Hemorrhagic Transformation After Thrombectomy for Tandem Occlusions
Bibliographic record
Abstract
Background and Purpose- Carotid artery stenting in tandem large vessel occlusion strokes is usually avoided because of the intracranial hemorrhagic risks induced by antiplatelet therapy during thrombectomy interventions. This study aimed to evaluate the incidence of hemorrhagic transformation following thrombectomy in large vessel occlusion strokes patients with atherosclerotic cervical carotid occlusion, associated factors, and clinical relevance. Methods- The TITAN (Thrombectomy in Tandem Lesions) collaboration pooled individual data of prospectively collected multicentric thrombectomy databases for consecutive anterior circulation tandem large vessel occlusion strokes patients who underwent thrombectomy. Hemorrhagic infarction (HI) and parenchymal hematoma (PH) were assessed within 24 hours. Results- Among 289 patients with atherosclerotic cause, 66 (24.7%) patients developed HI and 38 (14.2%) PH. Intracranial carotid occlusion, diabetes mellitus, absence of prior intravenous thrombolysis, and complete extracranial carotid occlusion were independent predictors of HI. Similar predictors were found for PH with addition of higher baseline National Institutes of Health Stroke Scale and Alberta Stroke Program Early CT Score <7. No detrimental effect of HI on 90-day clinical outcome was found. The occurrence of PH was associated with increased mortality rates (adjusted odds ratio, 2.63; 95% CI, 1.05-6.59; P=0.039) and had no detrimental effect on 90-day modified Rankin Scale 0 to 2 (adjusted odds ratio, 0.52; 95% CI, 0.20-1.28; P=0.25). Conclusions- Incidence of PH after tandem large vessel occlusion strokes thrombectomy is equivalent to those reported in the literature data for isolated occlusions. Similar predictors were found for PH and HI within 24 hours, whereas acute carotid artery stenting and antiplatelet therapy were not, suggesting an aggressive endovascular treatment of tandem occlusions.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".