Association of clot burden score with radiographic and clinical outcomes following Solitaire stent retriever thrombectomy: analysis of the SWIFT PRIME trial
Bibliographic record
Abstract
BACKGROUND: The clot burden score (CBS) was developed as a tool to evaluate the extent of intracranial thrombus burden in patients with anterior circulation acute ischemic stroke. CBS is based on the presence or absence of contrast opacification on CT angiography (CTA). Its value in predicting radiographic and clinical outcomes in patients given endovascular stroke therapy remains unknown. OBJECTIVE: To evaluate the relationship between CBS and outcomes after stent retriever thrombectomy in the interventional arm of the SWIFT PRIME trial. METHODS: CBS was calculated for the endovascular arm (IV tissue plasminogen activator plus Solitaire stent retriever) of SWIFT PRIME using baseline CTA. The cohort of 69 patients was divided into three groups according to their CBS values: CBS 0-5 (n=14), CBS 6-7 (n=23), and CBS 8-9 (n=32). RESULTS: The mean age of the 69 patients who formed the study cohort was 63.2±13.1 years, mean National Institutes of Health Stroke Scale score was 16.8±4.5, and 55% of the patients were male. There was no difference in clinical characteristics among the three groups, except for the baseline Alberta Stroke Program Early CT Score (p=0.049). The site of proximal occlusion varied significantly among the three groups (p<0.001). Rates of successful recanalization (TICI 2b/3), complete recanalization (TICI 3 only) and of good clinical outcome at 3 months were similar among the three groups (p=0.24, p=0.35, and p=0.52, respectively). CONCLUSIONS: The combination of IV thrombolysis and stent retriever thrombectomy with the Solitaire device is highly effective in achieving successful recanalization and a good clinical outcome throughout the entire range of CBS values.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".