Survival, Resuscitation and Morbidities in Extremely Preterm Infant – A Retrospective Cohort Study [23C]
Bibliographic record
Abstract
INTRODUCTION: This study aims to evaluate survival to discharge, resuscitation, predictors of survival and short-term morbidities of preterm babies born at less than 24 weeks. METHODS: We conducted a retrospective cohort study using the Nationwide Inpatient Sample-Healthcare Cost and Utilization Project database. We evaluated the neonatal outcomes of all live birth admissions of less than 24 weeks from 2003-2011, excluding newborns with known congenital malformation. We used multivariate logistic regression to estimate the predictors of survival and intact survival in (1) all resuscitated newborn less than 24 weeks and in (2) resuscitated and survived infants. RESULTS: There were 9,644 live births that met study criteria, of which 76% were not resuscitated and 24% were resuscitated. The survival rate among resuscitated infants was 42.86%, while the overall survival rate to discharge among non-resuscitated infants was 10.27%. Mortality was highest in the first 2 days of life. The incidence of intraventricular hemorrhage was 13.62%, respiratory distress syndrome was 65.79%, and necrotizing enterocolitis was 0.91%. The rate of intact survival was 31.89 % in resuscitated newborn less than 24 weeks of gestation. Birth weight greater than 500g and urban non-teaching hospitals were positive predictors of survival, with an adjusted OR of 1.46 (95% CI 1.12-1.90) and OR of 1.71(95% CI 1.43-2.06), respectively. CONCLUSION: Mortality and morbidity of extremely preterm infants born at less than 24 weeks of gestation is high. However, selected extremely preterm newborns can be viable without major short-term morbidity. Providing patient counseling requires up-to-date estimates of the health outcomes in extremely preterm births.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".