IDENTIFYING HUNDREDS of POTENTIAL SUBTYPES of Long COVID from the electronic health records of over 12 million patients !!! 💯👍
nature.com/articles/s4174…
2) This study used a powerful data analysis technique called topic modeling to identify hundreds of potential sub-types of Long COVID.
The analysis revealed that PASC and COVID-19 patients experienced significantly higher rates of various conditions.
3) These spanned the nervous system (e.g. fatigue, headaches), cardiovascular system (e.g. heart rhythm issues), lungs (e.g. pneumonia), and immune system (e.g. autoimmune conditions).
4) Importantly, the study also found that certain Long COVID sub-types were more common in specific patient groups based on their age, sex, or the pandemic wave they were infected in. For example, pediatric and adolescent PASC patients showed increases in skin/hair problems.
5) Overall, this unprecedented analysis provides a detailed, data-driven look at the diverse ways Long COVID can manifest. It confirms many known symptoms, while also suggesting new avenues for better diagnosing and understanding this complex, multi-faceted condition.
Thanks 🙏
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