Kelvin K F Tsoi1, Joyce Y C Chan2, Hoyee W Hirai2, Adrian Wong3, Vincent C T Mok3, Linda C W Lam4, Timothy C Y Kwok3, Samuel Y S Wong5. 1. JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, Hong Kong; Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Shatin, Hong Kong. 2. Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Shatin, Hong Kong. 3. Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong. 4. Department of Psychiatry, The Chinese University of Hong Kong, Shatin, Hong Kong. 5. JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, Hong Kong. Electronic address: yeungshanwong@cuhk.edu.hk.
Abstract
BACKGROUND: Mild cognitive impairment (MCI) is a prevalent symptom associated with the increased risk of dementia. There are many cognitive tests available for detection of MCI, and investigation of the diagnostic performance of the tests is deemed necessary. OBJECTIVE: This study aims to evaluate the diagnostic performance of different cognitive tests used for MCI detection. DATA SOURCES: A list of cognitive tests was identified in previous reviews and from online search engines. Literature searches were performed on each of the cognitive tests in MEDLINE, Embase, and PsycINFO from the earliest available dates of individual databases to December 31, 2016. Google Scholar was used as a supplementary search tool. STUDY SELECTION: Studies that were used to assess the diagnostic performance of the cognitive tests were extracted with inclusion and exclusion criteria. Each test's performance was compared with the standard diagnostic criteria. Bivariate random effects models were used to summarize the test performance as a point estimate for sensitivity and specificity, and presented in a summary receiver operating characteristic curve. Reporting quality and risk of bias were evaluated. RESULTS: A total of 108 studies with 23,546 participants were selected to evaluate 9 cognitive tests for MCI detection. Most of the studies used the Mini-Mental State Examination (MMSE) (n = 58) and the Montreal Cognitive Assessment (MoCA) (n = 35). The combined diagnostic performance of the MMSE in MCI detection was 0.71 sensitivity [95% confidence interval (CI): 0.66-0.75] and 0.74 specificity (95% CI: 0.70-0.78), and of the MoCA in MCI detection was 0.83 sensitivity (95% CI: 0.80-0.86) and 0.75 specificity (95% CI: 0.69-0.80). Among the 9 cognitive tests, recall tests showed the best diagnostic performance with 0.89 sensitivity (95% CI: 0.86-0.92) and 0.84 specificity (95% CI, 0.79-0.89). In subgroup analyses, long- or short-delay recall tests have shown better performance than immediate recall tests. CONCLUSIONS: Recall tests were shown to be the most effective test in MCI detection, especially for the population with symptoms of memory deterioration. They can be potentially used as the triage screening test for MCI in primary care setting. But when a patient shows cognitive impairments beyond memory deterioration, a more comprehensive test such as the MoCA should be used.
BACKGROUND: Mild cognitive impairment (MCI) is a prevalent symptom associated with the increased risk of dementia. There are many cognitive tests available for detection of MCI, and investigation of the diagnostic performance of the tests is deemed necessary. OBJECTIVE: This study aims to evaluate the diagnostic performance of different cognitive tests used for MCI detection. DATA SOURCES: A list of cognitive tests was identified in previous reviews and from online search engines. Literature searches were performed on each of the cognitive tests in MEDLINE, Embase, and PsycINFO from the earliest available dates of individual databases to December 31, 2016. Google Scholar was used as a supplementary search tool. STUDY SELECTION: Studies that were used to assess the diagnostic performance of the cognitive tests were extracted with inclusion and exclusion criteria. Each test's performance was compared with the standard diagnostic criteria. Bivariate random effects models were used to summarize the test performance as a point estimate for sensitivity and specificity, and presented in a summary receiver operating characteristic curve. Reporting quality and risk of bias were evaluated. RESULTS: A total of 108 studies with 23,546 participants were selected to evaluate 9 cognitive tests for MCI detection. Most of the studies used the Mini-Mental State Examination (MMSE) (n = 58) and the Montreal Cognitive Assessment (MoCA) (n = 35). The combined diagnostic performance of the MMSE in MCI detection was 0.71 sensitivity [95% confidence interval (CI): 0.66-0.75] and 0.74 specificity (95% CI: 0.70-0.78), and of the MoCA in MCI detection was 0.83 sensitivity (95% CI: 0.80-0.86) and 0.75 specificity (95% CI: 0.69-0.80). Among the 9 cognitive tests, recall tests showed the best diagnostic performance with 0.89 sensitivity (95% CI: 0.86-0.92) and 0.84 specificity (95% CI, 0.79-0.89). In subgroup analyses, long- or short-delay recall tests have shown better performance than immediate recall tests. CONCLUSIONS: Recall tests were shown to be the most effective test in MCI detection, especially for the population with symptoms of memory deterioration. They can be potentially used as the triage screening test for MCI in primary care setting. But when a patient shows cognitive impairments beyond memory deterioration, a more comprehensive test such as the MoCA should be used.
Authors: Frank Jessen; Rebecca E Amariglio; Rachel F Buckley; Wiesje M van der Flier; Ying Han; José Luis Molinuevo; Laura Rabin; Dorene M Rentz; Octavio Rodriguez-Gomez; Andrew J Saykin; Sietske A M Sikkes; Colette M Smart; Steffen Wolfsgruber; Michael Wagner Journal: Lancet Neurol Date: 2020-01-17 Impact factor: 44.182
Authors: Joyce Y C Chan; Adrian Wong; Brian Yiu; Hazel Mok; Patti Lam; Pauline Kwan; Amany Chan; Vincent C T Mok; Kelvin K F Tsoi; Timothy C Y Kwok Journal: J Med Internet Res Date: 2020-12-18 Impact factor: 5.428
Authors: Kelly Estrada-Orozco; Kely Bonilla-Vargas; Francy Cruz; Oscar Mancera; Miguel Ruiz; Laura Alvarez; Rodrigo Pardo; Humberto Arboleda Journal: Int J Alzheimers Dis Date: 2018-07-02