Researchers identify 6 distinctive clusters of COVID-19 symptoms
One of the tricky aspects of COVID-19 is infected individuals seems to experience a wide range of different illness. The virus might wreak havoc on one patient's gastrointestinal system, while it leads to shortness of breath and fever in another.
To help sort through some of the confusion, a new study, which has not been peer-reviewed, revealed six distinctive versions of the illness -- each with its own cluster of symptoms -- that may be among the most common. What's more, researchers at King's College discovered each category of symptoms were more likely to lead to different levels of severity in disease and need for hospitalization, offering hope that healthcare professionals may be able to predict patients' needs in the early stages of illness.
“These findings have important implications for care and monitoring of people who are most vulnerable to severe COVID-19,” said consultant geriatrician and a King's College lecturer Dr. Claire Steves, one of the researchers who worked on the study, in a press statement.
While cough, fever and loss of smell are usually highlighted as the three key symptoms of COVID-19, researchers used data from a symptom-tracker app with more than 4 million users to identify a long list of additional symptoms including headaches, muscle pains, fatigue, diarrhea, confusion, loss of appetite, shortness of breath and more.
Honing in on a subset of data from around 1,600 users infected with COVID-19 in the United Kingdom and United States, the team identified the six groups of symptoms outlined below:
1. Flu-like with no fever: Headache, loss of smell, muscle pains, cough, sore throat, chest pain, no fever.
2. Flu-like with fever: Headache, loss of smell, cough, sore throat, hoarseness, fever, loss of appetite.
3. Gastrointestinal: Headache, loss of smell, loss of appetite, diarrhea, sore throat, chest pain, no cough.
4. Severe level 1, fatigue: Headache, loss of smell, cough, fever, hoarseness, chest pain, fatigue.
5. Severe level 2, confusion: Headache, loss of smell, loss of appetite, cough, fever, hoarseness, sore throat, chest pain, fatigue, confusion, muscle pain.
6. Severe level 3, abdominal and respiratory: Headache, loss of smell, loss of appetite, cough, fever, hoarseness, sore throat, chest pain, fatigue, confusion, muscle pain, shortness of breath, diarrhea, abdominal pain.
Researchers then conducted further analysis to determine whether people in particular symptom clusters experienced more severe illness and were more likely to require breathing support.
They found 1.5% of patients in the first cluster, 4.4% in the second and 3.3% in the third required breathing support. These figures were 8.6%, 9.9% and 19.8% for the third, fourth and sixth clusters respectively. What's more, nearly half of the patients in cluster 6 ended up in hospital, compared with just 16% of those in the first.
Next, the team developed a model matching patients' age, sex, BMI and pre-existing conditions together with symptoms gathered five days from the onset of the illness. It predicted which cluster a patient falls into and their risk of requiring hospitalization and breathing support with more accuracy than an existing risk model based solely on age, sex, BMI and pre-existing conditions.
Because patients who require breathing support usually come to a hospital around 13 days into the illness, according to the study authors, this model could be useful to doctors by providing "early warning" as to who is most likely to need intensive care.
"“If you can predict who these people are at day five, you have time to give them support and early interventions such as monitoring blood oxygen and sugar levels, and ensuring they are properly hydrated - simple care that could be given at home, preventing hospitalisations and saving lives,” said Steves.
UC Berkeley professor of infectious disease and vaccinology Dr. John Swartzberg said the research has the potential to help doctors and other healthcare providers identify people who will require earlier and more robust intervention.
"Certainly, we will have to see how this performs in the 'real world,'" said Swartzberg, an expert on COVID-19 who didn't work on the study. "With widespread use, it should 'learn' and become progressively more effective."
Amy Graff is the news editor for SFGATE. Email her: firstname.lastname@example.org.