Pharmacological strategies in multimodal analgesia for adults scheduled for ambulatory surgery
Bibliographic record
Abstract
PURPOSE OF REVIEW: The present review aims to propose pharmacological strategies to enhance current clinical practices for analgesia in ambulatory surgical settings and in the context of the opioid epidemic. RECENT FINDINGS: Each year, a high volume of patients undergoes ambulatory surgery worldwide. The multimodal analgesia proposed to ambulatory patients must provide the best analgesic effect and patient satisfaction while respecting the rules of safety for ambulatory surgery. The role of nurses, anesthesiologists, and surgeons around said surgery is to relieve suffering, achieve early mobilization and patient satisfaction, and reduce duration of stay in hospital. Currently, and particularly in North America, overprescription of opioids has reached a critical level constituting a 'crisis'. Thus, we see the need to offer more optimal multimodal analgesia strategies to ambulatory patients. SUMMARY: These strategies must combine three key components when not contraindicated: regional/local analgesia, acetaminophen, and nonsteroidal anti-inflammatory drugs (NSAIDs). Adjuvants such as gabapentinoids, N-methyl-D-aspartate receptor modulators, glucocorticoids, α2-adrenergic receptor agonists, intravenous lidocaine might be added to the initial multimodal strategy, however, caution must be used regarding their side effects and risks of delaying recovery after ambulatory surgery. Weaker opioids (e.g. oxycodone, hydrocodone, tramadol) could be used rather than more powerful ones (e.g. morphine, hydromorphone, inhaled fentanyl, sufentanil). This, combined with education about postoperative weaning of opioids after surgery must be done in order to avoid long-term reliance of these drugs.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".