The paper defines “long Kovid” as symptoms persisting for more than four weeks, while a shorter duration of Kovid was defined to be less than 10 days, with no subsequent pause.
In about 20 people with Kovid-19, or 4.5%, are likely to experience symptoms for eight weeks or longer, prior analysis of data from the Kovid Symptom Study App. The analysis has not been published in a peer reviewed journal.
Data was collected from 4,182 users of the app in the UK, who reported testing positive for coronovirus and regularly logged their health information in the app.
When it came to the group of reported symptoms, the research identified two main groups of long Kovid victims. One group experienced predominantly respiratory symptoms, such as cough and shortness of breath, as well as fatigue and headaches. The second group experienced “multi-system” symptoms in many parts of the body, such as heart palpitations, bowel issues, pins and needles or numbness, and “brain fog.”
Dr. “It is important that we use the knowledge gained from the first wave of the pandemic to mitigate the long-term effects of the second. This should pave the way for early intervention trials to mitigate the long-term effects,” said Claire. . Claire said in a news release Stevens, clinical academic and senior author of King’s College London.
While the majority of people with Kovid-19 in the study reported it to be normal in 11 days or less, 1 in 7 had symptoms lasting for at least four weeks, about 1 in at least eight weeks, and approximately in 50 Was 1 For at least 12 weeks.
Long covid victims were also twice as likely to report relapse after being recovered compared with “short covid” (16% vs. 8.4%).
The study found that approximately 1 adult over the age of 70 or over 21.9% who tested positive for coronovirus developed a long covid. Women were 14.9% more likely to suffer from long-term kovid than men, compared to 9.5% of men – but only in the younger age group.
Those who developed longer Kovid had a slightly higher average BMI with shorter Kovid according to the paper. Researchers also found that people with asthma were more likely to develop long covariates, but found no clear link to any other underlying health conditions.
The analysis has several limitations, including that it is based on self-reported information, was conducted online through an app, and app users were approximately 70 plus women and youth.
Researchers used the information to develop a model to predict who is most at risk of long covariates based on their age, gender, and early symptom counts. Statistical tests showed that this simple prediction was able to detect two-thirds (69%) of those who went on to achieve long covariates (sensitivity), and 73% effective in avoiding false alarms (specificity) Were.
The team then tested this model against an independent dataset of 2,472 people who reported the result of a positive coronavirus antibody test with a range of symptoms and found that it gave similar predictions of risk.