: Heat shock proteins (HSPs) are stress proteins. The endogenous nitric oxide (NO) synthase inhibitor asymmetric dimethyl arginine (ADMA) is a mediator of endothelial dysfunction. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus causes endothelial dysfunction and coagulopathy through severe inflammation and oxidative stress. Using these markers, we analyzed the prognostic value of serum ADMA and HSP-90 levels for early prediction of severe coronavirus disease (COVID-19) patients. : A total of 76 COVID-19 patients and 35 healthy control subjects were included in this case-control study. COVID-19 patients were divided into two groups: mild and severe. : Serum ADMA and HSP-90 levels were significantly higher in the COVID-19 patients compared to the control subjects ( < 0.001). Additionally, serum ADMA and HSP-90 levels were determined to be higher in a statistically significant way in severe COVID-19 compared to mild COVID-19 ( < 0.001). Univariable logistic regression analysis revealed that ADMA and HSP-90, respectively, were independent predictors of severe disease in COVID-19 patients (ADMA (OR = 1.099, 95% CI = 1.048-1.152, < 0.001) and HSP-90 (OR = 5.296, 95% CI = 1.719-16.316, = 0.004)). When the cut-off value for ADMA was determined as 208.94 for the prediction of the severity of COVID-19 patients, the sensitivity was 72.9% and the specificity was 100% (AUC = 0.938, 95%CI = 0.858-0.981, < 0.001). When the cut-off value for HSP-90 was determined as 12.68 for the prediction of the severity of COVID-19 patients, the sensitivity was 88.1% and the specificity was 100% (AUC = 0.975, 95% CI= 0.910-0.997, < 0.001). : Increased levels of Heat shock proteins-90 (HSP-90) and ADMA were positively correlated with increased endothelial damage in COVID-19 patients, suggesting that treatments focused on preventing and improving endothelial dysfunction could significantly improve the outcomes and reduce the mortality rate of COVID-19. ADMA and HSP-90 might be simple, useful, and prognostic biomarkers that can be utilized to predict patients who are at high risk of severe disease due to COVID-19.

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http://dx.doi.org/10.3390/medicina60071041DOI Listing

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