Comparison of embolic agents in preoperative embolization for intracranial meningiomas: multicenter adjusted analysis of 275 cases
Bibliographic record
Abstract
BACKGROUND: Preoperative embolization has been used for intracranial meningiomas for nearly 40 years with varying preferences for embolic materials and limited comparative data on their efficacy. METHODS: Consecutively treated patients from 2013 until 2023 who underwent preoperative embolization for meningioma from 12 centers across North America and Europe were included and classified by embolic material: (1) particles, (2) Onyx, and (3) coils. Primary outcomes included estimated blood loss (EBL), procedural complications, surgery duration, gross total resection (GTR), unplanned rescue surgery, modified Rankin Scale (mRS), and mortality. After unmatched analysis. Propensity score matching (PSM) subgroup analyses compared each pair of embolic materials, controlling for age, sex, body mass index, smoking, comorbidities, prior surgery, pre-treatment antithrombotics, WHO grade, tumor location, maximal diameter, and baseline mRS. RESULTS: A total of 275 patients (median age 47 years, 62.9% female) underwent preoperative embolization for meningioma. The mean maximum tumor diameter was 32.9±10.1 mm, with 61.1% classified as WHO I. Onyx was most frequently used 117 (42.5%), followed by particles 107 (38.9%), and coils (18.5%). Unmatched analysis revealed that Onyx was significantly associated with reduced EBL, surgery duration, and increased GTR, while decreasing unplanned rescue surgeries compared to particles and coils. PSM produced 89, 48, and 44 matched pairs for Onyx vs. Particles, Particles vs. Coils, and Onyx vs. Coils, respectively. Onyx demonstrated significant reductions against Particles in EBL (250 mL vs. 350 mL, P = 0.011) and surgical time (291 min vs. 403 min, P < 0.001), and against Coils in EBL (250 mL vs. 400 mL, P = 0.012) and surgical time (255 min vs. 347 min, P = 0.002). Onyx also showed higher rates of gross total resection compared to Particles (80.9% vs. 56.2%, P = 0.021) and Coils (88.6% vs. 56.8%, P = 0.002). No significant differences were observed in blood transfusion requirements, embolization-related complications mRS, or mortality rates across all comparisons. CONCLUSIONS: Onyx, a liquid embolic agent, reduces EBL which may explain the shorter surgery duration, higher GTR rates, and lower retreatment rates. Procedural risks and patient selection require 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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".