Grading Embolization of Middle Meningeal Artery for Chronic Subdural Hematoma
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Embolization of middle meningeal artery (EMMA) is a relatively new treatment for chronic subdural hematoma (CSDH). To date, an objective method that assesses or describes the extent of EMMA for the treatment of CSDH does not exist. Recently, the concept of a novel grading scale for EMMA in patients with CSDH has emerged. However, this has not been applied to a clinical case setting and inter-rater reliability has not yet been studied. The purpose of this study was to validate the grading scale in clinical practice and to assess for inter-rater reliability. MATERIALS AND METHODS: We retrospectively examined consecutive patients who underwent EMMA for CSDH. Patients were included if the whole head angiogram from common carotid as well as external carotid arteries before and after EMMA were available in the arterial, capillary as well as venous phases. Two independent readers, each with more than 5 years of experience in independent practice, assessed the angiograms for the grading of EMMA and assigned a score ranging between 0 and 3. The grading score between the two readers were compared using Cohen's Kappa score to assess the inter-rater reliability. RESULTS: In 19 patients, we found that EMMA had no periprocedural morbidity and mortality. The number of cases in each EMMA grading score category are as follows: 0 n =1; 1 n =3; 2 n =1; and 3 n =10. There was substantial inter-rater reliability for the assessment of grading of EMMA (Kappa = 0.74). CONCLUSIONS: The novel EMMA grading scheme demonstrated substantial inter-rater reliability and appears promising.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".