1091 Thrombectomy in Elderly Stroke Patients Presenting With Low Aspects: Insights From STAR Registry
Bibliographic record
Abstract
INTRODUCTION: Four recent randomized controlled trials demonstrated the efficacy and safety of mechanical thrombectomy (MT) for large vessel occlusion acute ischemic strokes (LVO-AIS) patients presenting with low Alberta Stroke Program Early CT Score (ASPECTS). However, these trials included very few patients aged over 80 years. METHODS: Data from the Stroke Thrombectomy and Aneurysm Registry (STAR), an international prospectively maintained database, between 2013 and 2023 was used. LVO-AIS patients = 80-year-old presenting with ASPECTS = 5, who underwent MT for internal carotid artery (ICA), M1, or M2 segments of middle cerebral artery (MCA) occlusion. The primary outcome was 90-day favorable outcomes, defined as modified Rankin Scale [mRS] score of 0-3. Secondary outcomes included modified Thrombolysis in Cerebral Ischemia (mTICI) score, 90-day mortality and symptomatic intracranial hemorrhage (sICH). RESULTS: Among the 10,229 MT patients, 101 met the inclusion criteria. Successful recanalization was achieved in 81 (80.2%) of patients. 19 (18.8%) patients experienced 90-day favorable outcomes, with 8 (7.9%) achieving an mRS score of 0-2. sICH occurred in 14 (13.9%) patients, and the 90-day mortality rate was 49.5%. Only 1 patient (5.6%) = 90 years achieved a favorable outcome at 90 days, while 11 patients (21.2%) aged 80-84 years and 7 patients (22.5%) aged 85-89 did. Among all patients aged = 80 years, multivariate analysis identified higher ASPECTS (aOR, 1.21; 95% CI, 1.09 – 1.35; p < 0.001) as a predictor of 90-day favorable outcome, but it is not associated with 90-day mortality (aOR, 1.02; 95% CI, 0.93 – 1.12; p = 0.70). CONCLUSIONS: Our study highlights the efficacy and safety of mechanical thrombectomy for elderly patients aged = 80 years presenting with low ASPECTS. However, for individuals aged = 90 years, the decision to proceed with thrombectomy should be carefully considered on a case-by-case basis.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".