SARS-CoV-2 Is a Culprit for Some, but Not All Acute Ischemic Strokes: A Report from the Multinational COVID-19 Stroke Study Group.

COVID-19 SARS-CoV-2 cerebrovascular disorders cluster analysis comorbidity risk factors stroke

Journal

Journal of clinical medicine
ISSN: 2077-0383
Titre abrégé: J Clin Med
Pays: Switzerland
ID NLM: 101606588

Informations de publication

Date de publication:
01 Mar 2021
Historique:
received: 16 01 2021
revised: 11 02 2021
accepted: 16 02 2021
entrez: 3 4 2021
pubmed: 4 4 2021
medline: 4 4 2021
Statut: epublish

Résumé

SARS-CoV-2 infected patients are suggested to have a higher incidence of thrombotic events such as acute ischemic strokes (AIS). This study aimed at exploring vascular comorbidity patterns among SARS-CoV-2 infected patients with subsequent stroke. We also investigated whether the comorbidities and their frequencies under each subclass of TOAST criteria were similar to the AIS population studies prior to the pandemic. This is a report from the Multinational COVID-19 Stroke Study Group. We present an original dataset of SASR-CoV-2 infected patients who had a subsequent stroke recorded through our multicenter prospective study. In addition, we built a dataset of previously reported patients by conducting a systematic literature review. We demonstrated distinct subgroups by clinical risk scoring models and unsupervised machine learning algorithms, including hierarchical K-Means (ML-K) and Spectral clustering (ML-S). This study included 323 AIS patients from 71 centers in 17 countries from the original dataset and 145 patients reported in the literature. The unsupervised clustering methods suggest a distinct cohort of patients (ML-K: 36% and ML-S: 42%) with no or few comorbidities. These patients were more than 6 years younger than other subgroups and more likely were men (ML-K: 59% and ML-S: 60%). The majority of patients in this subgroup suffered from an embolic-appearing stroke on imaging (ML-K: 83% and ML-S: 85%) and had about 50% risk of large vessel occlusions (ML-K: 50% and ML-S: 53%). In addition, there were two cohorts of patients with large-artery atherosclerosis (ML-K: 30% and ML-S: 43% of patients) and cardioembolic strokes (ML-K: 34% and ML-S: 15%) with consistent comorbidity and imaging patterns. Binominal logistic regression demonstrated that ischemic heart disease (odds ratio (OR), 4.9; 95% confidence interval (CI), 1.6-14.7), atrial fibrillation (OR, 14.0; 95% CI, 4.8-40.8), and active neoplasm (OR, 7.1; 95% CI, 1.4-36.2) were associated with cardioembolic stroke. Although a cohort of young and healthy men with cardioembolic and large vessel occlusions can be distinguished using both clinical sub-grouping and unsupervised clustering, stroke in other patients may be explained based on the existing comorbidities.

Sections du résumé

BACKGROUND BACKGROUND
SARS-CoV-2 infected patients are suggested to have a higher incidence of thrombotic events such as acute ischemic strokes (AIS). This study aimed at exploring vascular comorbidity patterns among SARS-CoV-2 infected patients with subsequent stroke. We also investigated whether the comorbidities and their frequencies under each subclass of TOAST criteria were similar to the AIS population studies prior to the pandemic.
METHODS METHODS
This is a report from the Multinational COVID-19 Stroke Study Group. We present an original dataset of SASR-CoV-2 infected patients who had a subsequent stroke recorded through our multicenter prospective study. In addition, we built a dataset of previously reported patients by conducting a systematic literature review. We demonstrated distinct subgroups by clinical risk scoring models and unsupervised machine learning algorithms, including hierarchical K-Means (ML-K) and Spectral clustering (ML-S).
RESULTS RESULTS
This study included 323 AIS patients from 71 centers in 17 countries from the original dataset and 145 patients reported in the literature. The unsupervised clustering methods suggest a distinct cohort of patients (ML-K: 36% and ML-S: 42%) with no or few comorbidities. These patients were more than 6 years younger than other subgroups and more likely were men (ML-K: 59% and ML-S: 60%). The majority of patients in this subgroup suffered from an embolic-appearing stroke on imaging (ML-K: 83% and ML-S: 85%) and had about 50% risk of large vessel occlusions (ML-K: 50% and ML-S: 53%). In addition, there were two cohorts of patients with large-artery atherosclerosis (ML-K: 30% and ML-S: 43% of patients) and cardioembolic strokes (ML-K: 34% and ML-S: 15%) with consistent comorbidity and imaging patterns. Binominal logistic regression demonstrated that ischemic heart disease (odds ratio (OR), 4.9; 95% confidence interval (CI), 1.6-14.7), atrial fibrillation (OR, 14.0; 95% CI, 4.8-40.8), and active neoplasm (OR, 7.1; 95% CI, 1.4-36.2) were associated with cardioembolic stroke.
CONCLUSIONS CONCLUSIONS
Although a cohort of young and healthy men with cardioembolic and large vessel occlusions can be distinguished using both clinical sub-grouping and unsupervised clustering, stroke in other patients may be explained based on the existing comorbidities.

Identifiants

pubmed: 33804307
pii: jcm10050931
doi: 10.3390/jcm10050931
pmc: PMC7957755
pii:
doi:

Types de publication

Journal Article

Langues

eng

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Auteurs

Shima Shahjouei (S)

Neurology Department, Neuroscience Institute, Geisinger Health System, Danville, PA 17822, USA.

Michelle Anyaehie (M)

Neurology Department, Neuroscience Institute, Geisinger Health System, Danville, PA 17822, USA.

Eric Koza (E)

Neuroscience Institute, Geisinger Commonwealth School of Medicine, Scranton, PA 18510, USA.

Georgios Tsivgoulis (G)

Second Department of Neurology, "Attikon" University Hospital, National and Kapodistrian University of Athens, School of Medicine, 12462 Athens, Greece.

Soheil Naderi (S)

Department of Neurosurgery, Tehran University of Medical Sciences, Tehran 14155-6559, Iran.

Ashkan Mowla (A)

Neurology Department, Neuroscience Institute, Geisinger Health System, Danville, PA 17822, USA.
Division of Stroke and Endovascular Neurosurgery, Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA.

Venkatesh Avula (V)

Neurology Department, Neuroscience Institute, Geisinger Health System, Danville, PA 17822, USA.

Alireza Vafaei Sadr (A)

Department de Physique Theorique and Center for Astroparticle Physics, University Geneva, 1211 Geneva, Switzerland.

Durgesh Chaudhary (D)

Neurology Department, Neuroscience Institute, Geisinger Health System, Danville, PA 17822, USA.

Ghasem Farahmand (G)

Iranian Center of Neurological Research, Neuroscience Institute, Tehran University of Medical Sciences, Tehran 14155-6559, Iran.

Christoph Griessenauer (C)

Neurology Department, Neuroscience Institute, Geisinger Health System, Danville, PA 17822, USA.
Research Institute of Neurointervention, Paracelsus Medical University, 5020 Salzburg, Austria.

Mahmoud Reza Azarpazhooh (MR)

Department of Clinical Neurological Sciences, Western University, London, ON N6A 3K7, Canada.

Debdipto Misra (D)

Steele Institute of Health and Innovation, Geisinger Health System, Danville, PA 17822, USA.

Jiang Li (J)

Department of Molecular and Functional Genomics, Geisinger Health System, Danville, PA 17822, USA.

Vida Abedi (V)

Department of Molecular and Functional Genomics, Geisinger Health System, Danville, PA 17822, USA.
Biocomplexity Institute, Virginia Tech, Blacksburg, VA 24060, USA.

Ramin Zand (R)

Neurology Department, Neuroscience Institute, Geisinger Health System, Danville, PA 17822, USA.

Classifications MeSH