DOI: 10.1093/ofid/ofad592 ISSN: 2328-8957

An automated virtual reality program accurately diagnoses HIV-associated neurocognitive disorders in older people with HIV

Raeanne C Moore, Kevin S Kuehn, Anne Heaton, Erin E Sundermann, Laura M Campbell, Peter Torre, Anya Umlauf, David J Moore, Nicole Kosoris, David W Wright, Michelle C LaPlaca, Drenna Waldrop, Albert M Anderson
  • Infectious Diseases
  • Oncology

Abstract

Background

HIV-associated neurocognitive disorders (HAND) remain prevalent despite antiretroviral therapy (ART), particularly among older people with HIV (PWH). However, the diagnosis of HAND is labor intensive and requires expertise to administer neuropsychological tests. Our prior pilot work established the feasibility and accuracy of a computerized, self-administered virtual reality program (DETECT) to measure cognition in younger PWH. The present study expands this to a larger sample of older PWH.

Methods

We enrolled PWH who were >60 years old, on ART, with undetectable plasma viral loads, and without significant neuropsychological confounds. HAND status was determined via Frascati criteria. Regression models that controlled for demographic differences (age, sex, education, race/ethnicity) examined the association between DETECT’s cognition module and both HAND status and Global Deficit Scores (GDS) derived via traditional neuropsychological tests.

Results

Seventy-nine PWH (mean age=66 years, 28% women) completed a comprehensive neuropsychological battery and DETECT’s cognition module. Twenty-five (32%) had HAND based on the comprehensive battery. A significant correlation was found between the DETECT cognition module and the neuropsychological battery (r=.45, p<.001). Furthermore, in two separate regression models HAND status (b=-.79, p<.001) and GDS impairment status (b=-.83, p<.001) significantly predicted DETECT performance. Area under the curve values for DETECT were.78 for differentiating participants by HAND status (HAND vs. no-HAND) and.85 for detecting GDS impairment.

Conclusions

The DETECT cognition module provides a novel means to identify cognitive impairment in older PWH. As DETECT is fully-immersive and self-administered, this virtual reality tool holds promise as a scalable cognitive screening battery.

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