Embolization of middle meningeal artery (EMMA) for non-acute subdural hematoma: Insight from recent randomized trials and meta-analysis
Bibliographic record
Abstract
Embolization of the middle meningeal artery (EMMA) has emerged as a promising treatment for non-acute subdural hematoma (NASDH), either as an adjunct to surgical drainage or as a primary intervention in patients not undergoing surgery. Recent randomized controlled trials (RCTs) have investigated the efficacy of EMMA using dimethyl sulfoxide (DMSO)-based agents like ONYX and SQUID. The EMBOLISE trial demonstrated a significant reduction in hematoma recurrence with adjunctive EMMA, while the STEM trial showed similar benefits at 180 days. Conversely, the MAGIC MT trial found no significant difference in recurrence rates with EMMA. A meta-analysis of these trials confirmed EMMA's safety, with no significant increase in serious adverse events. The analysis indicated a modest overall benefit in reducing NASDH recurrence (risk difference −0.09, P = 0.02), though results were largely driven by the STEM trial. The benefit of adjunctive EMMA was less clear, with no significant effect found. Primary EMMA showed marginal benefit but with considerable variability. Factors such as primary outcome, trial design, patient demographics, and surgical biases complicate the interpretation of these findings. While the safety of EMMA is supported, its clinical efficacy remains inconclusive. Further trials, including patient-level meta-analyses, are needed to refine the role of EMMA in NASDH management and address existing gaps in 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 | 0.026 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.023 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 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".