Suprascapular Nerve Blockade for Postoperative Pain Control After Arthroscopic Shoulder Surgery: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Background: Regional nerve blocks are commonly used to manage postoperative pain after arthroscopic shoulder procedures. The interscalene brachial plexus block (ISB) is commonly used; however, because of the reported side effects of ISB, the use of a suprascapular nerve block (SSNB) has been described as an alternative strategy with fewer reported side effects. Purpose: To examine the efficacy of SSNB for pain control after shoulder arthroscopy compared with ISB as well as anesthesia without a nerve block. Study Design: Systematic review; Level of evidence, 1. Methods: Three databases (PubMed, MEDLINE, and EMBASE) were searched on April 20, 2018, to systematically identify and screen the literature for randomized controlled trials (RCTs). A meta-analysis of standard mean differences (SMDs) was performed to pool the estimated effects of the nerve blocks. Results: The search identified 14 RCTs that included 1382 patients, with a mean age of 54 years (SD, 13 years). The mean follow-up time was 3 days (range, 24 hours to 6 weeks). Postoperative pain control was significantly more effective in the SSNB groups compared with the control groups within 1 hour (SMD, –0.76; 95% CI, –1.45 to –0.07; P = .03) and 4 to 6 hours (SMD, –0.81; 95% CI, –1.53 to –0.09; P = .03) postoperatively. However, pain control was significantly less effective in the SSNB groups compared with ISB within 1 hour (SMD, 0.87; 95% CI, 0.28 to 1.46; P = .004). No major complications were noted in the SSNB groups, and minor complications such as hoarseness and prolonged motor block were significantly less common for SSNB compared with ISB. Conclusion: Although not more efficacious than ISB in terms of pain control for patients undergoing shoulder arthroscopy, SSNB provides significantly improved pain control in comparison with analgesia without a nerve block. Moreover, few major and minor complications are associated with SSNB reported across the literature.
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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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.036 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".