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Predicting Death Of Severe COVID-19 Patients May Be Possible with EKG

Oct, 2021 - By WMR

Predicting Death Of Severe COVID-19 Patients May Be Possible with EKG

Scientists found a way to predict death and worsening health of COVID-19 patients by detecting specific and dynamic changes on EKG.

A researcher’s team at the Mount Sinai Hospital, New York, discovered changes to electrical activity in the heart can aid in the prediction of worsening health and death of patient hospitalized for sever COVID-19 infection. The biomarker can be measured easily and it forecasts death time frame of the patients few days beforehand, according to the study published in the American Journal of Cardiology on August 8, 2021. The study reveals that shrinking waveforms on these tests can aid in the identification of patients with high-risk and can enable aggressive treatment.

COVID-19 patients at high-risk can be detected with blood-based biomarkers. However, these blood tests often take time to be analysed. The scientists found new biomarker that can be analysed with a simple EKG device. According to the researchers, this method can predict the demise of the patients two days beforehand. The criteria created by the team is named LoQRS. In the research, the LoQRS detected average time frame of 52 hours of the death in the first reading. The team studied EKGs of 140 COVID-19 patients hospitalized in the Mount Sinai hospital and compared them with 281 EKGs of influenza A or influenza B patients at the same hospital. The study showed that diminished waveforms on EKGs of COVID-19 patients were a sign of deteriorating in 74% of the patients. 52 patients died after two days of the first abnormal EKG.

Moreover, the study also discovered that LoQRS measure helped detecting also the patients with influenza who were declining very fast. The average time of death in influenza patients was approximately 6 days after the first LoQRS measure. The scientists claim that these diminishing waveforms can be a significant tool to recognize instant clinical changes required for patients during their hospital stay.

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