Long-Acting Patient-Controlled Opioids Are Not Associated With More Postoperative Hypoxemia Than Short-Acting Patient-Controlled Opioids After Noncardiac Surgery
Bibliographic record
Abstract
BACKGROUND: Opioids can contribute to postoperative desaturation. Short-acting opioids, titrated to need, may cause less desaturation than longer-acting opioids. We thus tested the primary hypothesis that long-acting patient-controlled intravenous opioids are associated with more hypoxemia (defined as an integrated area under a postoperative oxyhemoglobin saturation of 95%) than short-acting opioids. METHODS: This analysis was a substudy of VISION, a prospective cohort study focused on perioperative cardiovascular events (NCT00512109). After excluding for predefined criteria, 191 patients were included in our final analysis, with 75 (39%) patients being given fentanyl (short-acting opioid group) and 116 (61%) patients being given morphine and/or hydromorphone (long-acting opioid group). The difference in the median areas under a postoperative oxyhemoglobin saturation of 95% between short-acting and long-acting opioids was compared using multivariable median quantile regression. RESULTS: The short-acting opioid median area under a postoperative oxyhemoglobin saturation of 95% per hour was 1.08 (q1, q3: 0.62, 2.26) %-h, whereas the long-acting opioid median was 1.28 (0.50, 2.23) %-h. No significant association was detected between long-acting and short-acting opioids and median area under a postoperative oxyhemoglobin saturation of 95% per hour (P = .66) with estimated change in the medians of -0.14 (95% CI, -0.75, 0.47) %-h for the patients given long-acting versus short-acting IV patient-controlled analgesia opioids. CONCLUSIONS: Long-acting patient-controlled opioids were not associated with the increased hypoxemia during the first 2 postoperative days.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".