A Rapid, Mobile Neurocognitive Screening Test to Aid in Identifying Cognitive Impairment and Dementia (BrainCheck): Cohort Study

Abstract

Background: The US population over the age of 65 is expected to double by the year 2050. Concordantly, the incidence of dementia is projected to increase. The subclinical stage of dementia begins years before signs and symptoms appear. Early detection of cognitive impairment and/or cognitive decline may allow for interventions to slow its progression. Furthermore, early detection may allow for implementation of care plans that may affect the quality of life of those affected and their caregivers.

Objective: We sought to determine the accuracy and validity of BrainCheck Memory as a diagnostic aid for age-related cognitive impairment, as compared against physician diagnosis and other commonly used neurocognitive screening tests, including the Saint Louis University Mental Status (SLUMS) exam, the Mini-Mental State Examination (MMSE), and the Montreal Cognitive Assessment (MoCA).

Methods: We tested 583 volunteers over the age of 49 from various community centers and living facilities in Houston, Texas. The volunteers were divided into five cohorts: a normative population and four comparison groups for the SLUMS exam, the MMSE, the MoCA, and physician diagnosis. Each comparison group completed their respective assessment and BrainCheck Memory.

Results: A total of 398 subjects were included in the normative population. A total of 84 participants were in the SLUMS exam cohort, 51 in the MMSE cohort, 35 in the MoCA cohort, and 18 in the physician cohort. BrainCheck Memory assessments were significantly correlated to the SLUMS exam, with coefficients ranging from .5 to .7. Correlation coefficients for the MMSE and BrainCheck and the MoCA and BrainCheck were also significant. Of the 18 subjects evaluated by a physician, 9 (50%) were healthy, 6 (33%) were moderately impaired, and 3 (17%) were severely impaired. A significant difference was found between the severely and moderately impaired subjects and the healthy subjects (P=.02). We derived a BrainCheck Memory composite score that showed stronger correlations with the standard assessments as compared to the individual BrainCheck assessments. Receiver operating characteristic (ROC) curve analysis of this composite score found a sensitivity of 81% and a specificity of 94%.

Conclusions: BrainCheck Memory provides a sensitive and specific metric for age-related cognitive impairment in older adults, with the advantages of a mobile, digital, and easy-to-use test.

Trial registration: ClinicalTrials.gov NCT03608722; https://ichgcp.net/clinical-trials-registry/NCT03608722 (Archived by WebCite at http://www.webcitation.org/76JLoYUGf).

Keywords: Alzheimer’s disease; BrainCheck; computerized cognitive assessment; dementia; digital cognitive assessment; digital testing; electronic neurocognitive tools; mild cognitive impairment (MCI); neurocognitive computerized assessment tools (NCAT); neurocognitive tests.

Conflict of interest statement

Conflicts of Interest: BrainCheck Inc provided personal fees in the form of annual salaries for the authors BF, WD, KMSR, YK, and DME; fees for consulting were provided to SG.

©Samantha Groppell, Karina M Soto-Ruiz, Benjamin Flores, William Dawkins, Isabella Smith, David M Eagleman, Yael Katz. Originally published in JMIR Aging (http://aging.jmir.org), 21.03.2019.

Figures

Figure 1

Normative distribution. Distributions of scores for individuals in the normative population are shown for each assessment. The number of normative data points in each distribution is indicated above each panel.

Figure 2

Comparison of BrainCheck assessments with the Saint Louis University Mental Status (SLUMS) exam. Shown are comparisons between SLUMS scores and the scores for each assessment. Each data point represents one participant who took both assessments. Pearson correlation coefficients are indicated above each panel.

Figure 3

Comparison of BrainCheck assessments with the Mini-Mental State Examination (MMSE). Shown are comparisons between MMSE scores and the scores for each assessment. Each data point represents one participant who took both assessments. Pearson correlation coefficients are indicated above each panel.

Figure 4

Comparison of BrainCheck assessments with the Montreal Cognitive Assessment (MoCA). Shown are comparisons between MoCA scores and the scores for each assessment. Each data point represents one participant who took both assessments. Pearson correlation coefficients are indicated above each panel.

Figure 5

Comparison of BrainCheck assessments with physician diagnosis. Shown are mean scores on each assessment for patients classified as healthy or impaired by a physician. P values determined by a two-sided t test are given above each panel.

Figure 6

Comparison between BrainCheck composite score and the Saint Louis University Mental Status (SLUMS) exam.

Figure 7

Comparison between BrainCheck composite score and the Mini-Mental State Examination (MMSE).

Figure 8

Comparison between BrainCheck composite score and the Montreal Cognitive Assessment (MoCA).

Figure 9

Receiver operating characteristic (ROC) curve for comparison between the physician diagnosis and the BrainCheck composite score.

Figure 10

Receiver operating characteristic (ROC) curve for comparison between the Saint Louis University Mental Status (SLUMS) test (cutoff 21) and the BrainCheck composite score.