Validation of the Addenbrooke’s Cognitive Examination-III in Mild Cognitive Impairment in Arabic Speakers in Egypt

2020 ◽  
pp. 1-5
Author(s):  
Tarik Qassem ◽  
Mohamed S. Khater ◽  
Tamer Emara ◽  
Doha Rasheedy ◽  
Heba M. Tawfik ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Characteristic Curve ◽  
Screening Tools ◽  
Arabic Version ◽  
Cognitive Screening ◽  
Egyptian Arabic ◽  
Arabic Speakers ◽  
Significant Difference ◽  
Addenbrooke’S Cognitive Examination

<b><i>Background and Aims:</i></b> Mild cognitive impairment (MCI) represents an important point on the pathway to developing dementia and a target for early detection and intervention. There is a shortage of validated cognitive screening tools in Arabic to diagnose MCI. The aim of this study was to validate Addenbrooke’s Cognitive Examination-III (ACE-III) (Egyptian-Arabic version) in a sample of patients with MCI, to provide cut-off scores in Egyptian-Arabic speakers. <b><i>Methods:</i></b> A total of 24 patients with MCI and 54 controls were included in the study and were administered the Egyptian-Arabic version of the ACE-III. <b><i>Results:</i></b> There was a statistically significant difference (<i>p</i> &#x3c; 0.001) in the total ACE-III score between MCI patients (mean 75.83, standard deviation (SD) 8.1) and controls (mean 86.26, SD 6.74). There was also a statistically significant difference between MCI patients and controls in the memory, fluency, and visuospatial sub-scores of the ACE-III (<i>p</i> &#x3c; 0.05) but not in attention and language sub-scores. Using a receiver operator characteristic curve, the optimal cut-off score for diagnosing MCI on the ACE-III total score was 81, with 75% sensitivity, 82% specificity, and 80% accuracy. <b><i>Conclusions:</i></b> The results of this study provide objective validation of the Egyptian-Arabic version of the ACE-III as a screening tool for MCI, with good sensitivity, specificity, and accuracy that are comparable to other translated versions of the ACE-III in MCI.

Validation of the Mini-Addenbrooke’s Cognitive Examination in Mild Cognitive Impairment in Arabic Speakers

2021 ◽  
pp. 1-5
Author(s):  
Tarik Qassem ◽  
Mohamed S. Khater ◽  
Tamer Emara ◽  
Doha Rasheedy ◽  
Heba M. Tawfik ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Screening Tool ◽  
Characteristic Curve ◽  
Receiver Operator Characteristic Curve ◽  
Screening Tools ◽  
Arabic Speakers ◽  
Significant Difference ◽  
Sensitivity Specificity ◽  
Addenbrooke’S Cognitive Examination

<b><i>Introduction:</i></b> Mild cognitive impairment (MCI) represents a target for early detection and intervention in dementia, yet there is a shortage of validated screening tools in Arabic to diagnose MCI. The mini-Addenbrooke’s Cognitive Examination (m-ACE) is a brief cognitive battery that is scored out of 30 and can be administered in under 5 min providing a quick screening tool for assessment of cognition. <b><i>Objective:</i></b> We aimed to validate the m-ACE in Arabic speakers in Egypt with MCI to provide cut-off scores. <b><i>Methods:</i></b> We included 24 patients with MCI and 52 controls and administered the Arabic version of the m-ACE. <b><i>Results:</i></b> There was a statistically significant difference (<i>p</i> &#x3c; 0.0001) on the total m-ACE score between MCI patients (mean 18.54, SD 3.05) and controls (mean 24.54, SD 2.68). There was also a statistically significant difference between MCI patients and controls on the total score and the fluency, visuospatial, and memory recall sub-scores of the m-ACE (<i>p</i> &#x3c; 0.05). Performance on the m-ACE significantly correlated with both the Mini-Mental State Examination (MMSE) and the Addenbrooke’s Cognitive Examination-III (ACE-III). Using a receiver operator characteristic curve, the optimal cut-off score for MCI on the m-ACE total score was 21 out of 30 (87.5% sensitivity, 84.6% specificity, and 85.5% accuracy). <b><i>Conclusions:</i></b> We validated the Arabic m-ACE in Egyptian patients with MCI and provided objective validation of it as a screening tool for MCI, with good sensitivity, specificity, and accuracy that is comparable to other translated versions of the m-ACE in MCI.

Adaptation and Validation of the Mini-Addenbrooke’s Cognitive Examination in Dementia in Arabic Speakers in Egypt

2020 ◽  
Vol 49 (6) ◽  
pp. 611-616
Author(s):  
Tarik Qassem ◽  
Mohamed S. Khater ◽  
Tamer Emara ◽  
Doha Rasheedy ◽  
Heba M. Tawfik ◽  
...  
Keyword(s):  
Screening Tool ◽  
Characteristic Curve ◽  
High Sensitivity ◽  
Receiver Operator Characteristic Curve ◽  
Cutoff Score ◽  
Arabic Speakers ◽  
Dementia Patients ◽  
Significant Difference ◽  
Sensitivity Specificity ◽  
Addenbrooke’S Cognitive Examination

<b><i>Background:</i></b> The mini-Addenbrooke’s Cognitive Examination (m-ACE) is a brief cognitive battery that assesses 5 subdomains of cognition (attention, memory, verbal fluency, visuospatial abilities, and memory recall). It is scored out of 30 and can be administered in under 5 min providing a quick screening tool for assessment of cognition. <b><i>Objectives:</i></b> We aimed to adapt the m-ACE in Arabic speakers in Egypt and to validate it in dementia patients to provide cutoff scores. <b><i>Methods:</i></b> We included 37 patients with dementia (Alzheimer’s disease [<i>n</i> = 25], vascular dementia [<i>n</i> = 8], and dementia with Lewy body [<i>n</i> = 4]) and 43 controls. <b><i>Results:</i></b> There was a statistically significant difference (<i>p</i> &#x3c; 0.001) on the total m-ACE score between dementia patients (mean 10.54 and standard deviation [SD] 5.83) and controls (mean 24.02 and SD 2.75). There was also a statistically significant difference between dementia patients and controls on all sub-score domains of the m-ACE (<i>p</i> &#x3c; 0.05). Performance on the m-ACE significantly correlated with both the Mini-Mental State Examination (MMSE) and the Addenbrooke’s Cognitive Examination-III (ACE-III). Using a receiver operator characteristic curve, the optimal cutoff score for dementia on the m-ACE total score was found to be 18 (92% sensitivity, 95% specificity, and 94% accuracy). <b><i>Conclusions:</i></b> We adapted the m-ACE in Arabic speakers in Egypt and provided objective validation of it as a screening tool for dementia, with high sensitivity, specificity, and accuracy.

scholarly journals Utility of MemTrax and Machine Learning Modeling in Classification of Mild Cognitive Impairment

2020 ◽  
Vol 77 (4) ◽  
pp. 1545-1558
Author(s):  
Michael F. Bergeron ◽  
Sara Landset ◽  
Xianbo Zhou ◽  
Tao Ding ◽  
Taghi M. Khoshgoftaar ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Performance Metrics ◽  
Early Stage ◽  
Characteristic Curve ◽  
Classification Performance ◽  
Cognitive Screening ◽  
Cross Sectional ◽  
Machine Learning Classification

Background: The widespread incidence and prevalence of Alzheimer’s disease and mild cognitive impairment (MCI) has prompted an urgent call for research to validate early detection cognitive screening and assessment. Objective: Our primary research aim was to determine if selected MemTrax performance metrics and relevant demographics and health profile characteristics can be effectively utilized in predictive models developed with machine learning to classify cognitive health (normal versus MCI), as would be indicated by the Montreal Cognitive Assessment (MoCA). Methods: We conducted a cross-sectional study on 259 neurology, memory clinic, and internal medicine adult patients recruited from two hospitals in China. Each patient was given the Chinese-language MoCA and self-administered the continuous recognition MemTrax online episodic memory test on the same day. Predictive classification models were built using machine learning with 10-fold cross validation, and model performance was measured using Area Under the Receiver Operating Characteristic Curve (AUC). Models were built using two MemTrax performance metrics (percent correct, response time), along with the eight common demographic and personal history features. Results: Comparing the learners across selected combinations of MoCA scores and thresholds, Naïve Bayes was generally the top-performing learner with an overall classification performance of 0.9093. Further, among the top three learners, MemTrax-based classification performance overall was superior using just the top-ranked four features (0.9119) compared to using all 10 common features (0.8999). Conclusion: MemTrax performance can be effectively utilized in a machine learning classification predictive model screening application for detecting early stage cognitive impairment.

Contributions of the Computer-Administered Neuropsychological Screen for Mild Cognitive Impairment (CANS-MCI) for the diagnosis of MCI in Brazil

2014 ◽  
Vol 26 (9) ◽  
pp. 1483-1491 ◽  
Author(s):  
Cláudia M. Memória ◽  
Mônica S. Yassuda ◽  
Eduardo Y. Nakano ◽  
Orestes V. Forlenza
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Goodness Of Fit ◽  
Formal Education ◽  
Factor Model ◽  
Characteristic Curve ◽  
Reliability And Validity ◽  
Cognitive Status ◽  
Cognitive Screening ◽  
Extensive Evaluation

ABSTRACTBackground:The Computer-Administered Neuropsychological Screen for Mild Cognitive Impairment (CANS-MCI) is a computer-based cognitive screening instrument that involves automated administration and scoring and immediate analyses of test sessions. The objective of this study was to translate and culturally adapt the Brazilian Portuguese version of the CANS-MCI (CANS-MCI-BR) and to evaluate its reliability and validity for the diagnostic screening of MCI and dementia due to Alzheimer's disease.Methods:The test was administered to 97 older adults (mean age 73.41 ± 5.27 years) with at least four years of formal education (mean education 12.23 ± 4.48 years). Participants were classified into three diagnostic groups according to global cognitive status (normal controls, n = 41; MCI, n = 35; AD, n = 21) based on clinical data and formal neuropsychological assessments.Results:The results indicated high internal consistency (Cronbach's α = 0.77) in the total sample. Three-month test-retest reliability correlations were significant and robust (0.875; p < 0.001). A moderate level of concurrent validity was attained relative to the screening test for MCI (MoCA test, r = 0.76, p < 0.001). Confirmatory factor analysis supported the three-factor model of the original test, i.e., memory, language/spatial fluency, and executive function/mental control. Goodness of fit indicators were strong (Bentler Comparative Fit Index = 0.96, Root Mean Square Error of Approximation = 0.09). Receiver operating characteristic curve analyses suggested high sensitivity and specificity (81% and 73% respectively) to screen for possible MCI cases.Conclusions:The CANS-MCI-BR maintains adequate psychometric characteristics that render it suitable to identify elderly adults with probable cognitive impairment to whom a more extensive evaluation by formal neuropsychological tests may be required.

scholarly journals Screening for mild cognitive impairment in people with obesity: a systematic review

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Nimantha Karunathilaka ◽  
Sarath Rathnayake
Keyword(s):  
Systematic Review ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
General Population ◽  
Age Groups ◽  
Positive Association ◽  
Screening Tools ◽  
Cognitive Screening ◽  
Screening Process ◽  
Older Adulthood

Abstract Objective Recent evidence demonstrates that obesity is associated with developing cognitive impairment. However, evidence related to the assessment of mild cognitive impairment (MCI) in people with obesity is limited. Therefore, this systematic review aimed to examine evidence concerning the screening of MCI in people with obesity from the general population. Method We conducted a systematic search of CINHAL, EMBASE, MEDLINE, PsycINFO and PubMed electronic databases for observational studies to assess MCI in people with obesity from the general population. PRISMA guideline was followed. The articles published from January 2011 to July 2021 were included. Results Database search found 3104 sources. After the screening process, two articles from China and Egypt were included. The main age groups assessed were middle-aged adulthood and older adulthood. There were no studies undertaken in young adults or across the life span. Obesity was assessed by body mass index. MCI was assessed by cognitive screening tools; Mini-mental State Examination and Addenbrooke’s Cognitive Examination. The prevalence of MCI in people with obesity was 18.5 % and 42.9 % in Chinese and Egyptian studies, respectively. Only one study supported a positive association between MCI and obesity. Conclusions Limited studies were found on screening MCI in people with obesity in the general population. The available evidence was not adequate to explain the overall prevalence, possible associations, and the best tool for assessing MCI in people with obesity. Expanding screening studies for MCI in people with obesity in the general population is essential.

scholarly journals Role of Executive Functions in the Conversion from Mild Cognitive Impairment to Dementia

2020 ◽  
Vol 77 (2) ◽  
pp. 641-653
Author(s):  
Almudena Junquera ◽  
Estefanía García-Zamora ◽  
Javier Olazarán ◽  
Mario A. Parra ◽  
Sara Fernández-Guinea
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Executive Functions ◽  
Significant Proportion ◽  
Executive Dysfunction ◽  
Clinical Syndrome ◽  
Screening Tools ◽  
Cognitive Screening ◽  
Functional Impairments ◽  
Lineal Regression

Background: Recent research pointed to executive dysfunction as a potential early predictor of the progression of mild cognitive impairment (MCI) to dementia in Alzheimer’s clinical syndrome (ACS). Such cognitive impairments account for functional impairments in instrumental activities of daily living (IADL). Objective: The present study analyzes the contributions of executive functions to predict MCI–dementia progression in ACS. Methods: We assessed 145 participants, 51 cognitively unimpaired and 94 MCI. The latter were divided using the traditional, memory-based MCI classification (single domain amnestic, multidomain amnestic, and non-amnestic). Eight tests assessing executive functions were administered at baseline and at 1-year follow-up, together with cognitive screening tools and IADL measures. MCI patients were reclassified based on the outcomes from a K-mean cluster analysis which identified three groups. A simple lineal regression model was used to examine whether the classification based on executive functioning could more accurately predict progression to dementia a year later. Results: Clusters based on executive function deficits explained a significant proportion of the variance linked to MCI–dementia conversion, even after controlling for the severity of MCI at baseline (F(1, 68) = 116.25, p = 0.000, R2 = 0.63). Classical memory-based MCI classification failed to predict such a conversion (F(1, 68) = 5.09, p = 0.955, R2 = 0.07). Switching, categories generation, and planning were the executive functions that best distinguished between MCI converters and stable. Conclusion: MCI with a dysexecutive phenotype significantly predicts conversion to dementia in ACS a year later. Switching abilities and verbal fluency (categories) must be evaluated in MCI patients to assess risk of future dementia.

Adjusting the Thai version of the Addenbrooke’s Cognitive Examination III for education to screen for dementia

2021 ◽  
Author(s):  
Thammanard Charernboon
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Diagnostic Accuracy ◽  
Receiver Operating Characteristic Curve ◽  
Operating Characteristic ◽  
Characteristic Curve ◽  
Education Level ◽  
Operating Characteristic Curve ◽  
Normal Controls ◽  
Addenbrooke’S Cognitive Examination

Aim: To examine whether education adjusted cut-off points of the Thai version of the ACE-III improve diagnostic accuracy in the detection of mild cognitive impairment (MCI) and dementia. Materials & methods: There were 172 participants consisting of 70 normal controls, 49 people with MCI and 53 patients with dementia. Results: To screen for MCI, the adjusted for education method yielded greater accuracy for the area under the receiver operating characteristic curve (AuROC) than the unadjusted method (0.9–0.92 vs 0.86). For the detection of dementia, when applying the education correction, AuROC increased from 0.87 (unadjusted) to 0.91 for the education >6 group, but there was no improvement for education ≤6 group (AuROC 0.86). Conclusion: The use of adjusted cut-off score for education level could increase the diagnostic accuracy of the test.

scholarly journals Cognitive Impairment in Transient Ischemic Attack Patients: A Systematic Review

2016 ◽  
Vol 42 (1-2) ◽  
pp. 1-9 ◽  
Author(s):  
Frank G. van Rooij ◽  
Roy P.C. Kessels ◽  
Edo Richard ◽  
Frank-Erik De Leeuw ◽  
Ewoud J. van Dijk
Keyword(s):  
Systematic Review ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Transient Ischemic Attack ◽  
Risk Of Bias ◽  
Screening Tools ◽  
Insufficient Data ◽  
Cognitive Screening ◽  
Considerable Heterogeneity ◽  
Ischemic Attack

Background: Although by definition a transient ischemic attack (TIA) lasts less than 24 h, many patients experience cognitive complaints beyond focal symptom resolution. However, their prevalence, causes and profile are unclear. We therefore performed a systematic review on cognitive impairment after TIA. Summary: Medline and Embase were searched for relevant studies. Risk of bias was assessed, and data synthesis was performed according to the severity of cognitive impairment. Thirteen studies were included, with considerable heterogeneity concerning methods and timing of cognitive testing. Confounding, detection bias and attrition were the main causes of a high risk of bias in several studies. The prevalence of post-TIA mild cognitive impairment ranged from 29 to 68%. Severe cognitive impairment was found in 8-22% of patients. Studies using a cognitive screening instrument and those performed shortly after TIA or several years later, reported the highest frequencies of impairment. Patients evaluated with a screening tool were substantially older than those who underwent a full neuropsychological assessment (weighted mean age difference 10.9 years). Based on limited data, the post-TIA cognitive profile showed prominent executive function deficits. Insufficient data refrained us from drawing conclusions on causality. The few studies that reported neuroimaging results found a minor correlation with cognitive impairment. Key Messages: Mild cognitive impairment is present in more than a third of the TIA patients and has a profile comparable with vascular cognitive impairment. Reported rates of post-TIA cognitive impairment are highly variable and higher frequencies are found with cognitive screening tools. Considerable heterogeneity and insufficient data limit further conclusions about potential causative factors.

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