Payal B Patel1, Tanakorn Apornpong2, Thanyawee Puthanakit3,4, Kulvadee Thongpibul5, Pope Kosalaraksa6, Rawiwan Hansudewechakul7, Suparat Kanjanavanit8, Chiawat Ngampiyaskul9, Wicharn Luesomboon10, Jurai Wongsawat11, Ly Penh Sun12, Kea Chettra12, Vonthanak Saphonn13, Claude A Mellins14, Kathleen Malee15, Serena Spudich1, Jintanat Ananworanich16,17, Stephen J Kerr6, Robert Paul18. 1. From the Department of Neurology, Yale University, New Haven, Connecticut. 2. Department of Statistics, HIV-NAT, The Thai Red Cross AIDS Research Center, Bangkok, Thailand. 3. Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand. 4. Center of Excellence in Pediatric Infectious Diseases and Vaccines, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand. 5. Department of Psychology, Faculty of Humanities, Chiang Mai University, Chiang Mai, Thailand. 6. Department of Pediatrics, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand. 7. Department of Pediatrics, Infectious Diseases, Chiangrai Prachanukroh Hospital, Chiang Rai, Thailand. 8. Department of Pediatrics, Infectious Diseases, Nakornping Hospital, Chiang Mai, Thailand. 9. Prapokklao Hospital, Chantaburi, Thailand. 10. Department of Pediatrics, Infectious Diseases, Queen Savang Vadhana Memorial Hospital, Chonburi, Thailand. 11. Department of Pediatrics, Infectious Diseases, Bamrasnaradura Infectious Diseases Institute, Nonthaburi, Thailand. 12. Department of Infectious Diseases, Department of Infectious Diseases, National Center for HIV/AIDS Dermatology and STDs, Phnom Penh, Cambodia. 13. Department of Pediatrics, Infectious Diseases, University of Health Sciences, Phnom Pehn, Cambodia. 14. Department of Medical Psychology, HIV Center for Clinical and Behavioral Studies, New York State Psychiatric Institute, and Columbia University, New York, New York. 15. Northwestern University Feinberg School of Medicine, Department of Psychiatry and Behavioral Science, Chicago, Illinois. 16. Department of HIV Therapeutics Research, The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, Maryland. 17. Department of Global Health, University of Amsterdam, Amsterdam, The Netherlands. 18. Missouri Institute of Mental Health, University of Missouri-St. Louis, St. Louis, Missouri.
Abstract
BACKGROUND: Children with perinatal HIV (pHIV) may display distinct long-term cognitive phenotypes. We used group-based trajectory modeling to identify clusters of children with pHIV after similar developmental trajectories and predictors of belonging to select cognitive trajectory groups. METHODS: Participants included children, 4-17 years of age, with pHIV in Thailand and Cambodia. Cognitive measures included translated versions of Intelligence Quotient tests, Color Trails Tests and Beery-Buktenica Developmental Test of Visual-Motor Integration conducted semiannually over 3-6 years. The best fit of trajectory groups was determined using maximum likelihood estimation. Multivariate logistic regression identified baseline factors associated with belonging to the lowest scoring trajectory group. RESULTS: Group-based trajectory analyses revealed a 3-cluster classification for each cognitive test, labeled as high, medium and low scoring groups. Most trajectory group scores remained stable across age. Verbal IQ declined in all 3 trajectory groups and the high scoring group for Children's Color Trails Test 1 and 2 showed an increase in scores across age. Children in the lowest scoring trajectory group were more likely to present at an older age and report lower household income. CONCLUSIONS: Group-based trajectory modeling succinctly classifies cohort heterogeneity in cognitive outcomes in pHIV. Most trajectories remained stable across age suggesting that cognitive potential is likely determined at an early age with the exception of a small subgroup of children who displayed developmental gains in select cognitive domains and may represent those with better cognitive reserve. Poverty and longer duration of untreated HIV may predispose children with pHIV to suboptimal cognitive development.
BACKGROUND:Children with perinatal HIV (pHIV) may display distinct long-term cognitive phenotypes. We used group-based trajectory modeling to identify clusters of children with pHIV after similar developmental trajectories and predictors of belonging to select cognitive trajectory groups. METHODS:Participants included children, 4-17 years of age, with pHIV in Thailand and Cambodia. Cognitive measures included translated versions of Intelligence Quotient tests, Color Trails Tests and Beery-Buktenica Developmental Test of Visual-Motor Integration conducted semiannually over 3-6 years. The best fit of trajectory groups was determined using maximum likelihood estimation. Multivariate logistic regression identified baseline factors associated with belonging to the lowest scoring trajectory group. RESULTS: Group-based trajectory analyses revealed a 3-cluster classification for each cognitive test, labeled as high, medium and low scoring groups. Most trajectory group scores remained stable across age. Verbal IQ declined in all 3 trajectory groups and the high scoring group for Children's Color Trails Test 1 and 2 showed an increase in scores across age. Children in the lowest scoring trajectory group were more likely to present at an older age and report lower household income. CONCLUSIONS: Group-based trajectory modeling succinctly classifies cohort heterogeneity in cognitive outcomes in pHIV. Most trajectories remained stable across age suggesting that cognitive potential is likely determined at an early age with the exception of a small subgroup of children who displayed developmental gains in select cognitive domains and may represent those with better cognitive reserve. Poverty and longer duration of untreated HIV may predispose children with pHIV to suboptimal cognitive development.
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