Machine-learning classification of neurocognitive performance in children with perinatal HIV initiating de novo antiretroviral therapy.
Journal
AIDS (London, England)
ISSN: 1473-5571
Titre abrégé: AIDS
Pays: England
ID NLM: 8710219
Informations de publication
Date de publication:
01 04 2020
01 04 2020
Historique:
pubmed:
3
1
2020
medline:
20
2
2021
entrez:
3
1
2020
Statut:
ppublish
Résumé
To develop a predictive model of neurocognitive trajectories in children with perinatal HIV (pHIV). Machine learning analysis of baseline and longitudinal predictors derived from clinical measures utilized in pediatric HIV. Two hundred and eighty-five children (ages 2-14 years at baseline; Mage = 6.4 years) with pHIV in Southeast Asia underwent neurocognitive assessment at study enrollment and twice annually thereafter for an average of 5.4 years. Neurocognitive slopes were modeled to establish two subgroups [above (n = 145) and below average (n = 140) trajectories). Gradient-boosted multivariate regressions (GBM) with five-fold cross validation were conducted to examine baseline (pre-ART) and longitudinal predictive features derived from demographic, HIV disease, immune, mental health, and physical health indices (i.e. complete blood count [CBC]). The baseline GBM established a classifier of neurocognitive group designation with an average AUC of 79% built from HIV disease severity and immune markers. GBM analysis of longitudinal predictors with and without interactions improved the average AUC to 87 and 90%, respectively. Mental health problems and hematocrit levels also emerged as salient features in the longitudinal models, with novel interactions between mental health problems and both CD4 cell count and hematocrit levels. Average AUCs derived from each GBM model were higher than results obtained using logistic regression. Our findings support the feasibility of machine learning to identify children with pHIV at risk for suboptimal neurocognitive development. Results also suggest that interactions between HIV disease and mental health problems are early antecedents to neurocognitive difficulties in later childhood among youth with pHIV.
Identifiants
pubmed: 31895148
doi: 10.1097/QAD.0000000000002471
pmc: PMC7072001
mid: NIHMS1549667
pii: 00002030-202004010-00010
doi:
Banques de données
ClinicalTrials.gov
['NCT00234091']
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
737-748Subventions
Organisme : NIAID NIH HHS
ID : U19 AI053741
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH102151
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH089722
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH108559
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI075408
Pays : United States
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