Researchers from the University of Washington School of Medicine found that long COVID is not a singular condition but has distinct symptom categories.
In the multicenter, prospective study published in Open Forum Infectious Diseases, researchers looked at the long COVID symptoms of 5,962 people with COVID-19 — 4,504 COVID-positive and 1,459 COVID-negative — at three and six months after acquiring the disease.
After examining the data, the team found that long COVID has four distinct phenotypes of general and fatigue-related symptoms.
Specifically, at three months post-diagnosis among people who tested positive: 72% had minimal symptoms,17% experienced tiredness; muscle and joint aches, and headache; 5% had tiredness, muscle and joint aches, and headache, plus taste and smell loss; 6% experienced multiple miscellaneous symptoms.
Among the COVID-negative participants, three-month data showed that 75% had almost no long COVID symptoms, 20% had tiredness, headache, and musculoskeletal symptoms, and 4% experienced miscellaneous symptoms.
In addition, when compared with the COVID-negative participants, COVID-positive individuals had a higher rate of taste and smell loss and cognition problems.
However, when the scientists tracked one group of participants, they found that 32% of COVID-positive individuals switched between different general symptom classes from three-to-six months.
The researchers suggest that these results add to the growing evidence that long COVID is not a singular condition as previously believed but a range of phenotypes that evolve and change over time.
In a news release, senior author Kari Stephens, Ph.D., an adjunct professor at the University of Washington School of Medicine, says, "This study will help us understand how we need to treat long COVID over time, in very specific ways for each patient depending on how their symptoms present."
- UW Medicine. Long COVID is not a single condition, study finds.
- Open Forum Infectious Diseases. Long COVID Clinical Phenotypes Up to Six Months After Infection Identified by Latent Class Analysis of Self-Reported Symptoms.