Poincaré maps on population-based data of subjects with a confirmatory diagnosis of COVID-19

• Published in: AIP conference proceedings Vol. 2947; no. 1
• Main Authors: Martínez-Garcés, Vania Jocelyn, Olguín-Rodríguez, Paola V., Mehta, Roopa, Almeda-Valdes, Paloma, Barajas-Martínez, Antonio, Ibarra-Coronado, Elizabeth, Arellano, Monserrat Ramírez, Fossion, Ruben, Frank, Alejandro, Aguilar-Salinas, Carlos A., Rivera, Ana Leonor
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Melville American Institute of Physics 05.10.2023
• Subjects: Biomarkers; Blood pressure; Complex systems; Poincare maps; Prognosis; System dynamics; Time series; Triglycerides
• ISSN: 0094-243X; 1551-7616
• DOI: 10.1063/5.0161645

Poincaré maps are a time series analysis technique, that consists in a scattered plot that allows the visualization of the dynamics in a time series. This study aims to visualize and characterize the behavior of complex systems (human body) in disease (COVID-19 disease with lung involvement), according to prognosis outcome, stratified by two comparable groups. The potential use of our work lies in its possible application for identifying biomarkers of physiological health and predictive biomarkers in the prognosis against COVID-19 by changes in system dynamics. Results show that certain variables such as Diastolic blood pressure, PaO2/FiO2, average epicardial fat, direct bilirubin, and Triglyceride-Glucose Ratio/BMI can be inferred as important predictive markers of worse prognosis against COVID-19, with dynamic becoming deterministic.