Efficacy of stellate ganglion block in treatment of electrical storm: a systematic review and meta-analysis
Bibliographic record
Abstract
Electrical storm (ES) is a life-threatening condition of recurrent ventricular arrhythmias (VA) in a short period of time. Percutaneous stellate ganglion blockade (SGB) is frequently used - however the efficacy is undefined. The objective of our systematic review was to determine the efficacy of SGB in reducing VA events and mortality among patients with ES. A search of Medline, EMBASE, Scopus, CINAHL and CENTRAL was performed on February 29, 2024 to include studies with adult patients (≥ 18 years) with ES treated with SGB. Our outcomes of interest were VA burden pre- and post-SGB, and in-hospital/30-day mortality. A total of 553 ES episodes in 542 patients from 15 observational studies were included. Treated VAs pre- and post-SGB were pooled from eight studies including 383 patients and demonstrated a decrease from 3.5 (IQR 2.25-7.25) to 0 (IQR 0-0) events (p = 0.008). Complete resolution after SGB occurred in 190 of 294 patients (64.6%). Despite this, in-hospital or 30-day mortality remained high occurring in 140 of 527 patients (random effects prevalence 22%). Repeat SGB for recurrent VAs was performed in 132 of 490 patients (random effects prevalence 21%). In conclusion, observational data suggests SGB may be effective in reducing VAs in ES. Definitive studies for SGB in VA management are needed. Study protocol: PROSPERO - registration number CRD42023430031.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.029 |
| Bibliometrics | 0.005 | 0.006 |
| 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".