Automated oxygen titration and weaning with FreeO<sub>2</sub> in patients with acute exacerbation of COPD: a pilot randomized trial
Bibliographic record
Abstract
INTRODUCTION: We developed a device (FreeO2) that automatically adjusts the oxygen flow rates based on patients' needs, in order to limit hyperoxia and hypoxemia and to automatically wean them from oxygen. OBJECTIVE: The aim of this study was to evaluate the feasibility of using FreeO2 in patients hospitalized in the respiratory ward for an acute exacerbation of COPD. METHODS: We conducted a randomized controlled trial comparing FreeO2 vs manual oxygen titration in the respiratory ward of a university hospital. We measured the perception of appropriateness of oxygen titration and monitoring in both groups by nurses and attending physicians using a Likert scale. We evaluated the time in the target range of oxygen saturation (SpO2) as defined for each patient by the attending physician, the time with severe desaturation (SpO2 <85%), and the time with hyperoxia (SpO2 >5% above the target). We also recorded length of stay, intensive care unit admissions, and readmission rate. Fifty patients were randomized (25 patients in both groups; mean age: 72±8 years; mean forced expiratory volume in 1 second: 1.00±0.49 L; and mean initial O2 flow 2.0±1.0 L/min). RESULTS: Nurses and attending physicians felt that oxygen titration and monitoring were equally appropriate with both O2 administration systems. The percentage of time within the SpO2 target was significantly higher with FreeO2, and the time with severe desaturation and hyperoxia was significantly reduced with FreeO2. Time from study inclusion to hospital discharge was 5.8±4.4 days with FreeO2 and 8.4±6.0 days with usual oxygen administration (P=0.051). CONCLUSION: FreeO2 was deemed as an appropriate oxygen administration system by nurses and physicians of a respiratory unit. This system maintained SpO2 at the target level better than did manual titration and reduced periods of desaturation and hyperoxia. Our results also suggest that FreeO2 has the potential to reduce the hospital length of stay.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".