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Trajectory Analysis of Cognitive Outcomes in Children With Perinatal HIV
Payal B Patel1, Tanakorn Apornpong2, Thanyawee Puthanakit3,4
1From the Department of Neurology, Yale University, New Haven, Connecticut.
Insights
Children with perinatal HIV (pHIV) show stable cognitive trajectories, with most potential determined early. Factors like older age at presentation and lower income are linked to poorer outcomes in these children.
Area of Science:
- Pediatric HIV research
- Neurodevelopmental studies
- Cognitive trajectory modeling
Background:
- Children with perinatal HIV (pHIV) may exhibit unique long-term cognitive patterns.
- Understanding these patterns is crucial for targeted interventions.
Purpose of the Study:
- To identify distinct cognitive developmental trajectories in children with pHIV.
- To determine predictors associated with belonging to specific cognitive trajectory groups.
Main Methods:
- Group-based trajectory modeling was applied to cognitive data from children (4-17 years) with pHIV in Thailand and Cambodia.
- Cognitive assessments included IQ, Color Trails Tests, and Beery-Buktenica VMI, conducted over 3-6 years.
- Multivariate logistic regression identified baseline predictors of the lowest scoring trajectory group.
Main Results:
- Three distinct cognitive trajectory clusters (high, medium, low) were identified for each test.
- Most cognitive trajectories remained stable over time; Verbal IQ declined across groups.
- Children in the lowest scoring group were older at presentation and had lower household income.
Conclusions:
- Group-based trajectory modeling effectively characterizes cognitive heterogeneity in children with pHIV.
- Cognitive potential appears largely established early, with some exceptions showing developmental gains.
- Factors such as poverty and longer untreated HIV duration may negatively impact 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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