Patterns and Predictors of Cognitive Function Among Virally Suppressed Women With HIV

Cognitive impairment remains frequent and heterogeneous in presentation and severity among virally suppressed (VS) women with HIV (WWH). We identified cognitive profiles among 929 VS-WWH and 717 HIV-uninfected women from 11 Women's Interagency HIV Study sites at their first neuropsychological (...

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Vydáno v:Frontiers in neurology Ročník 12; s. 604984
Hlavní autoři: Dastgheyb, Raha M., Buchholz, Alison S., Fitzgerald, Kathryn C., Xu, Yanxun, Williams, Dionna W., Springer, Gayle, Anastos, Kathryn, Gustafson, Deborah R., Spence, Amanda B., Adimora, Adaora A., Waldrop, Drenna, Vance, David E., Milam, Joel, Bolivar, Hector, Weber, Kathleen M., Haughey, Norman J., Maki, Pauline M., Rubin, Leah H.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Switzerland Frontiers Media S.A 11.02.2021
Témata:
cognition
heterogeneity
HIV
Neurology
phenotypes
random forest
women
phenotypes
HIV
cognition
random forest
machine learning
heterogeneity
women
ISSN:1664-2295, 1664-2295
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Shrnutí:Cognitive impairment remains frequent and heterogeneous in presentation and severity among virally suppressed (VS) women with HIV (WWH). We identified cognitive profiles among 929 VS-WWH and 717 HIV-uninfected women from 11 Women's Interagency HIV Study sites at their first neuropsychological (NP) test battery completion comprised of: Hopkins Verbal Learning Test-Revised, Trail Making, Symbol Digit Modalities, Grooved Pegboard, Stroop, Letter/Animal Fluency, and Letter-Number Sequencing. Using 17 NP performance metrics (T-scores), we used Kohonen self-organizing maps to identify patterns of high-dimensional data by mapping participants to similar nodes based on T-scores and clustering those nodes. Among VS-WWH, nine clusters were identified (entropy = 0.990) with four having average T-scores ≥45 for all metrics and thus combined into an “unimpaired” profile ( n = 311). Impaired profiles consisted of weaknesses in: (1) sequencing ( Profile-1 ; n = 129), (2) speed ( Profile-2 ; n = 144), (3) learning + recognition ( Profile-3 ; n = 137), (4) learning + memory ( Profile-4 ; n = 86), and (5) learning + processing speed + attention + executive function ( Profile-5 ; n = 122). Sociodemographic, behavioral, and clinical variables differentiated profile membership using Random Forest models. The top 10 variables distinguishing the combined impaired vs. unimpaired profiles were: clinic site, age, education, race, illicit substance use, current and nadir CD4 count, duration of effective antiretrovirals, and protease inhibitor use. Additional variables differentiating each impaired from unimpaired profile included: depression, stress-symptoms, income ( Profile-1 ); depression, employment ( Profile 2 ); depression, integrase inhibitor (INSTI) use ( Profile-3 ); employment, INSTI use, income, atazanavir use, non-ART medications with anticholinergic properties ( Profile-4 ); and marijuana use ( Profile-5 ). Findings highlight consideration of NP profile heterogeneity and potential modifiable factors contributing to impaired profiles.
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This article was submitted to Neuroinfectious Diseases, a section of the journal Frontiers in Neurology
Edited by: Pankaj Seth, National Brain Research Centre (NBRC), India
Reviewed by: Robert Paul, University of Missouri–St. Louis, United States; Walter Royal III, Morehouse School of Medicine, United States
ISSN:1664-2295
1664-2295
DOI:10.3389/fneur.2021.604984