Does Resuscitation Training Reduce Neonatal Deaths in Low-Resource Communities? A Systematic Review of the Literature
Bibliographic record
Abstract
Every year, nearly 1 million babies succumb to birth asphyxia (BA) within the Asia-Pacific region. The present study sought to determine whether educational interventions containing some element of resuscitation training would decrease the relative risk (RR) of neonatal mortality attributable to BA in low-resource communities. We systematically reviewed 3 electronic databases and identified 14 relevant reports. For community deliveries, providing traditional birth attendants (TBAs) with neonatal resuscitation training modestly reduced the RR in 3 of 4 studies. For institutional deliveries, training a range of clinical staff clearly reduced the RR within 2 of 8 studies. When resuscitation-specific training was directed to community and institutional health care workers, a slight benefit was observed in 1 of 2 studies. Specific training in neonatal resuscitation appears most effective when provided to TBAs (specifically, those presented with ongoing opportunities to review and update their skills), but this particular intervention alone may not appreciably reduce mortality.
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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 | 0.005 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".