Cognitive and language outcomes in HIV-uninfected infants exposed to combined antiretroviral therapy in utero and through extended breast-feeding
Bibliographic record
Abstract
OBJECTIVE: To determine whether there is a higher risk for cognitive or language delay among HIV-exposed uninfected (HEU) children exposed to cART (zidovudine/lamivudine/lopinavir/ritonavir) in utero and through 1 year of breast-feeding (World health Organization Option B+), compared with the control children born to HIV-uninfected mothers. DESIGN: This is a double cohort study from Lusaka, Zambia. METHODS: HEU (n = 97) and control (n = 103) children aged 15-36 months were assessed on their early nonverbal problem-solving and language skills using the standardized Capute Scales. A score of less than 85 on the Capute Full-Scale Developmental Quotient (FSDQ) was considered indicative of developmental delay and was the primary outcome of interest. RESULTS: An FSDQ of less than 85 was found in eight (8.3%) of HEU participants and 15 (14.6%) of controls. In univariate logistic regressions, lower income [odds ratio (OR) = 0.93, P = 0.02], older infant age (OR = 1.08, P = 0.03), lower birth weight (OR = 0.16, P < 0.001), and less maternal education (OR = 0.41, P = 0.047) were associated with the probability of FSDQ less than 85, whereas Group (control/HEU) was not (OR = 1.88, P = 0.16). In the multivariable analysis, only lower birth weight (OR = 0.15, P < 0.001) remained associated with FSDQ less than 85. CONCLUSIONS: Our study did not support the presence of an adverse effect on cognitive and language development with prolonged antepartum and postpartum cART e/xposure. Larger studies and studies of older HEU children will be required to confirm these reassuring findings.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".