Metabolic Risk Factors as Differential Predictors of Profiles of Neurocognitive Impairment Among Older HIV plus and HIV- Adults: An Observational Study

被引:15
|
作者
Pasipanodya, Elizabeth C. [1 ]
Montoya, Jessica L. [2 ]
Campbell, Laura M. [3 ]
Hussain, Mariam A. [3 ]
Saloner, Rowan [3 ]
Paolillo, Emily M. [3 ]
Jeste, Dilip, V [4 ]
Letendre, Scott L. [2 ]
McCutchan, J. Allen [2 ]
Heaton, Robert K. [2 ]
Moore, David J. [2 ]
机构
[1] Santa Clara Valley Med Ctr, Rehabil Res Ctr, San Jose, CA 95128 USA
[2] Univ Calif San Diego, HIV Neurobehav Res Program, 220 Dickinson St,MC8231, San Diego, CA 92103 USA
[3] San Diego State Univ Univ Calif, San Diego Joint Doctoral Program Clin Psychol, San Diego, CA USA
[4] Univ Calif San Diego, Sam & Rose Stein Inst Aging, La Jolla, CA 92093 USA
关键词
HIV; neurocognitive impairment; metabolic syndrome; latent class analysis; LATENT CLASS; NEUROPSYCHOLOGICAL IMPAIRMENT; COGNITIVE IMPAIRMENT; INFECTED PATIENTS; CENTRAL OBESITY; DEFICIT SCORES; DEMENTIA; DISORDERS; INFLAMMATION; PERFORMANCE;
D O I
10.1093/arclin/acz040
中图分类号
B849 [应用心理学];
学科分类号
040203 ;
摘要
Objective: Neurocognitive performance among older persons, including those living with HIV (people living with HIV [PLWH]), exhibits significant heterogeneity, suggesting subpopulations with differing profiles of neurocognitive impairment (NCI). Metabolic factors are associated with NCI, but their relationships to cluster-derived NCI profiles are unknown. Method: Participants (144 PLWH and 102 HIV uninfected) aged 50+ years completed a neuropsychological battery assessing seven cognitive domains. Latent class analysis (LCA) identified NCI profiles separately by HIV serostatus and in a combined sample. Obtained classes were examined against the Montreal Cognitive Assessment (MoCA) and diagnoses of HIV-associated neurocognitive disorders (HAND). Multinomial regression identified metabolic predictors of classification. Results: LCA identified three latent classes in each participant sample: Class1(Multidomain NCI) (high probability of impairment across multiple domains), Class 2(Learning & Recall NCI) (high probability of impairment in learning and recall), and Class 3NC Unimpaired (low probability of NCI across all domains). Severity of NCI implied by classes corresponded with MoCA scores and HAND diagnoses. In analyses on the combined sample, compared to HIV-uninfected individuals, PLWH were more likely to be in Class1(Multidomain NCI). Among PLWH, those with dyslipidemia and hypertension had greater odds of classification in Class 1(Multidomain NCI) while those with central obesity had higher odds of classification in Class2(Learning & Recall NCI); metabolic syndrome approached significance as a differential predictor. Regardless of HIV status, individuals with diabetes were more likely to be in Class 1(Multidomain NCI). Conclusions: Metabolic risk factors confer heightened risk of NCI in HIV infection. Interventions to reduce metabolic risk may improve neurocognitive outcomes among PLWH.
引用
收藏
页码:151 / 164
页数:14
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