scholarly journals BrainCheck: Validation of a Computerized Cognitive Test Battery for Detection of Mild Cognitive Impairment and Dementia

2020 ◽  
Author(s):  
Siao Ye ◽  
Bin Huang ◽  
Kevin Sun ◽  
Huy Q. Phi ◽  
Brian Ko ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Early Detection ◽  
Group Classification ◽  
Cognitive Testing ◽  
Cognitive Test ◽  
True Positive ◽  
Diagnosis Group ◽  
Sensitivity Specificity ◽  
Normal Cognition

AbstractEarly detection of dementia is critical for intervention and care planning, but remains difficult. This study evaluated a computerized cognitive testing battery (BrainCheck) for its diagnostic accuracy and ability to distinguish the severity of cognitive impairment. 99 participants diagnosed with Dementia, Mild Cognitive Impairment (MCI), or Normal Cognition (NC) completed the BrainCheck battery. Statistical analyses compared participant’s performance on BrainCheck based on their diagnosis group BrainCheck battery performance showed significant differences between the NC, MCI, and Dementia groups, achieving ≥88% sensitivity/specificity for separating NC from Dementia, and ≥77% sensitivity/specificity in separating the MCI group from NC/Dementia groups. Three-group-classification found true positive rates ≥80% for the NC and Dementia groups and ≥60% for the MCI group. BrainCheck was able to distinguish between diagnoses of Dementia, MCI, and NC, providing a potentially reliable tool for early detection of cognitive impairment.

Utility of Diffusion Modeling of Cogstate Brief Battery Test Performance in Detecting Mild Cognitive Impairment

Assessment ◽  
2022 ◽  
pp. 107319112110690
Author(s):  
Kyler Mulhauser ◽  
Bruno Giordani ◽  
Voyko Kavcic ◽  
L. D. Nicolas May ◽  
Arijit Bhaumik ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Test Performance ◽  
Drift Rate ◽  
Cognitive Testing ◽  
Diffusion Modeling ◽  
Testing Data ◽  
Recognition Learning ◽  
And Diffusion ◽  
Normal Cognition

Cognitive testing data are essential to the diagnosis of mild cognitive impairment (MCI), and computerized cognitive testing, such as the Cogstate Brief Battery, has proven helpful in efficiently identifying harbingers of dementia. This study provides a side-by-side comparison of traditional Cogstate outcomes and diffusion modeling of these outcomes in predicting MCI diagnosis. Participants included 257 older adults (160 = normal cognition; 97 = MCI). Results showed that both traditional Cogstate and diffusion modeling analyses predicted MCI diagnosis with acceptable accuracy. Cogstate measures of recognition learning and working memory accuracy and diffusion modeling variable of decision-making efficiency (drift rate) and nondecisional time were most predictive of MCI. While participants with normal cognition demonstrated a change in response caution (boundary separation) when transitioning tasks, participants with MCI did not evidence this change.

scholarly journals Improving the diagnosis and prediction of progression in mild cognitive impairment

2018 ◽  
Vol 30 (10) ◽  
pp. 1419-1421 ◽  
Author(s):  
Naaheed Mukadam
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Testing ◽  
Foreseeable Future ◽  
Cortical Volume ◽  
The Past ◽  
Clinical Support ◽  
Functional Assessments ◽  
Risk Of Progression ◽  
Normal Cognition

Mild cognitive impairment (MCI) is a clinical condition conceptualized as a stage between normal cognition and dementia. To diagnose it requires subjective cognitive impairment, evidence of cognitive impairment on cognitive testing but no abnormality in a person's functioning and no evidence of dementia (American Psychiatric Association, 2013). There has been growing interest in the condition over the past two decades or so because people with MCI are much more likely than people with no cognitive impairment to progress to dementia (Roberts et al., 2013). However, a significant percentage of people with MCI will not progress to dementia and some will revert to having normal cognition. Rates of progression and reversion to normal cognition vary widely in different studies (Manly et al., 2008). People with MCI experience worry about their symptoms and this is partly alleviated by receiving a diagnosis of MCI and being reassured they do not have dementia (Gomersall et al., 2017). The benefits of diagnosis also include gaining a greater understanding of their symptoms and accessing clinical support but a significant amount of uncertainty remains with regards to the risk of progression and recipients of the diagnosis remain frustrated at the lack of treatments for MCI (Gomersall et al., 2017). There has been much interest in improving the prediction of progression to dementia from MCI but to date, the best predictors of progression remain structured clinical and functional assessments, with some additional benefit from measures of cortical volume/thickness from brain imaging (Korolev et al., 2016). As yet, however, there are no interventions that can prevent (Kane et al., 2017) or treat (Cooper et al., 2013) MCI so it seems set to remain an important clinical entity for the foreseeable future.

scholarly journals Cognitive test norms and comparison to normal cognition and mild cognitive impairment: A population‐based study among community‐dwelling Filipinos

2020 ◽  
Vol 16 (S6) ◽  
Author(s):  
Jacqueline C. Dominguez ◽  
Raphael Louis B. Citron ◽  
Ma Fe P. De Guzman ◽  
Anne Cristine Deocariza Guevarra ◽  
Justine Megan F. Yu ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Population Based ◽  
Community Dwelling ◽  
Cognitive Test ◽  
Population Based Study ◽  
Test Norms ◽  
Normal Cognition

Elevated Inflammatory Markers and Arterial Stiffening Exacerbate Tau but Not Amyloid Pathology in Older Adults with Mild Cognitive Impairment

2021 ◽  
pp. 1-13
Author(s):  
Alexandra L. Clark ◽  
Alexandra J. Weigand ◽  
Kelsey R. Thomas ◽  
Seraphina K. Solders ◽  
Lisa Delano-Wood ◽  
...  
Keyword(s):  
Older Adults ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Inflammatory Markers ◽  
Memory Performance ◽  
Cognitive Testing ◽  
Interactive Effects ◽  
Protein Biomarkers ◽  
Age Related ◽  
T Tau

Background: Age-related cerebrovascular and neuroinflammatory processes have been independently identified as key mechanisms of Alzheimer’s disease (AD), although their interactive effects have yet to be fully examined. Objective: The current study examined 1) the influence of pulse pressure (PP) and inflammatory markers on AD protein levels and 2) links between protein biomarkers and cognitive function in older adults with and without mild cognitive impairment (MCI). Methods: This study included 218 ADNI (81 cognitively normal [CN], 137 MCI) participants who underwent lumbar punctures, apolipoprotein E (APOE) genotyping, and cognitive testing. Cerebrospinal (CSF) levels of eight pro-inflammatory markers were used to create an inflammation composite, and amyloid-beta 1–42 (Aβ 42), phosphorylated tau (p-tau), and total tau (t-tau) were quantified. Results: Multiple regression analyses controlling for age, education, and APOE ɛ4 genotype revealed significant PP x inflammation interactions for t-tau (B = 0.88, p = 0.01) and p-tau (B = 0.84, p = 0.02); higher inflammation was associated with higher levels of tau within the MCI group. However, within the CN group, analyses revealed a significant PP x inflammation interaction for Aβ 42 (B = –1.01, p = 0.02); greater inflammation was associated with higher levels of Aβ 42 (indicative of lower cerebral amyloid burden) in those with lower PP. Finally, higher levels of tau were associated with poorer memory performance within the MCI group only (p s <  0.05). Conclusion: PP and inflammation exert differential effects on AD CSF proteins and provide evidence that vascular risk is associated with greater AD pathology across our sample of CN and MCI older adults.

Mini-Mental State Examination (MMSE) for the early detection of dementia in people with mild cognitive impairment (MCI)

2021 ◽  
Vol 2021 (7) ◽  
Author(s):  
Ingrid Arevalo-Rodriguez ◽  
Nadja Smailagic ◽  
Marta Roqué-Figuls ◽  
Agustín Ciapponi ◽  
Erick Sanchez-Perez ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Early Detection ◽  
Mental State ◽  
Mini Mental State Examination ◽  
State Examination

scholarly journals Can the MMSE help clinicians predict progression from mild cognitive impairment to dementia?

2015 ◽  
Vol 21 (6) ◽  
pp. 363-366 ◽  
Author(s):  
Alex J. Mitchell
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Risk Prediction ◽  
Mental State ◽  
Mini Mental State Examination ◽  
Case Finding ◽  
Cognitive Test ◽  
Prediction Tool ◽  
State Examination

SummaryThe Mini-Mental State Examination (MMSE) is the most widely used bedside cognitive test. It has previously been shown to be poor as a case-finding tool for both dementia and mild cognitive impairment (MCI). This month's Cochrane Corner review examines whether the MMSE might be used as a risk prediction tool for later dementia in those with established MCI. From 11 studies of modest quality, it appears that the MMSE alone should not be relied on to predict later deterioration in people with MCI. As this is the case, it is likely that only a combination of predictors would be able to accurately predict progression from MCI to dementia.

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