Child Mortality According to Maternal and Infant HIV Status in Zimbabwe
Bibliographic record
Abstract
BACKGROUND: HIV causes substantial mortality among African children but there is limited data on how this is influenced by maternal or infant infection status and timing. METHODS: Children enrolled in the ZVITAMBO trial were divided into 5 groups: those born to HIV-negative mothers (NE, n = 9510), those born to HIV-positive mothers but noninfected (NI, n = 3135), those infected in utero (IU, n = 381), those infected intrapartum (IP, n = 508), and those infected postnatally (PN, n = 258). Their mortality was estimated. RESULTS: Two-year mortality was 2.9% (NE infants), 9.2% (NI), 67.5% (IU), 65.1% (IP), and 33.2% (PN). Between 8 weeks and 6 months, mortality in IU infants quintupled (from 309 to 1686/1000 c-y). The median time from infection to death was 208, 380, and >500 days for IU, IP, and PN infants, respectively. Among NI children, advanced maternal disease was predictive of mortality. Acute respiratory infection was the major cause of death. CONCLUSIONS: Perinatally infected infants are at particular risk of death between 2 and 6 months: cotrimoxazole prophylaxis and early pediatric HAART should be scaled up. Uninfected infants of infected mothers have at least twice the mortality risk of infants born to uninfected mothers: all HIV-exposed infants should be targeted with child survival interventions. HIV-positive mothers with more advanced disease are not only more likely to infect their infants, but their infants are more likely to die, whether infected or not: provision of antiretroviral treatment to pregnant and lactating women is an urgent need for both mothers and their children.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".