North American and European practices for opioid-sparing and opioid-free anaesthesia: a cross-sectional survey
Bibliographic record
Abstract
Background Opioids remain central to perioperative analgesia but concerns about the growing opioid crisis and adverse effects have prompted revaluation of their role. Opioid-sparing anaesthesia and opioid-free anaesthesia (OFA) have emerged as alternatives, yet their clinical adoption remains uncertain. This survey assessed adoption and perceptions among anaesthesiologists in North America and Europe. Methods A 26-question cross-sectional, web-based survey was distributed via email to members of the American, European, and French Societies of anaesthesiologists. The survey assessed routine use of opioid-sparing techniques, defined as the regular use of non-opioid analgesics and adjuncts to minimise intraoperative opioid use in the past month. We hypothesised that fewer than 50% of anaesthesiologists routinely used these techniques during this period. Results The overall response rate was 2% among ASA members (614/31 000) and 12% among European Society of Anaesthesiology and Intensive Care (ESAIC) members (414/3500). Concern about opioid use was reported as high in ESAIC and ASA members (90% vs 83%, P <0.001). Daily use of opioid sparing techniques was reported by 37% (95% confidence interval [CI] 32–42%) of ESAIC and 40% (95% CI 36–45%) of ASA members. OFA use was less common overall but reported to be higher by ASA repondents (21%, 95% CI 18–25%) vs 12% (95% CI 9–15%), P <0.001) for EASIC respondents. Perceived risks differed: EASIC respondents more often cited haemodynamic instability (43% vs 16%, P <0.001), whereas ASA respondents more often cited patient dissatisfaction (55% vs 30%) and uncontrolled pain (72% vs 53%, both P <0.001). Key barriers to OFA adoption included limited training, low confidence, and lack of evidence-based guidelines. Conclusions Interest in opioid-sparing anaesthesia and OFA is widespread, but routine use remains modest and varies by region. Regional perceptions, institutional protocols, and confidence in evidence appear to influence implementation.
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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 | 0.001 |
| 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".