Researchers may have exaggerated the risks of long Covid due to using flawed methods, study says
The true risks of developing long Covid may have been exaggerated because many of the studies that have been published so far are riven with ‘major flaws’, according to an analysis published today (26 September) in BMJ Evidence Based Medicine.
Some findings have unnecessarily fuelled anxiety among members of the public anxiety and influenced healthcare spending priorities, suggest first author Tracy Beth Høeg, who works in Epidemiology and Biostatistics at the University of California at San Francisco, and two colleagues. Other consequences include misdiagnoses and funds being diverted from people with other genuine long-term conditions linked to a Covid-19 infection, the authors note.
Their analysis suggests that researchers have used broad definitions or have failed to find appropriate, or any, comparison groups, when looking at the incidence, prevalence, and control of the condition. The problems have been further compounded by the inclusion of poorly conducted studies into systematic reviews and pooled data analyses that end up overstating risk, Dr Høeg and her colleagues note.
Epidemiological issues
The consequences of Covid-19 infection may include post-ICU syndrome and shortness of breath following pneumonia – but these are also associated with many upper respiratory viruses, the researchers point out.
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 Organization, the UK National Institute for Health and Care Excellence, Scottish Intercollegiate Guidelines Network and the Royal College of General Practitioners requires a causal link between the virus responsible for Covid-19 (SARS-CoV2) and a range of symptoms.
Not only should comparator (control) groups be included in long Covid studies, 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, say the researchers.
Sampling bias
During the early stages of the pandemic, when SARS-CoV-2 testing wasn’t widely available, studies were more likely to include a non-representative sample of SARS-CoV-2-positive patients by including fewer patients with mild or no symptoms. This is known as sampling bias, the research team explains.
Dr Høeg and her colleagues state: ‘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.’
The umbrella term ‘long Covid’ should be jettisoned in favour of different terms for specific after effects, the authors state.
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 [Tracy Beth Høeg et al]
Standards 'must be improved'
While the results of high-quality population studies on long Covid in adults and children have been reassuring, they point out, the body of research ‘is replete with studies with critical biases’.
The article concludes: ‘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.
‘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,’ the authors add.
To access the full version of the article – titled How methodological pitfalls have created widespread misunderstanding about long COVID doi 10.1136/bmjebm-2023-112338 – click https://ebm.bmj.com/lookup/doi/10.1136/bmjebm-2023-112338
Author: Ian A McMillan
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