LATE-BREAKING ABSTRACT: Oxygen titration and weaning with FreeO2 in COPD patients hospitalized for exacerbation. A randomized controlled pilot study
Bibliographic record
Abstract
Rationale: FreeO2 is an innovative device that automatically adjusts O2 flow to maintain SpO2 within target set by physicians. Main objective was to evaluate whether FreeO2 could be used in daily routine for COPD exacerbations and would be accepted by respiratory ward caregivers. Methods: we conducted a RCT comparing manual and automated O2 adjustment for exacerbated COPD patients admitted to the respiratory ward. We evaluated O2 management perception by nurses and physicians using a visual analogue scale. Patients were monitored for SpO2, respiratory and heart rate, EtCO2. We evaluated time within SpO2 target ±2%, severe desaturation (SpO2<85%), and hyperoxia duration (SpO2>5% above target). Results: 25 patients were included either in each group (n=50). Patients9 age was 72±9 yrs, FEV1=1000±500 ml, and initial O2 flow=2.0±1.0 L/min. Oxygen adjustment was quoted 8.9±1.5 and 8.8±1.8 (1=very bad to 10=very good) by nurses under FreeO2 and in the Manual group respectively (P=0.46). Oxygen adjustment was quoted 8.2±2.2 and 7.8±2.1 (P=0.48) by physicians. % time within SpO2 target was 81.2±15.9 with FreeO2 vs 51.3±19.7 with manual adjustment (p<0.001). % time with severe desaturation was 0.2±0.2 vs. 2.3±2.7 (p<0.001) and % time with hyperoxia was 1.5±1.9 vs. 10.4±10.3 (p<0.001). Hospital lenght of stay was 5.8±4.4 days with FreeO2 and 8.4±6.0 in the Manual group (p=0.05). Readmission rate was similar. Conclusions: FreeO2 was well accepted by caregivers, better maintained SpO2 within target, and reduced desaturations and hyperoxia, as compared to Manual adjustment. A lenght of stay reduction may also be observed, although the study was not designed for this sake.
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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) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".