Article: Is Long COVID Really Chronic Fatigue Syndrome by Another Name?

[Sly Saint]

Even after the World Health Organization declares the end of the global pandemic, COVID-19 will continue to cast a long shadow. By some estimates, nearly a third of people with a symptomatic infection still experience debilitating symptoms months later. Much about Post-Acute Sequelae of SARS-CoV-2 infection (PASC), the clinical term for what is commonly referred to as Long (or Long-haul) COVID, is unknown. However, one intriguing clue can be found in its similarity to myalgic encephalomyelitis, a disease also known as chronic fatigue syndrome or ME/CFS.

Mady Hornig, a Columbia Mailman School psychiatrist renowned for her research on ME/CFS, joined Walter J. Koroshetz, director of the National Institute of Neurological Disorders and Stroke (NINDS), for a late June panel discussion on post-acute COVID. The panel was part of WNYC Radio’s 2021 Health Convening, hosted by Nsikan Akpan, health and science editor at New York Public Radio.

“We’re really dealing with a mystery right now,” said Koroshetz. Yet the similarities of Long COVID to ME/CFS are striking, starting with a significant overlap in the symptoms, notably fatigue, unrefreshing sleep or “post-exertional malaise”—a general sense of being unwell after even minor physical or cognitive exertion affecting a majority of those with long COVID, along with high rates of problems with memory and attention (“brain fog”). Pain is another feature in common. And the onset of both Long COVID and up to 75 percent of ME/CFS cases can be traced to a viral infection. Indeed, one might easily ask: could Long COVID and ME/CFS be one and the same?

https://www.publichealth.columbia.e...-really-chronic-fatigue-syndrome-another-name

 

[Forbin]

From the article:

Even before the pandemic, an estimated three million Americans were suffering from the disorder [ME/CFS].

I thought it was more often said to be about one million US cases (which is based on Leonard Jason's prevalence study).

I think the CDC once claimed 1-4 million cases, but, as I recall, that included cases of "chronic fatigue" that didn't really meet the definition(s) of ME/CFS.

 

[Webdog]

I thought it was more often said to be about one million US cases (which is based on Leonard Jason's prevalence study).

I think the CDC once claimed 1-4 million cases, but, as I recall, that included cases of "chronic fatigue" that didn't really meet the definition(s) of ME/CFS.

Perhaps they used this study.

"...a predicted prevalence of 857/100,000 (p > 0.01), or roughly 2.8 million in the U.S."

Estimating Prevalence, Demographics, and Costs of ME/CFS Using Large Scale Medical Claims Data and Machine Learning -- Valdez et. al. 2019
https://www.frontiersin.org/articles/10.3389/fped.2018.00412/full

Thread on this paper here​

 

[Forbin]

That's an interesting U.S. study, @Webdog. They attempt to avoid duplication of the "de-identified" patients who might be counted more than once during the period of 2011-2016 due to a change in insurance carriers. They do this by requiring patients in two subsets to have continuous coverage with the same carrier for either the entire 6 years between 2011-2016 (SUBSET 1), or a period of between 2-4 years continuous coverage during the same period of 2011-2016 (SUBSET 2).

Unfortunately, this period (2011-2016) includes the time when the U.S. Affordable Care Act (aka "Obamacare") went into effect. During this time some insurance carriers stopped offering certain individual plans (the kind that disabled/unemployed ME patients might have had) or those plans became prohibitively expensive (at least they did in my state). As a result, I could see a lot of ME patients needing to change their insurance carriers during this time. Even if you remained with the same carrier, a new policy obtained through a "state marketplace" would almost certainly have a different identification number, allowing you to be counted more than once.

Also, the six-year window would allow for duplication (possibly twice) in SUBSET 2, where only two years of continuous coverage is required. All this might have inflated the numbers.

On the other hand, the study used a lot of data analysis and "machine learning" which could have mitigated this in some way.