Stellate ganglion block for non-pain indications: a scoping review
Bibliographic record
Abstract
INTRODUCTION: Stellate ganglion block (SGB) is performed to relieve head, face, neck, or upper limb pain, and several non-pain indications for performing this block have emerged over the years. To date, there has been no attempt to synthesize evidence on SGB for treating non-pain indications. This scoping review presents a summary of the efficacy and adverse effects of SGB when performed for 6 non-pain indications. METHODS: This scoping review was accomplished through the use of Arksey and O'Malley framework. A literature search was conducted for relevant articles in medical databases to identify publications on SGB and specified study types. Two reviewers independently assessed the risk of bias for randomized controlled trials, nonrandomized comparative studies, and case series. Results were summarized and recommendations were made on the basis of the strength of the available evidence according to the US Preventative Services Task Force grading system. RESULTS: Twenty-four studies (19 randomized controlled trials and 5 nonrandomized studies) were included in this review. On the basis of the evidence, SGB is recommended for obtunding cardiovascular sympathetic stimulation, improving perfusion in limbs, and alleviating menopausal symptoms with a Grade B or C recommendation and a moderate-to-low level of certainty. There was insufficient evidence to recommend SGB for the other indications. CONCLUSIONS: SGB can be considered for obtunding cardiovascular sympathetic stimulation and stress response, reducing vascular tone to improve vascular insufficiency in the limbs and perioperative hemodynamic stability, and alleviating hot flashes in menopause, in conditions refractory to conventional medical management.
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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 | 0.007 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".