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

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

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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00415-021-10620-8.