Affiliation:
1. McGill University Montreal Quebec Canada
2. MoCA Cognition Greenfield Park Quebec Canada
3. Harvard T.H. Chan School of Public Health Boston Massachusetts USA
4. Chambers‐Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences University of Nevada Las Vegas Las Vegas Nevada USA
Abstract
AbstractBackgroundThe need for cognitive testing is increasing with the aging population and the advent of new Alzheimer disease therapies. To respond to the increased demand, the XpressO was developed as a self‐administered digital cognitive prescreening tool that will help distinguish between populations of subjective and objective cognitive impairment according to the Montreal Cognitive Assessment (MoCA).MethodsThis is a prospective validation study. XpressO is composed of tasks that assess memory and executive functions. It is validated compared to the digital MoCA as a gold standard. Out of 118 participants screened from the MoCA Clinic and a family practice clinic, 88 met inclusion criteria, two participants had missing data due to incomplete tasks, 86 participants were included in the analysis; the mean age was 70.34 years. A logistic regression model was built, and its accuracy was evaluated by the sensitivity, specificity, and Area Under the Curve (AUC) of the Receiver Operating Characteristic.ResultsAnalysis showed strong correlation between (1) XpressO memory tasks scores and the MoCA Memory Index Score (p‐values < 0.001), and between (2) XpressO sub‐test scores and MoCA total score (p‐values < 0.005). The AUC for predicting MoCA performance is 0.845. To classify individuals with normal and abnormal MoCA scores, two threshold values were introduced for the total XpressO scores: sensitivity of 91% at a cutoff of 72, specificity of 90% at a cutoff of 42, and an undetermined range in between.ConclusionXpressO demonstrated high AUC, high sensitivity and specificity to predict cognitive performance compared to the digital MoCA. It may provide efficient cognitive prescreening by identifying individuals who would benefit from further clinical assessments, potentially reducing waiting times and high burden on healthcare clinics.