Severe Neonatal Morbidity Across Gestational Age: Monitoring Infants at High Risk of Mortality
Bibliographic record
Abstract
AIM: This study aimed to quantify temporal trends in severe neonatal morbidity (SNM) and examine its association with neonatal mortality, stratified by gestational age. METHODS: This study included all live births in Sweden from 2007 to 2021. SNM types and subtypes were identified based on diagnoses and procedure codes for births ≥ 22 weeks' gestation, including complications within 27 days. Rates were calculated by gestational age, and temporal changes were assessed using rate ratios (RR) and 95% confidence intervals (CI). Adjusted relative risks (aRR) of neonatal death were also estimated. RESULTS: From 2007 to 2021, 47,048 (2.8%) cases of SNM were identified, rising from 2.2% in 2007 to 3.6% in 2021, mainly due to increased resuscitation/mechanical ventilation rates across all gestational ages. Infections rose among infants born at ≥ 37 weeks (0.59% in 2007-2011 to 0.77% in 2017-2021, RR 1.30, 95% CI, 1.24-1.37), but declined in those born at 22-31 weeks. Neurological morbidity, especially seizures, slightly increased in term and moderately preterm infants. Except for infants born at 22-27 weeks, neonatal mortality risks among infants with SNM were higher in infants with greater gestational ages. CONCLUSION: Despite advances in neonatal care, SNM prevalence in Sweden increased from 2007 to 2021 across all gestational ages.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".