Mechanical thrombectomy in elderly stroke patients with low ASPECTS: insights from STAR
Bibliographic record
Abstract
BACKGROUND: The elderly population (≥80 years) were underrepresented in recent trials of endovascular thrombectomy (EVT) for anterior circulation large vessel occlusion acute ischemic stroke (LVO-AIS) with low Alberta Stroke Program Early CT Score (ASPECTS) (≤5). METHODS: This study analyzed data from a prospectively maintained database of 37 thrombectomy centers. The primary cohort of the study comprised patients with LVO-AIS aged ≥80 who underwent EVT with ASPECTS≤5 from 2013 to 2023. The primary outcome was favorable modified Rankin Scale (mRS) score of 0-3. Propensity score matching (PSM) and multivariate regression were applied. RESULTS: In a study of 14 233 patients undergoing EVT, 1741 patients were 80 or older, with 122 presenting with low ASPECTS. While successful recanalization rates were similar between age groups, patients aged ≥80 had significantly lower favorable 90-day mRS scores and higher mortality before propensity score matching (PSM). After PSM, differences in mortality and symptomatic intracranial hemorrhage (sICH) were no longer significant. Among all elderly patients, higher ASPECTS was an independent predictor of a 90-day favorable outcome but was not associated with 90-day mortality. For patients aged ≥80 years with low ASPECTS, favorable outcomes were associated only with lower rates of atrial fibrillation, baseline functioning (mRS 0-1), fewer thrombectomy passes, and higher likelihood of first-pass reperfusion within 30 min of puncture. CONCLUSION: While age ≥80 increases mortality and disability in patients with AIS and low ASPECTS, select elderly patients may still benefit from EVT when clinical factors are considered, supporting individualized treatment and better patient selection for future trials.
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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 | 0.003 |
| 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 | 0.000 |
| 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".