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Study identities how antibody levels differ between those who suffer long COVID and those who don’t

“Published Tuesday in Nature Communications, the new findings are the first time scientists have identified how antibody levels differ between those who suffer long COVID and those who don’t. By combining the new data with a few risk factors, Boyman and his colleagues have developed a model that can calculate long COVID risk for any patient in the early stages of infection. As part of the study, the researchers studied a cohort of 175 COVID patients and 40 healthy individuals for one year. Among the COVID cases, 53.9 percent of mild infections and 82.2 percent of severe infections led to long COVID symptoms. In analyzing the blood of COVID cases, the research team found that PACS patients typically exhibited lower levels of two types of antibodies: IgM, which is important in early immune responses to infections; and IgG3. which plays a big role in combating viruses. These levels were stable over the course of the whole year, which means a blood sample taken at any point in time, regardless of infection status, always returned the same IgM and IgG3 results. Boyman and his team used the antibody data, along with risk factors like asthma and old age, to develop a predictive model that would score a person’s risk for COVID on a scale of 1 to 100. They tested the model out on another set of 395 COVID-19 patients. Though accuracy varied between groups and settings, Boyman and his team found the model was clinically useful in guiding treatment decisions for anyone whose PACS score was over 55. [h/t Jason Herman]

The research team is already in the process of developing an online tool that uses their new model to calculate long COVID risk in people. No answer yet for when it will be available, but if it passes muster through future testing, it could be an invaluable tool in helping deliver early treatment to patients to help prevent or mitigate long COVID—especially now that we’re increasingly on our way to seeing COVID become an endemic disease…”

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