Abstract P406: Revised Intracerebral Hemorrhage Expansion Definitions and Relationship With Care Limitations
Bibliographic record
Abstract
Background: Hematoma expansion (HE) is an important therapeutic target in intracerebral hemorrhage. Recently proposed HE definitions have not been validated, and no previous definition has accounted for withdrawal of care (WOC). Objective: To compare conventional and revised definitions of hematoma expansion (HE), while accounting for WOC. Methods: We analyzed data from the ATACH-2 trial, comparing revised definitions of HE incorporating intraventricular hemorrhage (IVH) expansion to the conventional definition of “≥6 mL or ≥33%”. The primary outcome was modified Rankin Scale of 4-6 at 90-days. We calculated the incidence, sensitivity, specificity, positive and negative predictive values, and c- statistic for all definitions of HE. Definitions were compared using non-parametric methods. Secondary analyses were performed after removing patients who experienced WOC. Results: Primary analysis included 948 patients. Using the conventional definition, the sensitivity was 37.1% and specificity was 83.2% for the primary outcome. Sensitivity improved with all three revised definitions (53.3%, 48.7%, and 45.3%, respectively), with minimal change to specificity (78.4%, 80.5%, and 81.0%, respectively). The greatest improvement was seen with the definition “≥6 mL or ≥33% or any IVH”, with increased c -statistic from 60.2% to 65.9% (p < 0.001). Secondary analysis excluded 46 participants who experienced WOC. The revised definitions outperformed the conventional definition in this population as well, with the greatest improvement in c -statistic using “≥6 mL or ≥33% or any IVH” (58.1% vs 64.1%, p < 0.001). Conclusions: HE definitions incorporating intraventricular expansion outperformed conventional definitions for predicting poor outcome, even after accounting for care limitations.
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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 | 0.050 | 0.132 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".