Mortality of Neonatal Respiratory Failure Related to Socioeconomic Factors in Hebei Province of China
Bibliographic record
Abstract
Dramatic progress has occurred in neonatal intensive care in tertiary centers in mid-eastern China. We investigated the characteristics of neonatal respiratory failure (NRF) including the incidence, management, outcomes and costs in 14 neonatal intensive care units (NICUs) of Hebei, a province at an intermediate economic level in China. Over a period of 12 consecutive months in 2007-2008, perinatal data were collected prospectively from all NICU admissions (n = 11,100). NRF was defined as severe hypoxemia requiring respiratory support for more than 24 h, and was diagnosed in 1,875 newborns (16.9%). The average birth weight of newborns with NRF was 2,200 g (range 600-5,500 g), with 60.9% <2,500 g, and 2% <1,000 g. The male:female ratio was 2.6:1. The leading diagnosis was respiratory distress syndrome; 58.3% of newborns with respiratory distress syndrome received surfactant. Continuous positive airway pressure was used more than ventilation (73.3 vs. 49.1%,p < 0.001). Overall, the mortality rate until discharge was 31.4% (583/1,859). Most deaths (432, 74.1%) followed a parental decision to withdraw care. NRF mortality varied in association with different gross domestic product levels, family annual income and nurse-to-bed ratios. The median cost of a hospital stay was 10,169 CNY (interquartile range: 6,745-16,386) for NRF survivors. We conclude that, despite the available respiratory support in these emerging NICUs, the mortality of NRF remains. This was associated with prematurity, standard of care but also with socioeconomic factors affecting treatment decisions. Assessment of efficacy of respiratory support for NRF in such emerging neonatal services should account for both standard of care and socioeconomic conditions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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 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".