Enhancing Postoperative Pain Management: Assessing the Influence of Ultrasound‐Guided Stellate Ganglion Block on Arteriovenous Fistula Surgery
Bibliographic record
Abstract
INTRODUCTION: The effectiveness of stellate ganglion block in managing acute postoperative pain remains uncertain due to limited high-quality evidence. This study evaluates the impact of stellate ganglion block on acute pain following arteriovenous fistula surgery. METHODS: A randomized controlled clinical trial was conducted in the Surgery Department of Bahonar and Shafa Hospitals at Kerman University of Medical Sciences, Iran. Patients undergoing arteriovenous fistula surgery were randomly assigned to either the intervention group, which received an ultrasound-guided stellate ganglion block with 5 mL of 5% lidocaine, or the control group, which received no intervention. A total of 60 patients were selected based on age and gender similarity. Pain levels were assessed using the visual analog scale immediately after surgery and at 6 and 12 h postoperatively. FINDINGS: Pain scores differed significantly between the two groups at all time points (p ≤ 0.05). The intervention group reported lower pain levels at 6 and 12 h postoperatively compared to the control group. Repeated measures analysis confirmed a significant reduction in pain over time in both groups (p ≤ 0.05), with a more pronounced decrease in the intervention group (p ≤ 0.05). CONCLUSION: Preoperative stellate ganglion block effectively reduces acute postoperative pain following arteriovenous fistula surgery. However, its effects beyond the 12-h postoperative period remain unknown. Further research is needed to evaluate its long-term impact.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.002 | 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".