Perioperative Regional Anesthesia on Persistent Opioid Use and Chronic Pain after Noncardiac Surgery: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
BACKGROUND: Whether regional anesthesia impacts the development of chronic postsurgical pain is currently debateable, and few studies have evaluated an effect on prolonged opioid use. We sought to systematically review the effect of regional anesthesia for adults undergoing noncardiac elective surgery on these outcomes. METHODS: A systematic search was conducted in MEDLINE, EMBASE, CENTRAL, and CINHAL for randomized controlled trials (from inception to April 2022) of adult patients undergoing elective noncardiac surgeries that evaluated any regional technique and included one of our primary outcomes: (1) prolonged opioid use after surgery (continued opioid use ≥2 months postsurgery) and (2) chronic postsurgical pain (pain ≥3 months postsurgery). We conducted a random-effects meta-analysis on the specified outcomes and used the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach to rate the quality of evidence. RESULTS: Thirty-seven studies were included in the review. Pooled estimates indicated that regional anesthesia had a significant effect on reducing prolonged opioid use (relative risk [RR] 0.48, 95% CI, 0.24-0.96, P = .04, I 2 0%, 5 trials, n = 348 patients, GRADE low quality). Pooled estimates for chronic pain also indicated a significant effect favoring regional anesthesia at 3 (RR, 0.74, 95% CI, 0.59-0.93, P = .01, I 2 77%, 15 trials, n = 1489 patients, GRADE moderate quality) and 6 months (RR, 0.72, 95% CI, 0.61-0.85, P < .001, I 2 54%, 19 trials, n = 3457 patients, GRADE moderate quality) after surgery. No effect was found in the pooled analysis at 12 months postsurgery (RR, 0.44, 95% CI, 0.16-1.17, P = .10). CONCLUSIONS: The results of this study suggest that regional anesthesia potentially reduces chronic postsurgical pain up to 6 months after surgery. Our findings also suggest a potential decrease in the development of persistent opioid use.
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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 | 0.037 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.086 | 0.037 |
| Bibliometrics | 0.002 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".