Middle meningeal artery embolization for chronic subdural hematoma: Does statin therapy improve outcomes? A propensity score-matched analysis
Bibliographic record
Abstract
BackgroundChronic subdural hematoma (cSDH) is a common condition in older adults, often treated with surgical-evacuation, though recurrence rates can reach 30%. Middle meningeal artery embolization (MMAE) has emerged as a treatment alternative. Statins have been explored as adjunct therapies, but literature regarding their combined use with MMAE is limited.MethodsUsing TriNetX platform, we divided patients with cSDH who underwent MMAE into two groups: with adjuvant statins and without. Additionally, we divided patients with cSDH who underwent MMAE + Surgery into two groups: with adjuvant statins and without. Propensity score matching was conducted to minimize baseline differences. Primary outcomes included unplanned readmissions, surgical-evacuations, and mortality within 6 months of diagnosis.ResultsWe identified 2371 patients with cSDH who underwent MMAE, 1631 underwent MMAE alone, and 740 underwent MMAE + Surgery. Among MMAE alone group, 393 patients received statin therapy. While MMAE + Surgery group had 188 patients who received statin therapy. There was no significant difference in unplanned readmission rates between statin and nonstatin groups among MMAE alone group (36.6% vs. 39.7%; odds ratio (OR): 0.88; 95% confidence interval (CI): 0.66-1.17; P = 0.375). Similarly, rates of surgical-evacuation and mortality were comparable between the two groups; to MMAE + Surgery group's results were similar. There was no significant difference in unplanned readmission rates between statin and nonstatin groups (38.2% vs. 33.7%; OR: 1.22; 95% CI: 0.79-1.88; P = 0.377). Repeat surgical-evacuation and mortality rates were comparable.ConclusionThis study demonstrates that adding statins to MMAE does not improve outcomes in terms of the studied outcomes. While MMAE remains an effective treatment, the role of adjunct medical therapies requires further investigation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".