Angiogenic proteins, placental weight and perinatal outcomes among pregnant women in Tanzania
Bibliographic record
Abstract
INTRODUCTION: Placental vascular development, and ultimately placental weight, is essential to healthy fetal development. Here, we examined placental weight in a cohort of Tanzanian women in association with angiogenic proteins known to regulate placental vascular development and perinatal outcomes. METHODS: A total of n = 6579 women with recorded placental weight were included in this study. The relative risk of adverse perinatal outcomes (Apgar score, death, asphyxia, respiratory distress, seizures, pneumonia and sepsis) was compared between placental weight in the bottom and top 10th percentiles. We quantified angiogenic mediators (Ang-1, Ang-2, VEGF, PGF and sFlt-1) in plasma samples (n = 901) collected between 12 to 27 weeks of pregnancy using ELISA and assessed the relative risk of placental weight in the bottom and top 10th percentiles by protein levels in quartiles. RESULTS: Women with Ang-2 levels in the highest quartile had an increased relative risk of placental weight in the bottom 10th percentile (RR = 1.45 (1.10, 1.91), p = 0.01). Women with VEGF-A (RR = 0.73 (0.56, 0.96), p = 0.05) and PGF (RR = 0.58 (0.44, 0.72), p = 0.002) in the highest quartile had a reduced relative risk of placental weight in the bottom 10th percentile. Low placental weight (in bottom 10th percentile) was associated with an increased relative risk of Apgar score of <7 at 1 minute (RR = 2.31 (1.70, 3.13), p = 0.001), at 5 minutes (RR = 3.53 (2.34, 5.33), p = 0.001), neonatal death (RR = 5.02 (3.61, 7.00), p = 0.001), respiratory distress (RR = 4.80(1.71, 13.45), p = 0.001), and seizures (RR = 4.18 (1.16, 15.02), p = 0.03). DISCUSSION: The association between low placental weight and risk of adverse perinatal outcomes in this cohort suggests that placental weight could serve as a useful indicator, providing additional insight into high-risk pregnancies and identifying neonates that may require additional monitoring and follow-up.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".