Treatment of long COVID could be hampered by lack of consensus in identifying and diagnosing the condition, researchers say
In a new report, researchers say the challenges of treating long COVID are amplified by a critical issue: we do not know what constitutes long COVID or how to formally diagnose it, an issue that is further exacerbated by limited research data of varying quality and consistency.
Early reports foretell a difficult challenge with long COVID, which researchers call Post-Acute Sequelae of SARS-CoV-2 infection (PASC). Some patients with prior acute COVID-19 cases have continued to report new or persistent health issues affecting nearly every organ system.
Writing in the March 8 Annals of Internal Medicine, researchers from UCLA Health and the David Geffen School of Medicine at UCLA, with a colleague at the University of Washington in Seattle, point out that while PASC has been approved for inclusion and protections within the Americans with Disabilities Act, which has strict medical and legal paperwork requirements, there is limited study data or medical consensus on what constitutes long COVID.
“The first challenge when studying any disease is knowing how to diagnose it, and although we have seen serious medical consequences stemming from COVID-19, we do not yet have definitive diagnostic criteria,” said Lauren E. Wisk, PhD, a researcher with the Division of Internal Medicine and Health Services Research in the David Geffen School of Medicine at UCLA and the UCLA Fielding School of Public Health, the article’s first author. “We believe that as more high-quality data emerges, the current list of symptoms will become better refined, and the timing and duration of symptoms will become clearer. So far, however, these have remained elusive.”
“We need high-quality data and information that supports an accurate diagnosis before patients can receive appropriate supportive care and effective, disease-specific therapy,” said Joann G. Elmore, MD, MPH, professor at the David Geffen School of Medicine at UCLA and the UCLA Fielding School of Public Health, the article’s senior author. “The scientific research community will need to be able to provide data that helps the medical community to distinguish long COVID symptoms from those of other illnesses.”
Although multiple studies are in progress, the authors say making useful comparisons across studies are nearly impossible without uniformly applied criteria. They also point out that researchers must contend with confounding issues in study design that can skew results, such as biases that can result from patient’s own recollection and clinicians’ interpretation of symptoms.
“Due to the dynamic nature of the virus itself and the technology available to test, monitor, and treat infection, substantial variation may exist in apparent clinical presentation of PASC,” the authors write. “Now more than ever, we must implement robust, standardized, longitudinal assessments of health and well-being across systems and settings, including premorbid evaluation, to facilitate real-time monitoring of trends.”
In addition to recall and surveillance bias, study selection bias and health care access could produce misleading results, according to the article.
“People who were already vulnerable to socioeconomic and racial or ethnic disparities — people who often have limited access to health care — have disproportionately borne the burden of the COVID-19 pandemic. Now, inequities in the development, presentation and documentation of long COVID-19 may also be accentuated,” said Dr. Wisk.
The authors offer potential solutions to ensure equity in future study and treatment, first urging the medical community to come together on a case definition that can be consistently applied. They further recommend that researchers implement robust and standardized measures of potential risk factors and outcomes; consider risk of bias when designing studies; take steps to facilitate cross-study comparisons; and to “be judicious in application of this evolving evidence as we all strive to provide effective and efficient care that reduces prior inequities.”
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