Association of nurse staffing and unit occupancy with mortality and morbidity among very preterm infants: a multicentre study
Bibliographic record
Abstract
OBJECTIVE: In a healthcare system with finite resources, hospital organisational factors may contribute to patient outcomes. We aimed to assess the association of nurse staffing and neonatal intensive care unit (NICU) occupancy with outcomes of preterm infants born <33 weeks' gestation. DESIGN: Retrospective cohort study. SETTING: Four level III NICUs. PATIENTS: Infants born 23-32 weeks' gestation 2015-2018. MAIN OUTCOME MEASURES: Nursing provision ratios (nursing hours worked/recommended nursing hours based on patient acuity categories) and unit occupancy rates were averaged for the first shift, 24 hours and 7 days of admission of each infant. Primary outcome was mortality/morbidity (bronchopulmonary dysplasia, severe neurological injury, retinopathy of prematurity, necrotising enterocolitis and nosocomial infection). ORs for association of exposure with outcomes were estimated using generalised linear mixed models adjusted for confounders. RESULTS: Among 1870 included infants, 823 (44%) had mortality/morbidity. Median nursing provision ratio was 1.03 (IQR 0.89-1.22) and median unit occupancy was 89% (IQR 82-94). In the first 24 hours of admission, higher nursing provision ratio was associated with lower odds of mortality/morbidity (OR 0.93, 95% CI 0.89 to 0.98), and higher unit occupancy was associated with higher odds of mortality/morbidity (OR 1.19, 95% CI 1.04 to 1.36). In causal mediation analysis, nursing provision ratios mediated 47% of the association between occupancy and outcomes. CONCLUSIONS: NICU occupancy is associated with mortality/morbidity among very preterm infants and may reflect lack of adequate resources in periods of high activity. Interventions aimed at reducing occupancy and maintaining adequate resources need to be considered as strategies to improve patient outcomes.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".