Care Bundle to Improve Oxygen Maintenance and Events
Bibliographic record
Abstract
Introduction: Prolonged periods spent outside the target range of oxygen saturation (SpO2) in preterm infants, along with frequent desaturation events, predispose them to retinopathy of prematurity (ROP) and long-term neurodevelopmental impairment. The primary aim of this study was to increase the mean time spent within the target SpO2 range (WTR) by 10% and to reduce the frequency of desaturation events by 5 events per patient day, respectively, within 18 months of implementing a care bundle. Methods: This study was completed in a 46-bed neonatal intensive care unit (NICU), involving 246 staff members and led by a quality improvement team. The change interventions included implementing new practice guidelines, reviewing daily summaries of SpO2 maintenance, daily infant wellness assessment, standardizing workflow, and responding to SpO2 alarms. In addition, we collected staff satisfaction and compliance with change interventions, resource use, and morbidity and mortality data at discharge. Results: The mean time spent WTR increased from 65.3% to 75.3%, and the frequency of desaturation events decreased from 25.1 to 16.5 events per patient day, respectively, with a higher magnitude of benefit in infants on days with supplemental oxygen. Postimplementation, the duration of high-frequency ventilation and supplemental oxygen were lower, but morbidity and mortality rates were similar. Staff satisfaction with training workshops, coaching, use of the infant wellness assessment tool, and SpO2 alarm management algorithms were 74%, 82%, 80%, and 74%, respectively. Conclusion: Implementing a care bundle to improve oxygen maintenance and reduce desaturation events increased the time spent WTR and reduced the frequency of desaturation events.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.008 | 0.001 |
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".