Longitudinal Cognitive Outcomes in Children With HIV in Zambia: 2-Year Outcomes From the HIV-Associated Neurocognitive Disorders in Zambia (HANDZ) Study.
Journal
Journal of acquired immune deficiency syndromes (1999)
ISSN: 1944-7884
Titre abrégé: J Acquir Immune Defic Syndr
Pays: United States
ID NLM: 100892005
Informations de publication
Date de publication:
01 10 2022
01 10 2022
Historique:
received:
22
04
2022
accepted:
20
06
2022
entrez:
12
9
2022
pubmed:
13
9
2022
medline:
15
9
2022
Statut:
ppublish
Résumé
To describe longitudinal outcomes and predictors of cognitive outcomes in children with HIV in Zambia. Multiple studies have shown that children with HIV are at risk for impaired cognition. However, there are limited data on longitudinal cognitive outcomes in children with HIV. We conducted a prospective cohort study of 208 perinatally infected children with HIV ages 8-17 years, all treated with antiretroviral therapy, and 208 HIV-exposed uninfected controls. Participants were followed for 2 years. Cognition was assessed with a custom NIH Toolbox Cognition Battery, and tests were combined to generate a Summary Cognition Score (SCS). The contribution of potential risk factors to outcomes was explored using regression models and group-based trajectory modeling. HIV was strongly associated with lower SCS at baseline [β-14, 95% confidence interval (CI): -20 to -7, P < 0.001]. Change scores over time were similar between groups, but poorer average performance in children with HIV persisted at the 2-year follow-up visit (adjusted β = -11, 95% CI: -22 to -0.3, P = 0.04). Other than HIV, the strongest predictors of baseline SCS included socioeconomic status index (β =3, 95% CI: 1, 5, P = 0.004), history of growth stunting (β=-14, 95% CI: -23 to -6, P = 0.001), history of CD4 count below 200 (β = -19, 95% CI: -35 to -2, P = 0.02), and history of World Health Organization stage 4 disease (β = -10, 95% CI: -19 to -0.2, P = 0.04). In the group-based trajectory model, HIV+ status predicted membership in the lowest performing trajectory group (odds ratio 2.5, 95% CI: 1.2 to 5.1, P = 0.01). Children with HIV are at risk of poor cognitive outcomes, despite chronic treatment with antiretroviral therapy.
Sections du résumé
OBJECTIVE
To describe longitudinal outcomes and predictors of cognitive outcomes in children with HIV in Zambia.
BACKGROUND
Multiple studies have shown that children with HIV are at risk for impaired cognition. However, there are limited data on longitudinal cognitive outcomes in children with HIV.
METHODS
We conducted a prospective cohort study of 208 perinatally infected children with HIV ages 8-17 years, all treated with antiretroviral therapy, and 208 HIV-exposed uninfected controls. Participants were followed for 2 years. Cognition was assessed with a custom NIH Toolbox Cognition Battery, and tests were combined to generate a Summary Cognition Score (SCS). The contribution of potential risk factors to outcomes was explored using regression models and group-based trajectory modeling.
RESULTS
HIV was strongly associated with lower SCS at baseline [β-14, 95% confidence interval (CI): -20 to -7, P < 0.001]. Change scores over time were similar between groups, but poorer average performance in children with HIV persisted at the 2-year follow-up visit (adjusted β = -11, 95% CI: -22 to -0.3, P = 0.04). Other than HIV, the strongest predictors of baseline SCS included socioeconomic status index (β =3, 95% CI: 1, 5, P = 0.004), history of growth stunting (β=-14, 95% CI: -23 to -6, P = 0.001), history of CD4 count below 200 (β = -19, 95% CI: -35 to -2, P = 0.02), and history of World Health Organization stage 4 disease (β = -10, 95% CI: -19 to -0.2, P = 0.04). In the group-based trajectory model, HIV+ status predicted membership in the lowest performing trajectory group (odds ratio 2.5, 95% CI: 1.2 to 5.1, P = 0.01).
CONCLUSIONS
Children with HIV are at risk of poor cognitive outcomes, despite chronic treatment with antiretroviral therapy.
Identifiants
pubmed: 36094489
doi: 10.1097/QAI.0000000000003052
pii: 00126334-202210010-00015
pmc: PMC9480865
mid: NIHMS1819987
doi:
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
217-225Subventions
Organisme : NINDS NIH HHS
ID : K23 NS117310
Pays : United States
Organisme : NINDS NIH HHS
ID : L40 NS080264
Pays : United States
Organisme : NIAID NIH HHS
ID : P30 AI045008
Pays : United States
Informations de copyright
Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.
Déclaration de conflit d'intérêts
The authors have no conflicts of interest to disclose.
Références
UNAIDS 2021. Global HIV. AIDS Statistics—Fact Sheet. Available at: https://www.unaids.org/en/resources/fact-sheet . Accessed December 04, 2022.
Danforth K, Granich R, Wiedeman D, et al. Global mortality and morbidity of HIV/AIDS. In: Major Infectious Diseases. Washington, DC: The International Bank for Reconstruction and Development/The World Bank; 2017.
Health ZMO. Zambia National Health Strategic Plan, 2017–2021. Lusaka, Zambia: Ministry of Health; 2017.
Bearden DR, Ciccone O, Patel AA. Global health: pediatric neurology. Semin Neurol. 2018;38:200–207.
Thakur KT, Boubour A, Saylor D, et al. Global HIV neurology: a comprehensive review. AIDS. 2019;33:163–184.
Nachman SA, Chernoff M, Gona P, et al.; PACTG 219C Team. Incidence of noninfectious conditions in perinatally HIV-infected children and adolescents in the HAART era. Arch Pediatr Adolesc Med. 2009;163:164–171.
Phillips N, Amos T, Kuo C, et al. HIV-associated cognitive impairment in perinatally infected children: a meta-analysis. Pediatrics. 2016;138:e20160893.
Boivin MJ, Barlow-Mosha L, Chernoff MC, et al.; IMPAACT P1104s Study Team. Neuropsychological performance in African children with HIV enrolled in a multisite antiretroviral clinical trial. AIDS. 2018;32:189–204.
Cohen S, Ter Stege JA, Geurtsen GJ, et al. Poorer cognitive performance in perinatally HIV-infected children versus healthy socioeconomically matched controls. Clin Infect Dis. 2015;60:1111–1119.
Dean O, Buda A, Adams HR, et al. Brain magnetic resonance imaging findings associated with cognitive impairment in children and adolescents with human immunodeficiency Virus in Zambia. Pediatr Neurol. 2020;102:28–35.
Epstein LG, Sharer LR. Neurological manifestations of perinatally acquired HIV-1 infection. Semin Pediatr Neurol. 1994;1:50–57.
Foley J, Ettenhofer M, Wright M, Hinkin CH. Emerging issues in the neuropsychology of HIV infection. Curr HIV/AIDS Rep. 2008;5:204–211.
Hoare J, Phillips N, Joska JA, et al. Applying the HIV-associated neurocognitive disorder diagnostic criteria to HIV-infected youth. Neurology. 2016;87:86–93.
Hoare J, Myer L, Heany S, et al. Cognition, structural brain changes, and systemic inflammation in adolescents living with HIV on antiretroviral therapy. J Acquir Immune Defic Syndr. 2020;84:114–121.
Kapetanovic S, Griner R, Zeldow B, et al.; Pediatric HIV/AIDS Cohort Study Team. Biomarkers and neurodevelopment in perinatally HIV-infected or exposed youth: a structural equation model analysis. AIDS. 2014;28:355–364.
Koekkoek S, de Sonneville LMJ, Wolfs TFW, et al. Neurocognitive function profile in HIV-infected school-age children. Eur J Paediatr Neurol. 2008;12:290–297.
Laughton B, Cornell M, Boivin M, Van Rie A. Neurodevelopment in perinatally HIV-infected children: a concern for adolescence. J Int AIDS Soc. 2013;16:18603.
McHenry MS, McAteer CI, Oyungu E, et al. Neurodevelopment in young children born to HIV-infected mothers: a meta-analysis. Pediatrics. 2018;141:e20172888.
Mintz M. Neurological and developmental problems in pediatric HIV infection. J Nutr. 1996;126:2663S–2673S.
Molinaro M, Adams HR, Mwanza-Kabaghe S, et al. Evaluating the relationship between depression and cognitive function among children and adolescents with HIV in Zambia. AIDS Behav. 2021;25:2669–2679.
Smith R, Chernoff M, Williams PL, et al.; Pediatric HIV/AIDS Cohort Study PHACS Team. Impact of HIV severity on cognitive and adaptive functioning during childhood and adolescence. Pediatr Infect Dis J. 2012;31:592–598.
Smith R, Wilkins M. Perinatally acquired HIV infection: long-term neuropsychological consequences and challenges ahead. Child Neuropsychol. 2015;21:234–268.
Malee KM, Chernoff MC, Sirois PA, et al.; Memory and Executive Functioning Study of the Pediatric HIV/AIDS Cohort Study. Impact of perinatally acquired HIV disease upon longitudinal changes in memory and executive functioning (1999). J Acquir Immune Defic Syndr. 2017;75:455–464.
Patel PB, Apornpong T, Puthanakit T, et al.; PREDICT/Resilience Study Group. Trajectory analysis of cognitive outcomes in children with Perinatal HIV. Pediatr Infect Dis J. 2019;38:1038–1044.
Puthanakit T, Aurpibul L, Louthrenoo O, et al. Poor cognitive functioning of school-aged children in Thailand with perinatally acquired HIV infection taking antiretroviral therapy. AIDS Patient Care STDS. 2010;24:141–146.
Robbins RN, Zimmerman R, Korich R, et al. Longitudinal trajectories of neurocognitive test performance among individuals with perinatal HIV-infection and-exposure: adolescence through young adulthood. AIDS Care. 2020;32:21–29.
Van den Hof M, Ter Haar AM, Scherpbier HJ, et al. Neurocognitive development in perinatally human immunodeficiency virus-infected adolescents on long-term treatment, compared to healthy matched controls: a longitudinal study. Clin Infect Dis. 2020;70:1364–1371.
Boivin MJ, Chernoff M, Fairlie L, et al. African multi-site 2-year neuropsychological study of school-age children perinatally infected, exposed, and unexposed to human immunodeficiency Virus. Clin Infect Dis. 2020;71:e105–e114.
Wyhe KSV, Laughton B, Cotton MF, et al. Cognitive outcomes at ages seven and nine years in South African children from the children with HIV early antiretroviral (CHER) trial: a longitudinal investigation. J Int AIDS Soc. 2021;24:e25734.
Bearden DR, Meyer AC. Should the Frascati criteria for HIV-associated neurocognitive disorders be used in children. Neurology. 2016;87:17–18.
Wilmshurst JM, Hammond CK, Donald K, et al. NeuroAIDS in children. Handb Clin Neurol. 2018;152:99–116.
Woods SP, Moore DJ, Weber E, Grant I. Cognitive neuropsychology of HIV-associated neurocognitive disorders. Neuropsychol Rev. 2009;19:152–168.
Adams HR, Mwanza-Kabaghe S, Mbewe EG, et al. The HIV-associated neurocognitive disorders in Zambia (HANDZ) study: protocol of a research program in pediatric HIV in sub-saharan Africa. medRxiv. 2019:19003590.
Buda A, Dean O, Adams HR, et al. Neurocysticercosis among Zambian children and adolescents with human immunodeficiency Virus: a geographic information systems approach. Pediatr Neurol. 2020;102:36–43.
Buda A, Dean O, Adams HR, et al. Neighborhood-based socioeconomic determinants of cognitive impairment in Zambian children with HIV: a quantitative geographic information systems approach. J Pediatr Infect Dis Soc. 2021;10:1071–1079.
Mbewe EG, Kabundula PP, Mwanza-Kabaghe S, et al. Socioeconomic status and cognitive function in children with HIV: evidence from the HIV-associated neurocognitive disorders in Zambia (HANDZ) study. J Acqui Immune Defic Syndr. 2022;89:56–63.
World Health Organizatioin. WHO Child Growth Standards: Length/Height-for-Age, Weight-for-Age, Weight-for-Length, Weight-for-Height and Body Mass Index-for-Age: Methods and Development. Geneva, Switzerland World Health Organization. 2006.
Kabundula PP, Mbewe EG, Mwanza-Kabaghe S, et al. Validation of the national Institute of health Toolbox cognition battery (NIHTB-CB) in children and adolescents with and without HIV infection in Lusaka, Zambia. AIDS Behav. 2022.
Cysique LA, Vaida F, Letendre S, et al. Dynamics of cognitive change in impaired HIV-positive patients initiating antiretroviral therapy. Neurology. 2009;73:342–348.
Heaton RK, Temkin N, Dikmen S. Detecting change: a comparison of three neuropsychological methods, using normal and clinical samples. Arch Clin. 2001;16:75–91.
Heaton RK, Franklin DR, Ellis RJ, et al.; CHARTER Group; HNRC Group. HIV-associated neurocognitive disorders before and during the era of combination antiretroviral therapy: differences in rates, nature, and predictors. J Neurovirol. 2011;17:3–16.
Tennant PWG, Murray EJ, Arnold KF, et al. Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations. Int J Epidemiol. 2021;50:620–632.
Textor J, Hardt J, Knüppel S. DAGitty: a graphical tool for analyzing causal diagrams. Epidemiology. 2011;22:745.
Textor J. Drawing and analyzing causal DAGs with DAGitty. arXiv preprint arXiv. 2015;150804633.
Newman DA. Missing data: five practical guidelines. Organizational Res Methods. 2014;17:372–411.
Nagin DS, Odgers CL. Group-based trajectory modeling in clinical research. Annu Rev Clin Psychol. 2010;6:109–138.
Nagin DS. Group-based trajectory modeling: an overview. In: Piquero A, Weisburd D, (eds). Handbook of Quantitative Criminology. New York, NY: Springer; 2010:53–67.
Jones BL, Nagin DS. A note on a Stata plugin for estimating group-based trajectory models. Sociological Methods Res. 2013;42:608–613.