The Impact of <scp>SARS‐CoV</scp>‐2 on Stroke Epidemiology and Care: A Meta‐Analysis
Bibliographic record
Abstract
Objective Emerging data indicate an increased risk of cerebrovascular events with severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) and highlight the potential impact of coronavirus disease (COVID‐19) on the management and outcomes of acute stroke. We conducted a systematic review and meta‐analysis to evaluate the aforementioned considerations. Methods We performed a meta‐analysis of observational cohort studies reporting on the occurrence and/or outcomes of patients with cerebrovascular events in association with their SARS‐CoV‐2 infection status. We used a random‐effects model. Summary estimates were reported as odds ratios (ORs) and corresponding 95% confidence intervals (CIs). Results We identified 18 cohort studies including 67,845 patients. Among patients with SARS‐CoV‐2, 1.3% (95% CI = 0.9–1.6%, I2 = 87%) were hospitalized for cerebrovascular events, 1.1% (95% CI = 0.8–1.3%, I2 = 85%) for ischemic stroke, and 0.2% (95% CI = 0.1–0.3%, I2 = 64%) for hemorrhagic stroke. Compared to noninfected contemporary or historical controls, patients with SARS‐CoV‐2 infection had increased odds of ischemic stroke (OR = 3.58, 95% CI = 1.43–8.92, I2 = 43%) and cryptogenic stroke (OR = 3.98, 95% CI = 1.62–9.77, I2 = 0%). Diabetes mellitus was found to be more prevalent among SARS‐CoV‐2 stroke patients compared to noninfected historical controls (OR = 1.39, 95% CI = 1.00–1.94, I2 = 0%). SARS‐CoV‐2 infection status was not associated with the likelihood of receiving intravenous thrombolysis (OR = 1.42, 95% CI = 0.65–3.10, I2 = 0%) or endovascular thrombectomy (OR = 0.78, 95% CI = 0.35–1.74, I2 = 0%) among hospitalized ischemic stroke patients during the COVID‐19 pandemic. Odds of in‐hospital mortality were higher among SARS‐CoV‐2 stroke patients compared to noninfected contemporary or historical stroke patients (OR = 5.60, 95% CI = 3.19–9.80, I2 = 45%). Interpretation SARS‐CoV‐2 appears to be associated with an increased risk of ischemic stroke, and potentially cryptogenic stroke in particular. It may also be related to an increased mortality risk. ANN NEUROL 2021;89:380–388
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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 | 0.014 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.052 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".