Prematurity and Sudden Unexpected Infant Deaths in the United States
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Prematurity, a strong risk factor for sudden unexpected infant death (SUID), was addressed in recommendations by the American Academy of Pediatrics in 2011 for safe sleep education in NICUs. We documented associations between gestational age (GA) and SUID subsequent to these guidelines. METHODS: Using the 2012-2013 US linked infant birth and death certificate period files, we documented rates per live births of sudden infant death syndrome, ill-defined and unspecified causes, accidental suffocation and strangulation in bed, and overall SUID by GA in postneonatal, out-of-hospital, and autopsied cases; compared survivors and cases; and estimated logistic regression models of associations between GA and SUID. RESULTS: < .0001). SUID rates were 2.68, 1.94, 1.46, 1.16, 0.73, and 0.51 per 1000 live births for 24 to 27, 28 to 31, 32 to 33, 34 to 36, 37 to 38, and 39 to 42 weeks' GA, respectively. Logistic regression models additionally indicated declines in the risk for SUID as GA increased. Prenatal smoking, inadequate prenatal care, and demographics associated with poverty were strongly associated with SUID. CONCLUSIONS: Despite the 2011 American Academy of Pediatrics recommendations for increased safe sleep education in the NICUs, SUID rates were inversely associated with GA in 2012 to 2013, suggesting that risk of SUID associated with prematurity has multiple etiologies requiring continued investigation, including biological vulnerabilities and the efficacy of NICU education programs, and that strategies to reduce SUID should be multifaceted.
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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 | 0.000 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".