COVID symptoms shouldn't be downplayed in order to criticize the vaccines

We can hold different ideas without throwing the baby out with the bathwater.

Cover image: AlexLMX/ iStock / Getty Images Plus

In the past few months there’s been a strange trend among COVID vaccine critical people in which ideas surrounding harms from the virus have been discarded as being myths.

Several people have made the assumption that long COVID isn’t real, although the studies used to make such arguments are usually self-reported, online/telephone surveys which don’t provide an actual way of assessing these claims. However, this hasn’t stopped people from making assumptions that long COVID has been made up, maybe as a way to get ahead of the vaccines to cover up adverse reactions or because the data was never there (usually it falls along the former).

Recently Brian Mowrey¹ has raised some grounded criticisms against the term cytokine storm as there doesn’t appear to be a “storm” of inflammatory markers brewing in many of those severely infected with SARS-COV2.

Tolerance and severe disease, pt. 1

Here, the argument isn’t inherently against inflammation occurring, but more that this phenomenon of a cytokine storm may not be as prevalent or extreme as it has been made out, and is certainly a reasonable remark given some of the evidence. Rather, it’s possible that the term gained legs partially due to media attention with “sciency” sounding words and researchers who may not have spent time assessing the information, of which I would argue I was one, although I personally haven’t looked too deeply into the cytokine storm phenomenon to be able to fully refute claims in any direction.

The burden of science isn’t to proclaim a consensus thought or opinion, but to see where the evidence wind blows, piecing together the available information, and making a judgement as to what the prevailing information argues. More importantly, it’s critical to understand why certain studies may not show the same results as one another even though they are measuring the same variables or endpoints.

However, what has begun to emerge among vaccine critics is a driving narrative that sidesteps any consequences of a SARS-COV2 infection, especially if it shares any overlap with vaccine adverse reactions.

Again, we are seeing this with long COVID but we’re also seeing it with other concepts as well.

For instance, a while back I saw several comments that myocarditis does not occur with COVID infection², citing a systematic analysis from Almamlouk et al.³ as evidence to support a “myocarditis from COVID is a myth narrative”.

Upon looking at the Abstract one can maybe infer such a conclusion, especially with the Almamlouk et al. review which collected dozens of articles which referenced myocarditis relating to COVID.

The reported Results in the Abstract note the following (emphasis mine):

This review cohort contained 50 studies including 548 hearts. The median age of the deceased was 69 years. The most prevalent acute cardiovascular findings were myocardial necrosis (median: 100.0%; IQR, 20%–100%; number of studies = 9; number of patients = 64) and myocardial oedema (median: 55.5%; IQR, 19.5%–92.5%; number of studies = 4; number of patients = 46). The median reported prevalence of extensive, focal active, and multifocal myocarditis were all 0.0%. The most prevalent chronic changes were myocyte hypertrophy (median: 69.0%; IQR, 46.8%–92.1%) and fibrosis (median: 35.0%; IQR, 35.0%–90.5%). SARS-CoV-2 was detected in the myocardium with median prevalence of 60.8% (IQR 40.4-95.6%).

Zero percent?! Damning if true. IF true.

The problem with this dissemination of information is that it again falls under the fallacy of Abstract-only reading as a method of assessing information, wherein the actual information from an article may actually be overlooked.

Note that the above result references median reported prevalence.

For those who have a basic knowledge of statistics remember that median refers to the middle number among a dataset when organized numerically. However, it doesn’t tell much about the spread of the information or much about the other values.

Let’s suppose that 5 students took a test, with the end results being 0, 0, 0, 57, and 95.

If we took the middle value i.e. the median we would get a value of 0. Pretty ridiculous test scores to be honest—that teacher should probably be fired for such horrendous marks. However, if we were to examine the actual datasets we’d notice that one student would appear to be very close in getting a passing grade, with another getting a near perfect.

By taking the median value we may argue that the entire class just completely bombed this test, yet in reality several people bombed while a few select individuals did not.

In the case of the Almamlouk et al. review several of the reports on myocarditis were based on case autopsy reports, dealing with a very small autopsy sets of COVID-related deaths.

Compiling case reports in such a way essentially introduces tons of 0’s into the dataset of reports. Having 10 case reports focusing on 1 individual each and showing no signs of myocarditis is different than 1 study of 30 people which may show a prevalence of 10%.

Here, it appears that the pooling of reports and taking the median value has caused people to overlook the fact that several of the reports actually noted cases of myocarditis:

Few cases reported extensive myocarditis, ranging from 0.0% to 19.3%, with a median of 0.0% across 10 studies [20,23,26,28,32,37,[39], [40], [41], [42]] with a total of 175 cases (Fig. 3). Grosse et al., who authored the only consecutive study to report a prevalence for this finding, did not find any cases of extensive myocarditis across 14 cases. Focal active myocarditis was reported by 13 studies [20,21,23,25,26,28,32,[37], [38], [39], [40],42,43], ranging from 0.0% to 55.5%. Nine studies [19,20,26,28,32,37,39,42,44] with total of 131 cases described multifocal myocarditis with a median prevalence of 0.0% (IQR, 0.0%–2.1%). Finally, 15 studies [18,[20], [21], [22],[26], [27], [28],32,35,37,39,40,42,44,45] with 279 cases reported infiltrates without myocyte damage with a median prevalence of 0.6% (range, 0.0%–28.9%; Fig. 3).

Note here that when the range of prevalence among studies is mentioned the numbers are far more different than just 0.0%.

But why exactly did the researchers report median rather than the mean value? This is most likely due to the skewing of the reports as a mean is better used for evenly-distributed data. It’s quite apparent that this arrangement of reports would show a preponderance of 0% given very small sample sizes, even if the overall collection of autopsies would point to some incident of myocarditis even if lower than what was previously known.

But more important is the fact that Almamlouk, et al. is rather meticulous in noting several limitations in many of the conducted autopsies.

For instance, several of the reports on myocarditis were based on the Dallas criteria which took limited biopsy samples for assessment which may miss out on histological features of myocarditis:

The diagnosis of most cases of myocarditis included in this review were based on the Dallas criteria. This methodology, although widely accepted, is not without its inherent limitations. First and foremost, the Dallas criteria were developed to diagnose myocarditis by endomyocardial biopsy (EMB), not autopsy, wherein a more abundant amount of tissue is available for histologic evaluation. The generalization (and clinical significance) of small foci of myocyte damage within autopsy-derived cardiac tissue is challenging to ascertain. Other limitations of the Dallas criteria include significant interobserver variability and sampling errors [66,67].

Although less of an issue in autopsy-derived tissue, the focal nature of the disease leads to sampling errors that have been shown to compromise the sensitivity of the histopathological diagnosis of myocarditis by EMB [68,69]. Chow et al. had estimated that a mean of 17 samples per patient would be required to establish a diagnosis of myocarditis [69], which likely explains why examining an increased number of cardiac tissue blocks at the time of autopsy resulted in a greater likelihood of identifying focal myocarditis.

Limited tissue assessment means that features of myocarditis may have been overlooked in many of these reports, and in fact an article from 2006⁴ raised comments that the Dallas criteria may be an outdated method of diagnosing myocarditis.

So this systemic review is hardly a rebuking of myocarditis as several people have argued. It could, however, suggest that the prevalence of myocarditis may be lower than originally argued, although remarks are ambiguous both ways.

And even if myocarditis may not be prevalent, several noteworthy clinical features were noted including myocardial necrosis and enlarged hearts, suggesting that a severe COVID infection can still be detrimental to the heart even if not via myocarditis.

---

In the ongoing battle against vaccine tyranny many divergent thoughts have come about. In most cases it’s good to see different ideas as you never know what’s available unless you look.

However, in this attempt to end vaccine mandates and bring additional light to adverse reactions from the vaccines several arguments have been made that attempt to sidestep actual consequences related to the virus itself, taking a black/white approach when presenting information rather than spending time parsing and conciliating the information available.

We can argue that two things can be inherently true without removing one due to convenience over a narrative.

Long COVID can exist for many even if it may be lower than initially reported.

Cytokine storms may be a heuristic over exaggeration of a consequence of COVID infection, but elevated cytokine levels may still be present in many COVID-infected individuals.

Myocarditis can occur in those who are infected with COVID as well as those who get vaccinated. One does not need to concede one argument in order validate another. In fact, one should probably argue that a “safe and effective” vaccine shouldn’t come with any cases of myocarditis, full stop.

This comes along with an approach to reporting I have seen (not necessarily by those linked above, and certainly not by Brian) which encourages a position of showing people what to think rather than how to think. Even now I’ve seen a few sprinklings of articles touting the greatness of egg yolks and IgY in fighting SARS-COV2 that have overlooked the fact that hens need to be vaccinated in order to produce anti-spike IgY.

Readers are a lot more critical thinkers than we give them credit for. Allow them to see the information available and making their own conclusions rather than simplifying information to present one perspective while obfuscating another.

At the end of the day we still haven’t fully figured out why some people experience specific COVID symptoms or why some people experience vaccine-related adverse reactions. Rather than try to find THE ANSWER, we should be reminded that uncertainty and complexity drives much of science and life. It should be embraced rather than discouraged.

---

Substack is my main source of income and all support helps to support me in my daily life. If you enjoyed this post and other works please consider supporting me through a paid Substack subscription or through my Ko-fi. Any bit helps, and it encourages independent creators and journalists such as myself to provide work outside of the mainstream narrative.

Click on the image above or visit the website at https://ko-fi.com/moderndiscontent

1. I would argue that, unlike the other examples listed, Brian isn’t repudiating the role of cytokines, but more the fact that a widely used phrase of “cytokine storm” appears to lack the storm that has been widely alluded to. Several of my posts have remarked on a cytokine storm, but as stated by Brian it’s an ambiguous term.

2. To steel-man eugyppius it’s possible that the limited remarks made in his post didn’t allude to anything concrete. However, it’s the point that many readers may make a wrong conclusion when overlooking papers.

3. Almamlouk, R., Kashour, T., Obeidat, S., Bois, M. C., Maleszewski, J. J., Omrani, O. A., Tleyjeh, R., Berbari, E., Chakhachiro, Z., Zein-Sabatto, B., Gerberi, D., Tleyjeh, I. M., Cardiac Autopsy in COVID-19 Study Group, Paniz Mondolfi, A. E., Finn, A. V., Duarte-Neto, A. N., Rapkiewicz, A. V., Frustaci, A., Keresztesi, A. A., Hanley, B., … Grimes, Z. (2022). COVID-19-Associated cardiac pathology at the postmortem evaluation: a collaborative systematic review. Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases, 28(8), 1066–1075. https://doi.org/10.1016/j.cmi.2022.03.021

4. Baughman K. L. (2006). Diagnosis of myocarditis: death of Dallas criteria. Circulation, 113(4), 593–595. https://doi.org/10.1161/CIRCULATIONAHA.105.589663