Prospective multicenter study of heart rate variability with ANI monitor as predictor of mortality in critically ill patients with COVID-19

Author:

Aragón-Benedí Cristian,Caballero-Lozada Andres Fabricio,Perez-Calatayud Angel Augusto,Marulanda-Yanten Angela Maria,Oliver-Fornies Pablo,Boselli Emmanuel,De Jonckheere Julien,Bergese Sergio D.,Martinez-Ubieto Javier,Pascual-Bellosta Ana,Ortega-Lucea Sonia,Fernandez Juan Pablo Quintero,Camacho Miguel Ángel Martínez,Gaviria-Villarreal Leidy,Mantilla Jorge Mejia,Lopez-Arribas Irene,Centeno-Perez Alejandro,Merino-Ruiz Margarita,Fernandez-Garcia Raquel,Fajardo-Perez Mario,Ledochowski Stanislas,

Abstract

AbstractThe purpose of this study is to demonstrate that the most critically ill patients with COVID-19 have greater autonomic nervous system dysregulation and assessing the heart rate variability, allows us to predict severity and 30-day mortality. This was a multicentre, prospective, cohort study. Patients were divided into two groups depending on the 30-day mortality. The heart rate variability and more specifically the relative parasympathetic activity (ANIm), and the SDNN (Energy), were measured. To predict severity and mortality multivariate analyses of ANIm, Energy, SOFA score, and RASS scales were conducted. 112 patients were collected, the survival group (n = 55) and the deceased group (n = 57). The ANIm value was higher (p = 0.013) and the Energy was lower in the deceased group (p = 0.001); Higher Energy was correlated with higher survival days (p = 0.009), and a limit value of 0.31 s predicted mortalities with a sensitivity of 71.9% and a specificity of 74.5%. Autonomic nervous system and heart rate variability monitoring in critically ill patients with COVID-19 allows for predicting survival days and 30-day mortality through the Energy value. Those patients with greater severity and mortality showed higher sympathetic depletion with a predominance of relative parasympathetic activity.

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

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