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. 2022 Jan;269(1):1-11.
doi: 10.1007/s00415-021-10620-8. Epub 2021 May 24.

SARS-CoV-2 infection and acute ischemic stroke in Lombardy, Italy

Alessandro Pezzini  1 , Mario Grassi  2 , Giorgio Silvestrelli  3 , Martina Locatelli  4   5 , Nicola Rifino  6   7 , Simone Beretta  6   7 , Massimo Gamba  8 , Elisa Raimondi  9 , Giuditta Giussani  10 , Federico Carimati  11 , Davide Sangalli  12 , Manuel Corato  13 , Simonetta Gerevini  14 , Stefano Masciocchi  4 , Matteo Cortinovis  4 , Sara La Gioia  15 , Francesca Barbieri  3 , Valentina Mazzoleni  4 , Debora Pezzini  4 , Sonia Bonacina  4 , Andrea Pilotto  4 , Alberto Benussi  4 , Mauro Magoni  8 , Enrico Premi  8 , Alessandro Cesare Prelle  9 , Elio Clemente Agostoni  10 , Fernando Palluzzi  2 , Valeria De Giuli  5 , Anna Magherini  3 , Daria Valeria Roccatagliata  3 , Luisa Vinciguerra  5 , Valentina Puglisi  5 , Laura Fusi  16 , Susanna Diamanti  6   7 , Francesco Santangelo  6   7 , Rubjona Xhani  16 , Federico Pozzi  16 , Giampiero Grampa  16 , Maurizio Versino  11 , Andrea Salmaggi  12 , Simona Marcheselli  13 , Anna Cavallini  17 , Alessia Giossi  5 , Bruno Censori  5 , Carlo Ferrarese  6   7 , Alfonso Ciccone  3 , Maria Sessa #  15 , Alessandro Padovani #  4 ; STROKOVID group
Affiliations

SARS-CoV-2 infection and acute ischemic stroke in Lombardy, Italy

Alessandro Pezzini et al. J Neurol. 2022 Jan.

Abstract

Objective: To characterize patients with acute ischemic stroke related to SARS-CoV-2 infection and assess the classification performance of clinical and laboratory parameters in predicting in-hospital outcome of these patients.

Methods: In the setting of the STROKOVID study including patients with acute ischemic stroke consecutively admitted to the ten hub hospitals in Lombardy, Italy, between March 8 and April 30, 2020, we compared clinical features of patients with confirmed infection and non-infected patients by logistic regression models and survival analysis. Then, we trained and tested a random forest (RF) binary classifier for the prediction of in-hospital death among patients with COVID-19.

Results: Among 1013 patients, 160 (15.8%) had SARS-CoV-2 infection. Male sex (OR 1.53; 95% CI 1.06-2.27) and atrial fibrillation (OR 1.60; 95% CI 1.05-2.43) were independently associated with COVID-19 status. Patients with COVID-19 had increased stroke severity at admission [median NIHSS score, 9 (25th to75th percentile, 13) vs 6 (25th to75th percentile, 9)] and increased risk of in-hospital death (38.1% deaths vs 7.2%; HR 3.30; 95% CI 2.17-5.02). The RF model based on six clinical and laboratory parameters exhibited high cross-validated classification accuracy (0.86) and precision (0.87), good recall (0.72) and F1-score (0.79) in predicting in-hospital death.

Conclusions: Ischemic strokes in COVID-19 patients have distinctive risk factor profile and etiology, increased clinical severity and higher in-hospital mortality rate compared to non-COVID-19 patients. A simple model based on clinical and routine laboratory parameters may be useful in identifying ischemic stroke patients with SARS-CoV-2 infection who are unlikely to survive the acute phase.

Keywords: COVID-19; Risk factors; Stroke; Viral infection.

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Conflict of interest statement

The authors declare that they have no conflict of interest/competing interests.

Figures

Fig. 1
Fig. 1
Kaplan–Meier estimates of in-hospital death by COVID-19 status in patients with acute ischemic stroke. Testing of significance is by the log-rank test
Fig. 2
Fig. 2
The most representative tree plot of the 1000 trees used in the RF model. The tree visualizes a clear separation between ischemic stroke patients with COVID-19 who died in hospital and ischemic stroke patients with COVID-19 who survived, with the root node defined by the presence of COVID-19 symptoms at hospital admission. NIHSS National Institute of Health Stroke Scale, LDH lactate dehydrogenase, hs TpN high sensitivity cardiac troponin. COVID-19 symptoms and medical complications were binary variables
See this image and copyright information in PMC

References

    1. Gupta A, Madhavan MV, Sehgal K, Nair N, Mahajan S, Sehrawat TS, et al. Extrapulmonary manifestations of COVID-19. Nat Med. 2020;26:1017–1032. doi: 10.1038/s41591-020-0968-3. - DOI - PMC - PubMed
    1. Harapan BN, Yoo HJ. Neurological symptoms, manifestations, and complications associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease 19 (COVID-19) J Neurol. 2021 doi: 10.1007/s00415-021-10406-y. - DOI - PMC - PubMed
    1. Pezzini A, Padovani A. Lifting the mask on neurological manifestations of COVID-19. Nat Rev Neurol. 2020 doi: 10.1038/s41582-020-0398-3. - DOI - PMC - PubMed
    1. Ntaios G, Michel P, Georgiopoulos G, Guo Y, Li W, Xiong J, et al. Characteristics and outcomes in patients with COVID-19 and acute ischemic stroke: the Global COVID-19 Stroke Registry. Stroke. 2020 doi: 10.1161/STROKEAHA.120.031208. - DOI - PMC - PubMed
    1. Katz JM, Libman RB, Wang JJ, et al. Cerebrovascular complications of COVID-19. Stroke. 2020;51:e227–e231. doi: 10.1161/STROKEAHA.120.031265. - DOI - PMC - PubMed