Introduction: Stroke, a dreaded complication of SARS-CoV2, has been reported in 0.9 to 5% of SARS-CoV2 patients. There are concerns that SARS-CoV2 infection has a significant independent association with acute ischemic stroke, even in the absence of conventional cerebrovascular risk factors. Whether elevated levels of inflammatory biomarkers have predictive value in the occurrence of stroke in SARS-CoV2 is poorly understood.
Aim: To profile the characteristics of SARS-CoV2 positive patients with ischemic stroke (COVID-Stroke) and to identify the significance of elevated IBMs in the prediction of ischemic COVID-stroke.
Materials and methods: Clinical characteristics, stroke risk factors, laboratory parameters- including levels of inflammatory biomarkers, and outcome of SARS-CoV2 patients with stroke (n=60) were collected. SARS-CoV2 RT- PCR positive age, gender, and pulmonary severity matched non-stroke patients were taken as controls (n = 60). Binary multivariate logistic regression analysis was used to find the predictors of ischemic COVID-stroke.
Results: D-dimer > 441.8 ng/mL, LDH> 395U/L, ESR >19 mm/h and CRP> 0.2 mg/dL were independently found to be very strong predictors of occurrence of ischemic COVID-stroke (p < 0.001 for each). On multivariate analysis, D-dimer > 441.8 ng/mL, ESR > 19 mm/h, and RDW > 16.1% were found to be the most strong predictors of the occurrence of ischemic COVID-stroke. Conventional CVD risk factors- higher age (> 60years), presence of diabetes mellitus, and hypertension were not found to be significant predictors in multivariate analysis.
Conclusion: In SARS-CoV2 patients, D-dimer elevated beyond 441.8 ng/mL, ESR greater than 19 mm/h, and RDW widened more than 16.1% were the strongest predictors of the occurrence of ischemic stroke. This is the first study that attempts to find cut-off levels of IBMs in the prediction of ischemic COVID-stroke.
Keywords: COVID-19; Covid; Covid stroke; Ischemic stroke; Stroke.
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