**Researchers Launch Study to Test Weight-Loss Drugs as Potential Long COVID Treatment**
*By Julia Moore Voge*
In an innovative turn towards tackling long COVID, researchers at Scripps Research have initiated a nationwide digital clinical trial. Focusing on glucagon-like peptide-1 (GLP-1) drugs—medications traditionally prescribed for type 2 diabetes and obesity—the study aims to evaluate their effectiveness in alleviating persistent symptoms associated with long COVID.
The trial, which has already garnered significant attention, is open to 1,000 participants across the continental United States, excluding Hawaii. Designed as a randomized, double-blind, placebo-controlled study, it marks a groundbreaking approach to addressing the lingering effects of COVID-19 that millions are still battling. Participants will monitor their health through video check-ins and wearable devices, allowing researchers to gather real-time data on their progress.
Long COVID can manifest in various ways, including fatigue, brain fog, and respiratory issues, presenting a daunting challenge for those affected. The shift towards utilizing GLP-1 drugs represents a novel avenue for treatment, as these medications have shown promise in regulating metabolism and inflammation—key factors that could influence long COVID symptoms.
“We believe that the underlying mechanisms of these drugs could potentially provide relief for those suffering from long COVID,” said Dr. Michael T. McCoy, one of the study’s lead researchers. “By tapping into their ability to modulate inflammatory responses, we hope to offer a new solution for patients in need.”
The trial’s implications extend beyond long COVID; researchers are optimistic that the findings may also impact other infection-related conditions. With a robust methodology in place, the study represents a significant step forward in the quest for effective treatments in a post-pandemic world. Participants are encouraged to enroll as researchers embark on this critical journey to improve health outcomes for countless individuals.
