Growth Faltering and Developmental Delay in HIV-Exposed Uninfected Ugandan Infants: A Prospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: HIV-exposed but uninfected (HEU) infants are at increased risk of impaired early linear growth and cognitive development. We examined associations between prenatal and postnatal growth and subsequent neurodevelopment in Ugandan HEU infants, hypothesizing that early insults may explain alterations in both somatic growth and brain development. METHODS: We prospectively followed a cohort of HEU infants from birth to 18 months of age, and measured length/height, weight, head, and arm circumference longitudinally. The Malawi Development Assessment Tool (MDAT, 12 and 18 months) and the Color Object Association Test (18 months) were used for developmental assessments. RESULTS: Among 170 HEU infants, the prevalence of low-birth weight and failure to thrive was 7.6% and 37%, respectively. HEU infants had MDAT scores that were similar to the reference population. The mean (SD) score on the Color Object Association Test was 5.5 (3.1) compared with 6.9 (5.3) in developmentally normal children. Developmental ability at age 18 months showed strong cross-sectional correlation with weight-for-age (ρ = 0.36, P < 0.0001), length/height-for-age (ρ = 0.41, P < 0.0001), head circumference-for-age (ρ = 0.26, P = 0.0011), and mid-upper arm circumference-for-age (ρ = 0.34, P = 0.0014). There was a statistically significant correlation between birth weight and MDAT z-score at 18 months (ρ = 0.20, P = 0.010). Failure to thrive was associated with lower MDAT z-score [median -0.13 (IQR -0.75 to +0.14) versus +0.14 (IQR -0.44 to +0.63), P = 0.042]. CONCLUSION: Growth faltering in HEU infants was associated with lower attainment of developmental milestones at age 18 months. Our findings point to a simple screening method for identifying HEU infants at risk for developmental intervention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".