Neurocognitive Performance Profiling in People Living with HIV

• Author / Creator

  Gomez, Daniela Isabel

• Despite the wide availability of effective antiretroviral therapy (ART), neurocognitive problems persist in over 20% of people living with HIV. Neurocognitive problems are highly heterogeneous in HIV, and the underlying etiology of neurocognitive impairment (NCI) is multifactorial. The heterogeneity of NCI in HIV may not be fully captured by the current clinical staging criteria for HIV-associated neurocognitive disorders (HAND). Given the multifactorial nature of NCI, multiple neurocognitive impairment profiles associated with distinct risk-factors may exist. Here, we investigated the neurocognitive performance of 381 HIV-positive participants from the Southern Alberta HIV clinic (SAC) cohort to identify different neurocognitive impairment profiles and their associated risk-factors. Neurocognitive performance was assessed by multi-domain neuropsychological test battery. We implemented Latent Profile Analysis (LPA) to analyze performance and empirically define neurocognitive profiles. Random Forest Analysis (RFA), a machine learning technique, was applied to identify the most important factors associated with these profiles. Three profiles emerged from the LPA: Profile 1 (P1, n=159) achieved the highest performance, while Profile 2 (P2, n=163) had lowered executive functions and verbal memory, and Profile 3 (P3, n=59) was globally impaired. RFA achieved good prediction (area-under-the-curve ≥ 0.80) only for global impairment (P3). Non-North American descent was the dominant predictor of P3, followed by factors coinciding with non-North American descent (female sex and toxoplasma seropositivity). Additional predictors included unemployment, current depressive symptoms, lower nadir CD4, and longstanding HIV. Restricting analyses to North Americans pointed to the additional importance of ART achieving high CSF levels, and older age in prediction of P3. HAND diagnoses were most common in the globally impaired profile (P3=89.8%), followed by the group with reduced higher-order neurocognitive performance (P2=16.6%). Implementation of LPA and RFA empirically distinguished three distinct neurocognitive performance profiles in this cohort while also highlighting potential risk factors and their relative importance to neurocognitive impairment. These data-driven analytical methods pointed to discernible demographic, HIV- and treatment-related risk-factor constellations in patients born outside and within North America that might influence diagnostic and therapeutic decisions.

• Subjects / Keywords

  • Neuropsychology
  • HIV
  • Machine Learning
  • Neurocognitive profiling

• Graduation date

  Fall 2019

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/r3-69sj-w277

• License

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