Abstract TP22: Risk of Intracerebral Hemorrhage from Adjunct Intra-arterial Thrombolysis in Acute Ischemic Stroke Patients Undergoing Thrombectomy
Bibliographic record
Abstract
Background and Purpose: Intra-arterial thrombolysis as an adjunct to mechanical thrombectomy is increasingly being considered to enhance reperfusion in acute ischemic stroke patients. Intra-arterial thrombolysis may increase the risk of post-thrombectomy intracerebral hemorrhage (ICH) in certain patient subgroups. Methods: We analyzed acute ischemic stroke patients treated with mechanical thrombectomy in a multicenter registry. The occurrence of any (asymptomatic and symptomatic) post-thrombectomy ICH was ascertained using standard definition requiring serial neurological examinations and computed tomographic scans. We determined the risk of ICH in subgroups defined by clinical characteristics, and use of intravenous (IV) thrombolysis. Results: A total of 146 (7.5%) patients received intra-thrombolysis among 1953 acute ischemic stroke patients who underwent mechanical thrombectomy. The proportion of patients who developed any ICH was 26 (17.8%) and 510 (28.2%) among patients who were and were not treated with intra-arterial thrombolysis (p=0.006). Among patients who received IV thrombolysis (n=1042), the proportion of patients who developed ICH was 9 (16.7%) and 294 (30.7%) among patients who were and were not treated with intra-arterial thrombolysis (p=0.028). The risk was not different in strata defined by age, gender, location of occlusion, pre-procedure National Institutes of Health Stroke Scale score, time interval between symptom onset and thrombectomy, Alberta Stroke Program Early CT score, systolic blood pressure, and serum glucose concentrations. Conclusions: In patients undergoing mechanical thrombectomy, the risk of any ICH and sICH was not increased with intra-arterial thrombolysis, including in those who had already received IV thrombolytics.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".