Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/113703
Title: Classification Models for Neurocognitive Impairment in HIV Infection Based on Demographic and Clinical Variables
Author: Muñoz Moreno, José
Pérez Álvarez, Núria
Muñoz Murillo, Amalia
Prats, Anna
Garolera i Freixa, Maite
Jurado, Ma. Ángeles (María Ángeles)
Fumaz, Carmina
Negredo, Eugenia
Ferrer, María J.
Clotet, Bonaventura
Keywords: Infeccions per VIH
Antiretrovirals
Tests neuropsicològics
HIV infections
Antiretroviral agents
Neuropsychological tests
Issue Date: Sep-2014
Publisher: Public Library of Science (PLoS)
Abstract: Objective: We used demographic and clinical data to design practical classification models for prediction of neurocognitive impairment (NCI) in people with HIV infection. Methods: The study population comprised 331 HIV-infected patients with available demographic, clinical, and neurocognitive data collected using a comprehensive battery of neuropsychological tests. Classification and regression trees (CART) were developed to obtain detailed and reliable models to predict NCI. Following a practical clinical approach, NCI was considered the main variable for study outcomes, and analyses were performed separately in treatment-naı¨ve and treatment-experienced patients. Results: The study sample comprised 52 treatment-naı¨ve and 279 experienced patients. In the first group, the variables identified as better predictors of NCI were CD4 cell count and age (correct classification [CC]: 79.6%, 3 final nodes). In treatment-experienced patients, the variables most closely related to NCI were years of education, nadir CD4 cell count, central nervous system penetration-effectiveness score, age, employment status, and confounding comorbidities (CC: 82.1%, 7 final nodes). In patients with an undetectable viral load and no comorbidities, we obtained a fairly accurate model in which the main variables were nadir CD4 cell count, current CD4 cell count, time on current treatment, and past highest viral load (CC: 88%, 6 final nodes). Conclusion: Practical classification models to predict NCI in HIV infection can be obtained using demographic and clinical variables. An approach based on CART analyses may facilitate screening for HIV-associated neurocognitive disorders and complement clinical information about risk and protective factors for NCI in HIV-infected patients.
Note: Reproducció del document publicat a: https://doi.org/10.1371/journal.pone.0107625
It is part of: PLoS One, 2014, vol. 9, num. 9, p. e107625
Related resource: https://doi.org/10.1371/journal.pone.0107625
URI: http://hdl.handle.net/2445/113703
ISSN: 1932-6203
Appears in Collections:Articles publicats en revistes (Psicologia Clínica i Psicobiologia)

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