Clinical characteristics and outcomes of acute ischemic stroke in patients with COVID-19: A systematic review and meta-analysis of global data
Bibliographic record
Abstract
Objective. There is increased concern regarding acute ischemic stroke (AIS) in patients with coronavirus disease 2019 (COVID-19). The aim of this study was to depict the manifestations and outcomes of COVID-19-associated AIS. Methods. We systematically searched for eligible studies describing AIS in patients with COVID-19 using PubMed, Embase, and Web of Science up to November 29, 2021. We complied with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and used the Newcastle–Ottawa Scale to assess data quality. The data were pooled using fixed- and random-effects models. Results. Thirty-eight eligible studies involving 76,894 participants were included in this meta-analysis. Compared with AIS patients who did not have COVID-19, patients with COVID-19 were more likely to have anterior circulation stroke (odds ratio [OR]: 2.29, 95% confidence interval [CI]: 1.03 – 5.10; I2: 37%), particularly involving the internal carotid artery (OR: 1.85, 95% CI: 1.19 – 2.88; I2: 0); more severe neurological deficit (National Institutes of Health Stroke Scale [NIHSS]) (weighted mean difference [WMD]: 3.21, 95% CI: 2.13 – 4.29; I2: 64%); higher proportion of cryptogenic stroke (OR: 1.83, 95% CI: 1.24 – 2.70; I2: 62%), large vessel occlusion (OR: 1.68, 95% CI: 1.10 – 2.57; I2: 75%), and multi-territory involvement (OR: 2.64, 95% CI: 1.62 – 4.29; I2: 0%); higher C-reactive protein levels (WMD: 55.90, 95% CI: 33.32 – 78.49; I2: 67%), and D-dimer levels (standardized mean difference: 0.81, 95% CI: 0.52 – 1.10; I2: 59%). The proportion of poor outcomes were higher among patients with COVID-19, including increased risk of in-hospital death (OR: 3.70, 95% CI: 2.73 – 5.02; I2: 64%) and lower possibility of favorable discharge (OR: 0.49, 95% CI: 0.39 – 0.61; I2: 0). However, COVID-19 did not increase the risk of hemorrhagic transformation (OR: 1.34, 95% CI: 0.91 – 1.98; I2: 39%) and symptomatic intracerebral hemorrhage (OR: 1.46, 95% CI: 0.81 – 2.62; I2: 0). Conclusion. AIS patients with COVID-19 seem to display a pattern of large vessel occlusion and multi-territory infarcts. These patients have high inflammatory marker levels and increased D-dimer levels, which implies that thrombosis and/or thromboembolism might be the underlying mechanism. These patients tend to have worse prognosis regardless of whether they receive reperfusion treatment.
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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 | 0.016 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.045 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".