The novel coronavirus is typically considered as a threat to lungs but one of the major problems linked with COVID-19 that based on the inflammatory effects caused by the infection can result in possible damage to the heart.
However, researchers from the Johns Hopkins University (JHU) have recently introduced a machine that can be used to identify the worse outcomes from the heart of COVID-19 patients.
“By predicting who’s at risk for developing the worst outcomes, health care professionals will be able to undertake the best routes of therapy or primary prevention and save lives,” says #HopkinsEngineer @NTrayanova. https://t.co/6LjgAHMEcg
— Johns Hopkins Engineering (@HopkinsEngineer) May 22, 2020
The JHU researchers received a $195,000 Rapid Response Research grant from the National Science Foundation (NSF) for machine use. The machine can detect worst-case scenarios including heart failure, sustained abnormal heartbeats, heart attacks, cardiogenic shock, and even death.
The machine will help the medical health professionals in recognizing the early warning signs. So, the professional bodies could easily identify those high-risk COVID-19 patients and would be able to make an early plan to save lives because the deadly virus has already made massive destruction on a global level.
As per the latest report by JHU, the virus has taken over 338,000 lives and over 5 million cases are still running up throughout the globe of which more than 2 million cases have been recovered from the deadly coronavirus.
The research team has recently got the approval from institutional review board (IRB) that works under the regulation of the Food and Drug Administration (FDA). The team is heading towards the hospital setting to test the new inventory which is significantly more advanced than the previous machines.
Now, to make the algorithm, the researchers are planning to recruit more than 300 patients that have been diagnosed with the infectious and life-threatening coronavirus and have also undergone with several tests such as an electrocardiogram (ECG), cardiac-specific laboratory tests, continuously-obtained vital signs like heart rate and oxygen saturation, and imaging data such as CT scans and echocardiography. These tests will help the team to identify if there is any specific heart injury in COVID-19 patients.
The sample will be collected from two of the hospitals that are working under the Johns Hopkins Health System (JHHS) including Suburban Hospital (SH) and Sibley Memorial Hospital (SMH).
The investigators are hoping that the advanced approach will give results within 24 hours so that it would be easy to take further actions if the findings of the machine suggest any threat to life as it can calculate multiple sources of data and can give risk score.
The project’s clinical collaborator, Allison G. Hays, associate professor of medicine in the JHU, School of Medicine’s Division of Cardiology said:
“This project aims to help clinicians quickly risk-stratify patients using real-time clinical data, the goal of widely disseminate this knowledge to help medical practitioners around the world in their approach to treating and monitoring patients suffering from COVID-19”.
Previous Study: A recent study published in the Journal of the American Medical Association (JAMA) has found a significant link between cardiovascular diseases (CVDs) and the severe acute respiratory sun dorm coronavirus 2 (SARS-CoV-2). The study has suggested that almost 1 in 5 COVID-19 patients have also suffered from heart injury, even if there are no respiratory symptoms.
"individuals with underlying chronic CVDs were both more susceptible to COVID-19 and more prone to critical conditions and death ". Acute Respiratory Infection and the Most Common Noncommunicable Epidemic—COVID-19 and Cardiovascular Diseases https://t.co/9hkRf7xGLn
— Colleen Norris (@WomensHearts2) March 26, 2020
Researchers around the world are stunned by the connection between respiratory disease and CVDs. But, the good news is that it has been predicted by the JHU team that the new approach will be very helpful to get rid of the hazardous outcomes by detecting the early warning signs of any specific cardiac event. If the discovery goes as planned, it will be available to any interested health care institution for further use.
The project’s principal investigator, Natalia Trayanova, the Murray B. Sachs Professor in the Department of Biomedical Engineering at the JHU, Schools of Engineering and Medicine said: “By predicting who’s at risk for developing the worst outcomes, health care professionals will be able to undertake the best routes of therapy or primary prevention and save lives”.
We have a team with great synergy. @trayanovalab @julie_shade @Dr_AshishDoshi have been instrumental in developing the concept. @julie_shade is the algorithm guru! And a fantastic clinical collaboration with @AllisonGHaysMD. @HopkinsMedicine @hopkinsheart @JHUBME @JHU_ADVANCE https://t.co/Q82L7zibb0
— NataliaTrayanova (@NTrayanova) May 22, 2020