Middle Meningeal Artery Embolization for Chronic Subdural Hematoma: A Case Series
Bibliographic record
Abstract
BACKGROUND: Chronic subdural hematoma (CSDH) represents a common neurosurgical condition particularly in the elderly. Middle meningeal artery embolization (MMAE) has been proposed as a treatment option for this condition. OBJECT: To demonstrate the feasibility of MMAE for the treatment of CSDH avoiding the risk of interrupting anticoagulation and reducing the perioperative risk in a Canadian health care institution. METHODS: A retrospective chart review of patients receiving MMAE as primary treatment for CSDH is presented. Baseline demographics are collected (age, sex, and side of hematoma). Outcomes of interest include hematoma thickness pre-intervention and at follow up, procedural and post-operative complications, and length of hospital stay. Clinical outcomes (subdural hematoma resolution) are supplemented by computed tomography (CT) imaging. RESULTS: Patients (N=4) underwent MMAE for the treatment of CSDH to avoid risk of cessation of anticoagulation and expected perioperative risk. Median age was 74 years. Two patients were on antithrombotic therapy at the time of intervention. Patient follow-up occurred at 1, 3, 6, and 9 months post-operatively. Resolution of symptoms and significant reduction of hematoma thickness was evident (up to 14 mm) at follow-up. Improvement in all cases was confirmed by CT and clinical evaluation. No patients suffered from complications or recurrence. CONCLUSION: The MMAE is a safe and practical treatment for CSDH, even in this rather frail patient cohort with some on anticoagulation.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".