The impact of the use of continuous pulse oximetry monitoring to monitor patients at high risk of respiratory depression on nursing practice
Bibliographic record
Abstract
AIM: To describe the impact on nursing practice of using continuous pulse oximetry monitoring to monitor patients at high risk for respiratory depression after surgery. DESIGN: A convergent mixed method design. METHODS: Thirty (30) hours of non-participant structured observation and explanatory interviews were conducted with 10 nurses from the surgery care unit and intensive care unit. RESULTS: We found that nursing practice to evaluate and monitor at-risk patients through continuous pulse oximetry monitoring is mainly linked to technical care. Nurses generally meet the frequency of bedside monitoring required by established protocols. During the structured non-participant observation periods, it was observed that 90% of the alarms were false (unsustained desaturations). This was confirmed by the nurses during the explanatory interviews. Noisy environments, high number of false alarms, poor communication between nurses and various operational failures might have a negative impact on nursing practice. CONCLUSION: Several challenges must be overcome for this technology to achieve the desired outcomes of continuous surveillance and rapid detection of respiratory depression episodes for post-surgical patients. No Patient or Public Contribution.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".