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True long Covid risk likely 'exaggerated', says global study
The risk of post-Covid infections has been likely exaggerated with overly broad definitions, a lack of appropriate, or any, comparison groups, in studies looking at the incidence, prevalence, and control of the condition -- epidemiology -- have distorted the risks, according to a global team of researchers.
New York: The risk of post-Covid infections has been likely exaggerated with overly broad definitions, a lack of appropriate, or any, comparison groups, in studies looking at the incidence, prevalence, and control of the condition -- epidemiology -- have distorted the risks, according to a global team of researchers.
In the paper published in the journal BMJ Evidence-Based Medicine, the team said that this is further compounded by inclusion of poorly conducted studies into systematic reviews and pooled data analyses that end up overstating the risk yet again.
"The likely consequences of this include, but aren't limited to, increased public anxiety and health care spending; misdiagnoses; and diversion of funds from those who really do have other long term conditions secondary to Covid-19 infection," suggest the researchers including from universities of California, Southern Denmark, and Public Health England, UK.
Many after effects of Covid-19 infection include post-ICU syndrome -- a constellation of health issues that are present when the patient is in intensive care and which persist after discharge home -- and shortness of breath following pneumonia. However, these are common to many upper respiratory viruses, the researchers said.
None of the working definitions of "long Covid" used by influential health bodies, such as the US Centers for Disease Control and Prevention, the World Health Organisation, and the UK National Institute for Health and Care Excellence (NICE), among others, requires a causal link between SARS-CoV2, the virus responsible for Covid-19, and a range of symptoms.
Not only should comparator (control) groups be included in long Covid studies, when they often aren't, but they should also be properly matched to cases, ideally by age, sex, geography, socioeconomic status and, if possible, underlying health and health behaviours, which they rarely are, the researchers said.
"Our analysis indicates that, in addition to including appropriately matched controls, there is a need for better case definitions and more stringent [long Covid] criteria, which should include continuous symptoms after confirmed SARS-CoV-2 infection and take into consideration baseline characteristics, including physical and mental health, which may contribute to an individual's post Covid experience," said the researchers.
They also called for dropping the umbrella term long Covid in favour of different terms for specific after effects. While the results of high quality population studies on long Covid in adults and children have been reassuring, they pointed out that the body of research "is replete with studies with critical biases", setting out common pitfalls.
"Ultimately, biomedicine must seek to aid all people who are suffering. In order to do so, the best scientific methods and analysis must be applied. Inappropriate definitions and flawed methods do not serve those whom medicine seeks to help," the researchers said.
"Improving standards of evidence generation is the ideal method to take long Covid seriously, improve outcomes, and avoid the risks of misdiagnosis and inappropriate treatment," they added.
