Continuous measurement of combined oximetry and transcutaneous carbon dioxide in patients with opioid-treated chronic pain in a palliative care setting
Bibliographic record
Abstract
Aim: To evaluate the feasibility of continuous non-invasive monitoring of ventilation using combined oximetry and transcutaneous carbon dioxide (TcCO2) measurement in the palliative care setting in patients receiving opioids. Methods: 15 patients with advanced cancer and chronic pain at a palliative care hospital were included prospectively. TcCO2 and oxygen saturation (SpO2) were monitored. Results: Mean and median McGill pain scores were 20.5 + 13 and 18 respectively. Mean and median duration of the measurements were 43 + 8.8 hours and 46 hours respectively. Buprenorphine patch was used in 10 patients, oral buprenorphine in 3 patients, morphine in 7 patients, pregabalin in 7 patients, lorazepam in 4 patients and midazolam and a fentanyl patch in 1 patient each. Mean and median baseline SpO2 before administration of the opioids were 94% + 4% and 95% (range 87 – 100%) respectively. SpO2 of less than 88% was recorded in 10 patients after administration of opioids. Mean and median baseline TcCO2 values were 37 + 8 mm Hg and 35 mm Hg (range 28 – 60 mm Hg) respectively. Mean and median highest TcCO2 values were 53 + 12 mm Hg and 47 mm Hg (range 43 – 85 mm Hg) respectively. Mean and median rise in TcCO2 from baseline was 16 + 9 mm Hg and 15 mm Hg (7 – 45 mm Hg) respectively. 5 patients showed significant rise in TcCO2 measurement as per the AASM criteria. Conclusion: It is feasible to continuously monitor ventilation noninvasively using combined SpO2 and TcCO2 to detect hypoventilation in the palliative care setting. Patients with advanced cancer administered opioids in palliative care are at risk of manifesting hypercapnia and hypoxemia.
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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 | 0.001 | 0.003 |
| 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 | 0.001 | 0.000 |
| 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 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".