No Racial Disparity in Outcome Measures After Endovascular Treatment for Stroke in the Elderly
Bibliographic record
Abstract
Background and Purpose: Despite the lower rates of good outcomes and higher mortality in elderly patients, age does not modify the treatment effect of mechanical thrombectomy for large vessel occlusion strokes. We aimed to study whether racial background influences the outcome after mechanical thrombectomy in the elderly population. Methods: We reviewed a prospectively maintained database of patients with acute ischemic stroke treated with mechanical thrombectomy from October 2010 through June 2020 to identify all consecutive patients with age ≥80 years and anterior circulation large vessel occlusion strokes. The patients were categorized according to their race as Black and White. Univariable and multivariable analyses were performed to define the predictors of 90-day modified Rankin Scale and mortality in the overall population and in each race separately. Results: Among 2241 mechanical thrombectomy, a total of 344 patients (median [interquartile range]; age 85 [82–88] years, baseline National Institutes of Health Stroke Scale score of 19 [15–23], Alberta Stroke Program Early CT Score 9 [7–9], 69.5% females) were eligible for the analysis. White patients (n=251; 73%) had significantly lower median body mass index (25.37 versus 26.89, P =0.04) and less frequent hypertension (78.9% versus 90.3%, P =0.01) but more atrial fibrillation (64.5% versus 44.1%, P =0.001) compared with African Americans (n=93; 27%). Other clinical, imaging, and procedural characteristics were comparable between groups. The rates of symptomatic intracerebral hemorrhage, 90-day modified Rankin Scale score of 0 to 2, and mortality were comparable among both groups. On multivariable analysis, race was neither a predictor of 90-day modified Rankin Scale score of 0 to 2 (White race: odds ratio, 0.899 [95% CI, 0.409–1.974], P =0.79) nor 90-day mortality (White race: odds ratio, 1.368; [95% CI, 0.715–2.618], P =0.34). Conclusions: In elderly patients undergoing mechanical thrombectomy for acute ischemic stroke, there was no racial difference in terms of outcome.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".