Acute Ischemic Stroke in Patients With COVID-19
Bibliographic record
Abstract
Background and Purpose: Studies suggest an increased risk of adverse outcomes among patients with acute ischemic stroke (AIS) and coronavirus disease 2019 (COVID-19). Methods: Using Get With The Guidelines–Stroke, we identified 41 971 patients (AIS/COVID-19: 1143; AIS/no COVID-19: 40 828) with AIS hospitalized between February 4, 2020 and June 29, 2020, from 458 Get With The Guidelines–Stroke hospitals with at least one COVID-19 case and evaluated clinical characteristics, treatment patterns, and outcomes. Results: Compared with patients with AIS/no COVID-19, those with AIS/COVID-19 were younger, more likely to be non-Hispanic Black, Hispanic, or Asian, more likely to present with higher National Institutes of Health Stroke Scale scores, and had greater proportions of large vessel occlusions. Rates of thrombolysis and thrombectomy were similar between the groups. Door to computed tomography (median 55 [18–207] versus 35 [14–99] minutes, P <0.001), door to needle (59 [40–82] versus 46 [33–64] minutes, P <0.001), and door to endovascular therapy (114 [74–169] versus 90 [54–133] minutes, P =0.002) times were longer in the AIS/COVID-19 cohort. In adjusted models, patients with AIS/COVID-19 had decreased odds of discharge with modified Rankin Scale score of ≤2 (odds ratio, 0.65 [95% CI, 0.52–0.81], P <0.001) and increased odds of in-hospital mortality (odds ratio, 4.34 [95% CI, 3.48–5.40], P <0.001). ConclusionS: This analysis demonstrates younger age, greater stroke severity, longer times to evaluation and treatment, and worse morbidity and mortality in patients with AIS/COVID-19 compared with those with AIS/no COVID-19.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".