Study of Biomarkers in the Long-term Impact of Coronavirus Infection in the Cardiorespiratory System

Overview

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) poses a significant threat to global health. As the disease progresses, a series of acute complications tend to develop in multiple organs. Beyond the supportive care, no specific treatment has been established for COVID-19. The effectiveness, both short-term and long-term, of some promising antivirals, such as the hydroxychloroquine combination with azithromycin, needs to be evaluated. This study aims to investigate the predictive role of cardiac biomarkers and pulmonary symptoms for late complications of COVID-19 coronavirus infection on the heart and lung in patients treated with the hydroxychloroquine / azithromycin combination therapy. Thus, COVID-19 coronavirus patients undergoing hydroxychloroquine / azithromycin combination therapy will be compared to patients not undergoing this therapy. The comparison will be made by the analysis of the relationships between (1) levels of ultrasensitive cardiac troponins collected at the beginning of the infection and cardiac magnetic resonance data in the 3rd and 12th months of troponin collection and (2) findings CT scans and the results of the ergospirometers tests performed in those same periods. It is expected to demonstrate that: (1) cardiac troponin and lung tomographic findings can predict late complications of COVID-19 coronavirus infection in the heart and lung, assessed by cardiac magnetic resonance and ergospirometers one year after the beginning of the infection, and (2) hydroxychloroquine / azithromycin combined therapy can abolish the onset of these complications late. Furthermore, the results may point to the need for more rigorous monitoring of cardiologists and pulmonologists of these patients, due to the risk of hemodynamic complications, arrhythmogenic and respiratory.

The aim of this study is to investigate the predictive role of cardiac biomarkers and significant pulmonary complications for late infection complications COVID-19 coronavirus on the heart and lung in patients treated with hydroxychloroquine / combination therapy azithromycin. COVID-19 positive test patients will be divided into two groups according to therapeutic conduct. So, with a case-control distribution respecting age and sex, the two patient groups will be defined as "arm" with therapy (study population) and "Arm" without therapy (population control). This study is prospective and consists of three times: 1\) T0- Moment of inclusion of the patient in the study, which coincides with the collection of clinical data and laboratory tests. (2) T3- In the 3rd month after inclusion in the study, the patient will make a medical visit where data new laboratory tests will be acquired. (3) T12- In the 12th month after inclusion in the study, the patient will make another medical visit where data clinical data will be obtained. Laboratory tests, which were altered during visit T3 will be repeated. COVID-19 coronavirus patients undergoing therapy combined hydroxychloroquine / azithromycin will be compared to patients not undergoing this therapy. The comparison will be performed by analyzing the relationships between (1) troponin levels ultrasensitive cardiac data collected at the beginning of the infection and data of cardiac magnetic resonances in the 3rd and 12th month of collection troponins and (2) acute tomographic findings and the results the ergospirometers tests performed in those same periods. In our understanding of COVID-19, its diagnosis, prevention and treatment are evolving quickly. As the disease spreads and new evidence emerges, it would be prudent to identify risk factors for the development of late cardiorespiratory complications in patients survivors of serious COVID-19 infections. This prospective study of patients with COVID-19, involving a systematic record of clinical-laboratory variables and chronic cardiorespiratory complications, will be beneficial for the development of a risk model for these complications and to identify and / or predict the response to various treatment modalities.