Newborn Pulse Oximetry for Infants Born Out-of-Hospital
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Conventional timing of newborn pulse oximetry screening is not ideal for infants born out-of-hospital. We implemented a newborn pulse oximetry screen to align with typical midwifery care and measure its efficacy at detecting critical congenital heart disease. METHODS: Cohort study of expectant mothers and infants mainly from the Amish and Mennonite (Plain) communities with limited prenatal ultrasound use. Newborns were screened at 1 to 4 hours of life ("early screen") and 24 to 48 hours of life ("late screen"). Newborns were followed up to 6 weeks after delivery to report outcomes. Early screen, late screen, and combined results were analyzed on the basis of strict algorithm interpretation ("algorithm") and the midwife's interpretation in the field ("field") because these did not correspond in all cases. RESULTS: Pulse oximetry screening in 3019 newborns (85% Plain; 50% male; 43% with a prenatal ultrasound) detected critical congenital heart disease in 3 infants. Sensitivity of combined early and late screen was 66.7% (95% confidence interval [CI] 9.4% to 99.2%) for algorithm interpretation and 100% (95% CI 29.2% to 100%) for field interpretation. Positive predictive value was similar for the field interpretation (8.8%; 95% CI 1.9% to 23.7%) and algorithm interpretation (5.4%; 95% CI 0.7% to 18.2%). False-positive rates were ≤1.2% for both algorithm and field interpretations. Other pathologies (noncritical congenital heart disease, pulmonary issues, or infection) were reported in 12 of the false-positive cases. CONCLUSIONS: Newborn pulse oximetry can be adapted to the out-of-hospital setting without compromising sensitivity or prohibitively increasing false-positive rates.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".