Not Crying After Birth as a Predictor of Not Breathing
Bibliographic record
Abstract
BACKGROUND: Worldwide, every year, 6 to 10 million infants require resuscitation at birth according to estimates based on limited data regarding "nonbreathing" infants. In this article, we aim to describe the incidence of "noncrying" and nonbreathing infants after birth, the need for basic resuscitation with bag-and-mask ventilation, and death before discharge. METHODS: We conducted an observational study of 19 977 infants in 4 hospitals in Nepal. We analyzed the incidence of noncrying or nonbreathing infants after birth. The sensitivity of noncrying infants with nonbreathing after birth was analyzed, and the risk of predischarge mortality between the 2 groups was calculated. RESULTS: The incidence of noncrying infants immediately after birth was 11.1%, and the incidence of noncrying and nonbreathing infants was 5.2%. Noncrying after birth had 100% sensitivity for nonbreathing infants after birth. Among the "noncrying but breathing" infants, 9.5% of infants did not breathe at 1 minute and 2% did not to breathe at 5 minutes. Noncrying but breathing infants after birth had almost 12-fold odds of predischarge mortality (adjusted odds ratio 12.3; 95% confidence interval, 5.8-26.1). CONCLUSIONS: All nonbreathing infants after birth do not cry at birth. A proportion of noncrying but breathing infants at birth are not breathing by 1 and 5 minutes and have a risk for predischarge mortality. With this study, we provide evidence of an association between noncrying and nonbreathing. This study revealed that noncrying but breathing infants require additional care. We suggest noncrying as a clinical sign for initiating resuscitation and a possible denominator for measuring coverage of resuscitation.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".