Maternal risk factors for birth asphyxia in low-resource communities. A systematic review of the literature
Bibliographic record
Abstract
Birth asphyxia (BA) affects millions of newborns annually, especially in low-resource communities. Given that much of the attention to this point has focussed upon secondary prevention, we sought to inform the development of primary prevention strategies for BA in resource-limited settings by identifying maternal risk factors. To this end, we systematically reviewed the MEDLINE, PsychInfo, and EMBASE databases, and identified 38 relevant studies. Upon analysis, we found 12 maternal variables associated with BA, and thematically arranged them into 3 categories: sociodemographic factors (age, literacy, gravidity, parity), health care factors (antenatal care, delivery location), and health status (hypertension, pre-eclampsia, eclampsia, anaemia, antepartum haemorrhage, pyrexia). The factors with the greatest, and/or most consistent influence upon likelihood for BA were: young maternal age (<20 years), limited maternal literacy, insufficient antenatal care, non-hospital delivery, maternal hypertension, and anaemia. We hope our review will assist stakeholders guiding the development of BA-related policies and programmes.
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How this classification was reachedexpand
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".