Web of Science: 15 citations, Scopus: 14 citations, Google Scholar: citations,
Classification models for neurocognitive impairment in HIV Infection based on demographic and clinical variables
Muñoz-Moreno, Jose Antonio (Institut Germans Trias i Pujol. Institut de Recerca de la Sida IrsiCaixa)
Pérez-Álvarez, Núria (Institut Germans Trias i Pujol. Fundació de Lluita Contra la Sida)
Muñoz-Murillo, Amalia (Universitat de Barcelona)
Prats, Anna (Institut Germans Trias i Pujol. Fundació de Lluita Contra la Sida)
Garolera i Freixa, Maite (Consorci Sanitari Hospital de Terrassa)
Jurado, Ma. Ángeles (María Ángeles) (Universitat de Barcelona)
Fumaz, Carmina R. (Rodríguez Fumaz) (Institut Germans Trias i Pujol. Fundació de Lluita Contra la Sida)
Negredo Puigmal, Eugènia (Institut Germans Trias i Pujol. Fundació de Lluita Contra la Sida)
Ferrer, Maria J. (Institut Germans Trias i Pujol. Fundació de Lluita Contra la Sida)
Clotet, Bonaventura (Institut Germans Trias i Pujol. Fundació de Lluita Contra la Sida)
Universitat Autònoma de Barcelona

Date: 2014
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-naïve and treatment-experienced patients. Results: The study sample comprised 52 treatment-naïve 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.
Rights: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original. Creative Commons
Language: Anglès
Document: article ; recerca ; publishedVersion
Subject: Antiretroviral therapy ; Demography ; Drug therapy ; HIV diagnosis and management ; HIV infections ; Intelligence tests ; Neuropsychological testing ; Viral load
Published in: PloS one, Vol. 9 Issue 9 (September 2014) , p. e107625, ISSN 1932-6203

DOI: 10.1371/journal.pone.0107625
PMID: 25237895

7 p, 502.3 KB

The record appears in these collections:
Research literature > UAB research groups literature > Research Centres and Groups (scientific output) > Health sciences and biosciences > Institut d'Investigació en Ciencies de la Salut Germans Trias i Pujol (IGTP)
Articles > Research articles
Articles > Published articles

 Record created 2015-11-04, last modified 2021-02-21

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