Risk Factors for Stillbirth: Findings from a Population‐Based Case–Control Study, <scp>H</scp>aryana, <scp>I</scp>ndia
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Stillbirth is a prevalent adverse outcome of pregnancy in India despite efforts to improve care of women during pregnancy. Risk factors for stillbirths include sociodemographic factors, medical complications during pregnancy, intake of harmful drugs, and complications during delivery. The objective of the study was to examine the risk factors for stillbirth with a focus on sex selection drugs (SSDs). METHODS: A population-based case-control study was undertaken in Haryana. Cases of stillbirths were identified from the Maternal Infant Death Review System portal of Haryana state for the months of August-September 2014. A consecutive birth from the same geographical area as the case was selected as the control. The sample size was 325 per group. Mothers were interviewed using a validated tool. Bivariate analyses and logistic regression were conducted to examine the association between risk factors and stillbirth. Attributable risk proportions (ARP) and population attributable risk proportions (PARP) were estimated. RESULTS: The sociodemographic profiles of the cases and controls were similar. History of intake of SSDs [adjusted odds ratio (OR) 2.6, 95% confidence interval (CI) 1.5, 4.5] emerged as a risk factor. Other significant factors were preterm <37 weeks (OR 3.5, 95% CI 2.1, 6.0), history of previous stillbirths (OR 4.0, 95% CI 2.1, 7.8), and complications during labour (OR 3.3, 95% CI 2.1, 5.3). Estimates of the ARP and PARP for intake of SSDs were 0.60 (95% CI 0.32, 0.77) and 0.1 (95% CI -0.13, 0.28), respectively. CONCLUSIONS: SSDs could be attributed as a risk factor in a fifth of the cases of stillbirths. The number needed to harm for the use of SSDs in causing adverse effect of stillbirths was 5, suggesting thereby that for every five mothers exposed to SSDs, one would have stillbirth. Greater efforts are required to inform people about the harmful effects of SSD consumption during pregnancy.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it