Radiologic Evaluation Criteria for Chronic Subdural Hematomas: Recommendations for Clinical Trials
Bibliographic record
Abstract
Embolization of the middle meningeal artery has gained substantial interest as a therapy for chronic subdural hematomas. For the results of the currently running chronic subdural hematoma trials to inform clinical practice, sufficient accuracy and matching definitions are necessary. We summarized the current practice in chronic subdural hematoma evaluation and derived suggestions on reporting standards using the {Nested} Knowledge AutoLit living review platform. On the basis of the most commonly reported data elements, we suggested a set of standardized image-based study end points for chronic subdural hematoma evaluation for future trials. The measurement methods and reporting standards as proposed in this article have been derived from published best practices and are endorsed by the European Society of Minimally Invasive Neurological Therapy's research committee. The standardization of radiologic outcome measures and measurement techniques in chronic subdural hematoma embolization trials would increase the impact and implication of each trial as well as facilitate data pooling for increased statistical power and, therefore, translation to clinical practice.
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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 | 0.141 | 0.242 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.012 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.010 | 0.004 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".