H38 A new approach to digitized cognitive monitoring: validity of the selfcog in Huntington’s disease

Abstract

<h3>Background</h3> Cognitive deficits represent a hallmark of Huntington’s disease (HD) but evaluating their progression is complex. We developed the SelfCog, a digitized battery that tests motor, executive, visuospatial, language and memory functions in 15 minutes. Based on neuroscience principles, all cognitive functions are tested according to the same paradigm. A randomization algorithm provides a new test at each assessment. <h3>Aims</h3> We assessed its validity, reliability, and sensitivity to detect decline in early-stage HD in a prospective and international multilingual study (France, United Kingdom, and Germany). <h3>Methods</h3> Fifty-one out of 85 participants with HD and 40 of 52 healthy controls included at baseline were followed up for one year. We estimated associations between each of the classical clinical assessments and SelfCog using Pearson’s correlation and proneness to retest effects and sensitivity to decline through Linear Mixed Models. Longitudinal effect sizes were estimated for each cognitive score. Voxel-based morphometry and Tract-Based Spatial Statistics analyses were conducted to assess the consistency between performance and decline on the SelfCog and MRI 3D-T1 and diffusion weighted imaging. <h3>Results</h3> The SelfCog detected the decline of patients with HD in a one-year follow-up period with satisfactory psychometric properties. The SelfCog showed larger effect sizes than the classical cognitive assessments. Its scores were associated with grey and white matter damage at baseline and over one year. <h3>Conclusions</h3> The SelfCog should likely become a very useful tool for measuring cognition in HD in the future. It highlights the value of moving the field along the neuroscience principles.