Automatic<i>versus</i>manual oxygen administration in the emergency department
Bibliographic record
Abstract
Oxygen is commonly administered in hospitals, with poor adherence to treatment recommendations. We conducted a multicentre randomised controlled study in patients admitted to the emergency department requiring O 2 ≥3 L·min −1 . Patients were randomised to automated closed-loop or manual O 2 titration during 3 h. Patients were stratified according to arterial carbon dioxide tension ( P aCO 2 ) (hypoxaemic P aCO 2 ≤45 mmHg; or hypercapnic P aCO 2 >45–≤55 mmHg) and study centre. Arterial oxygen saturation measured by pulse oximetry ( S pO 2 ) goals were 92–96% for hypoxaemic, or 88–92% for hypercapnic patients. Primary outcome was % time within S pO 2 target. Secondary endpoints were hypoxaemia and hyperoxia prevalence, O 2 weaning, O 2 duration and hospital length of stay. 187 patients were randomised (93 automated, 94 manual) and baseline characteristics were similar between the groups. Time within the S pO 2 target was higher under automated titration (81±21% versus 51±30%, p<0.001). Time with hypoxaemia (3±9% versus 5±12%, p=0.04) and hyperoxia under O 2 (4±9% versus 22±30%, p<0.001) were lower with automated titration. O 2 could be weaned at the end of the study in 14.1% versus 4.3% patients in the automated and manual titration group, respectively (p<0.001). O 2 duration during the hospital stay was significantly reduced (5.6±5.4 versus 7.1±6.3 days, p=0.002). Automated O 2 titration in the emergency department improved oxygenation parameters and adherence to guidelines, with potential clinical benefits.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".