Malignant Profile Detected by CT Angiographic Information Predicts Poor Prognosis despite Thrombolysis within Three Hours from Symptom Onset
Bibliographic record
Abstract
OBJECTIVE: A malignant profile of early brain ischemia has been demonstrated in the Diffusion and Perfusion Imaging Evaluation for Understanding Stroke Evolution (DEFUSE) trial. Patients with a malignant profile had a low chance for an independent functional outcome despite thrombolysis within 3-6 h. We sought to determine whether CT angiography (CTA) could identify a malignant imaging profile within 3 h from symptom onset. METHODS: We studied consecutive patients (04/02-09/07) with anterior circulation stroke who received CTA before intravenous thrombolysis within 3 h. We assessed the Alberta Stroke Program Early CT Score (ASPECTS) on CTA source images (CTASI). Intracranial thrombus burden on CTA was assessed with a novel 10-point clot burden score (CBS). We analyzed percentages independent (modified Rankin Scale score < or =2) and fatal outcome at 3 months and parenchymal hematoma rates across categorized combined CTASI-ASPECTS + CBS score groups where 20 is best and 0 is worst. RESULTS: We identified 114 patients (median age 73 years [interquartile range 61-80], onset-to-tPA time 129 min [95-152]). Among 24 patients (21%) with extensive hypoattenuation on CTASI and extensive thrombus burden (combined score < or =10), only 4% (1/24) were functionally independent whereas mortality was 50% (12/24). In contrast, 57% (51/90) of patients with less affected scores (combined score 11-20) were functionally independent and mortality was 10% (9/90; p < 0.001). Parenchymal hematoma rates were 30% (7/23) vs. 8% (7/88), respectively (p = 0.008). CONCLUSION: CTA identifies a large hyperacute stroke population with high mortality and low likelihood for independent functional outcome despite early thrombolysis.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".