Association between maternal HIV infection and low birth weight and prematurity: a meta-analysis of cohort studies
Bibliographic record
Abstract
BACKGROUND: To assess the association between maternal human immunodeficiency virus (HIV) infection and low birth weight (LBW)/prematurity (PTD), we conducted a meta-analysis of cohort studies of HIV infected and uninfected women. METHODS: Several English and Chinese databases were searched (updated to May 2015) to find the studies reporting infant outcomes associated with exposure to maternal HIV infection during pregnancy. Relevant articles were manually selected based on several inclusion and exclusion criteria. RESULTS: Fifty-two cohort studies including 15,538 (for LBW) and 200,896 (for PTD) HIV infected women met the inclusion criteria. There was significant heterogeneity among studies for maternal HIV infection associated with LBW/PTD (I(2) = 71.7%, P < 0.05, and I(2) = 51.8%, P < 0.05 for LBW and PTD, respectively). The meta-analysis demonstrated that the maternal HIV infection was significantly associated with both LBW (pooled odds ratio (OR): 1.73, 95% confidence interval (CI): 1.64, 1.82, P < 0.001) and PTD (pooled OR: 1.56, 95% CI: 1.49, 1.63, P < 0.001). No significant difference in the relationship between maternal HIV infection and adverse pregnancy outcomes was detected among the groups of different study periods. HIV infected women were at slightly higher risk of LBW in developing countries compared with women in developed countries (OR: 2.12 (95% CI: 1.81, 2.48) vs. 1.75 (95% CI: 1.44, 2.12)). Antiretroviral drugs usage did not significantly change the associations of maternal HIV exposure with LBW and PTD. CONCLUSIONS: HIV infected women were at higher risk of having a low birth weight infant or a preterm delivery infant compared with uninfected women. Such associations did not change significantly over time or were not significantly affected by the usage of antiretroviral drugs.
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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 | 0.018 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.053 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".