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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 A. Pérez Álvarez, Núria Muñoz Murillo, Amalia Prats, Anna Garolera i Freixa, Maite Jurado, Ma. Ángeles (María Ángeles) Fumaz, Carmina Negredo, Eugènia Ferrer, María Jesus Clotet, Bonaventura, 1953- |
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 |
URI: | http://hdl.handle.net/2445/113703 |
Related resource: | https://doi.org/10.1371/journal.pone.0107625 |
ISSN: | 1932-6203 |
Appears in Collections: | Articles publicats en revistes (Psicologia Clínica i Psicobiologia) |
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