Ultraearly hematoma growth in active intracerebral hemorrhage
Bibliographic record
Abstract
OBJECTIVE: To determine the association of ultraearly hematoma growth (uHG) with the CT angiography (CTA) spot sign, hematoma expansion, and clinical outcomes in patients with acute intracerebral hemorrhage (ICH). METHODS: We analyzed data from 231 patients enrolled in the multicenter Predicting Haematoma Growth and Outcome in Intracerebral Haemorrhage Using Contrast Bolus CT study. uHG was defined as baseline ICH volume/onset-to-CT time (mL/h). The spot sign was used as marker of active hemorrhage. Outcome parameters included significant hematoma expansion (>33% or >6 mL, primary outcome), rate of hematoma expansion, early neurologic deterioration, 90-day mortality, and poor outcome. RESULTS: uHG was higher in spot sign patients (p < 0.001) and in patients scanned earlier (p < 0.001). Both uHG >4.7 mL/h (p = 0.002) and the CTA spot sign (p = 0.030) showed effects on rate of hematoma expansion but not its interaction (2-way analysis of variance, p = 0.477). uHG >4.7 mL/h improved the sensitivity of the spot sign in the prediction of significant hematoma expansion (73.9% vs 46.4%), early neurologic deterioration (67.6% vs 35.3%), 90-day mortality (81.6% vs 44.9%), and poor outcome (72.8% vs 29.8%), respectively. uHG was independently related to significant hematoma expansion (odds ratio 1.06, 95% confidence interval 1.03-1.10) and clinical outcomes. CONCLUSIONS: uHG is a useful predictor of hematoma expansion and poor clinical outcomes in patients with acute ICH. The combination of high uHG and the spot sign is associated with a higher rate of hematoma expansion, highlighting the need for very fast treatment in ICH patients.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".