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Researchers Develop Algorithm To Predict Whether A Person Gets Long Covid

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Researchers with Mount Sinai Hospital and Yale University say they’re the first to identify specific blood biomarkers that can accurately identify long Covid—allowing them to create an algorithm to determine whether a patient is suffering from the lingering condition, according to a new study published Monday in the journal Nature.

Key Facts

The study shows that long Covid patients have clear immune and hormonal differences from patients who don’t have the condition.

The researchers analyzed 271 patients from Mount Sinai Hospital, Mount Sinai Union Square and the Yale School of Medicine between January 2021 and June 2022.

After dividing them into three groups using a questionnaire—those who have never had Covid-19, those who had fully recovered from a confirmed case of the virus and those experiencing active long Covid symptoms at least four months after they had Covid-19—they were able to analyze the similarities and differences in a number of biomarkers to create an algorithm to predict which patients belonged to which group.

That algorithm was able to predict which patients had long Covid with 96% accuracy, according to the study.

The researchers said the biggest differences they saw in long Covid patients were the amount of immune and hormonal dysfunction.

They said that the biggest factors were abnormal T cell activity (which refers to cells’ ability to activate the immune system), reactivation of multiple latent viruses (or the ability of the immune system to summon its response to specific viruses) and reductions in cortisol levels (which regulates your body’s stress levels, among other things).

What To Watch For

How this can be applied in the real world. The study’s lead investigator, David Putrino, who works with the Icahn Mount Sinai School of Medicine, said the study’s findings “can inform more sensitive testing for long COVID patients,” and be used to create “personalized treatments for long COVID that have, until now, not had a proven scientific rationale.” Overall, Putrino said the study gives scientific validity to the experiences of long Covid patients, though he notes that physicians must listen to patients and provide personalized treatment plans.

Crucial Quote

“There is no ‘silver bullet’ for treating long COVID, because it is an illness that infiltrates complex systems such as the immune and hormonal regulation,” Putrino said.

Key Background

Long Covid is a condition that occurs when patients continue experiencing symptoms and after-effects of Covid-19, such as brain fog or difficulty exercising, well after the initial infection. It was first identified around spring 2020 by unprofessional online groups of patients, and eventually the mainstream medical community took notice. Doctors still know very little about long Covid, but this study marks a significant step forward in understanding the condition.

Big Number

One in 13, or 7.5%. That’s how much of the entire U.S. adult population was experiencing long Covid symptoms as of June, regardless of whether they’ve been infected or not, according to the Centers for Disease Control and Prevention, which defined long Covid as symptoms lasting at least three months after an initial infection. Among only patients that have had Covid-19 in the past, that number is one in five.

Tangent

The study comes as health experts fear a potential new wave of the virus this fall. In the week ending September 9, the most recent data available, 20,538 people in the U.S. were hospitalized for Covid-19, according to the CDC. That’s a 7.7% increase over the week prior, though it is still a far cry from the peak in January 2022, when there were around 150,000 hospitalizations. Since the pandemic began, 1.14 million people in the U.S. have died from the virus.

Further Reading

People with long COVID have distinct hormonal and immune differences from those without this condition (Nature)

NIH Opens Clinical Trials For Long Covid Treatment (Forbes)

Covid Drug Paxlovid Now Less Effective Than In Early Trials—But It’s Still Great At Preventing Death (Forbes)

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