Usual and Advanced Monitoring in Patients Receiving Oxygen Therapy
Bibliographic record
Abstract
Respiratory monitoring in patients receiving oxygen therapy for acute care is mandatory at the initial stage of in-hospital management given the potential risk of clinical worsening. Although some patients benefit from close monitoring in the ICU, the vast majority of them are managed in general wards with reduced staff and clinical supervision. The objective of monitoring is to detect early clinical deterioration, which may help prevent in-hospital cardiac arrest. In addition to the clinical and usual evaluations (eg, breathing frequency, breathing pattern, oximetry, and oxygen flow requirements), early warning scoring systems have been developed to detect clinical deterioration in acutely ill patients. The monitoring of these scores is recommended for patients receiving oxygen therapy. These scores have several limitations, among which is the absence of oxygen flow evaluation. Manual and intermittent monitoring of these scores in the ward is time-consuming and may not be sufficient to accurately detect deterioration of patient's clinical condition in a timely manner. Automated and continuous monitoring, in addition to clinical evaluation and arterial blood gases analysis, which remain necessary, may improve the detection of clinical worsening in specific patients. Devices that automatically titrate and wean oxygen flow on the basis of [Formula: see text] enable measurement of several major cardiorespiratory parameters (eg, [Formula: see text], oxygen flow, heart rate, breathing frequency, and heart rate variability). The combination of these parameters into new scores is at least as accurate and well-evaluated, and recommended early warning scores and may be useful in monitoring patients receiving oxygen therapy.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".