), New York, USA
- University of Chicago Medical School, Chicago, IL, USA
| | - Lee Hyer
- Medical, Scientific, Memory Screening Advisory Board, Alzheimer’s Foundation of American (AFA), New York, USA
- Gateway Behavioral Health, Mercer University, School of Medicine, Savannah, GA, USA
| | - George Perry
- Medical, Scientific, Memory Screening Advisory Board, Alzheimer’s Foundation of American (AFA), New York, USA
- Brain Health Consortium, Department Biology and Chemistry, University of Texas at San Antonio, San Antonio, TX, USA
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