Abstract WMP83: Prediction of Intracerebral Hematoma Expansion: Multicenter External Validation of the CTA Spot Sign Score
Bibliographic record
Abstract
Background and Purpose: The spot sign score (SSS) stratifies hematoma expansion risk in patients with acute intracerebral hemorrhage (ICH) but is not externally validated. We sought to validate the SSS and assess prognostic spot characteristics associated with hematoma expansion in a prospective multicenter study. Methods: We studied 228 ICH patients presenting < 6 hours post-onset enrolled in the PREDICT (PREdicting hematoma growth anD outcome in ICH using contrast bolus CT) study, a multicentre prospective observational cohort study of ICH patients evaluated with baseline non-contrast CT, CT angiography (CTA), and 24-hour follow-up CT. Primary outcome was significant hematoma expansion (>6ml or >33%). Secondary outcomes were absolute and relative expansion. Blinded CTA spot sign characterization (spot number, maximum axial size and attenuation, and relative attenuation compared to the ipsilateral internal carotid artery and superior sagittal sinus) and SSS calculation was performed independently by two neuroradiologists and a radiology resident. Multivariable regression for prediction of hematoma expansion was performed and diagnostic performance of the SSS and spot characteristics was examined with ROC analysis and tests for trend. Results: SSS independently predicted significant, absolute, and relative hematoma expansion (p-values of 0.001, <0.001, and 0.009, respectively), adjusting for initial hematoma volume, INR, mean arterial pressure, and time from onset-to-baseline CT, and demonstrated near perfect interobserver agreement (κ = 0.82). Spot number and SSS demonstrated similar area under the curve (AUC 0.69 vs. 0.68, p=0.149) for hematoma expansion. Incremental risk of hematoma expansion was demonstrated with increasing SSS however a significant trend was not identified (p trend=0.720). Of all spot characteristics, only spot number was independently associated with expansion (p<0.001) providing incremental risk stratification (p trend=0.050) and near perfect agreement (κ=0.85). Median absolute hematoma growth for 0, 1, 2 to 3, ≥4 spots was 0.4, 4, 12, 82 ml respectively. Conclusion: Spot number is the single best predictor of significant ICH expansion and appears to be as good as the total SSS in predicting expansion.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".