Scientists have claimed that there are six distinct "types" of COVID-19, each distinguished by a particular cluster of symptoms in patients, findings, if validated, can help physicians better diagnose and monitor those infected with the novel coronavirus.
The yet-to-be peer reviewed study, published in the medRxiv preprint platform, used a machine learning algorithm to analyse data from a subset of around 1,600 users in the UK and US with confirmed cases of COVID-19, who had regularly logged their symptoms using the app in March and April.
It analysed that if particular symptoms appeared together, and how this was related to the progression of the disease.
According to the scientists, led by those from King's College London in the UK, the findings have major implications for the clinical management of COVID-19 patients.
"These findings have important implications for care and monitoring of people who are most vulnerable to severe COVID-19," said Claire Steves, a co-author of the study from King's College London.
They said the research can also help doctors predict who is most at risk and likely to need hospital care in a second wave of coronavirus infections.