Patone et al; MYOCARDITIS is not mild, you may get help as a young person, but 25 years later it comes knocking and often results in death; severe myocarditis has a 5-10 year life expectancy of 50%
What about a 75+ male who had myocarditis when around 40, recovered and is currently seemingly healthy. Currently had Pfizer 1st, Moderna 2nd - 1st booster and is considering the 2nd booster (total of 4 shots). What are his chances of getting myocarditis at this point?
While the authors shed some light on increased risk of myocarditis for the young in this pre-print, they still conclude by touting the benefits of vaccination. In my opinion, this is caused by the toxic environment where any criticism of the covid vaccine products has to be soft-pedaled or else it results in censorship.
For anyone interested, I performed the equivalent of a “peer review” for the pre-print- with no holds barred for critiquing the covid vaccines. The most important point the authors must clarify is that *all 12* of the deaths “post Sars-cov-2 infection” must have either been (1) due to “breakthrough infections” or else (2) the vaccination occurred after infection but well within 28 days of death. Either way, vaccine injury may have been a factor (perhaps *the* factor) in the death.
Formal peer review for anything related to Covid is clearly broken (see Lancet-gate). So maybe “review by social media” is the next best option.
Here is the text (the figure refers to Supplemental Table 2) (1/n)
Approximately one month ago, a paper submitted by Dr. Jessica Rose and Dr. Peter McCullough was accepted by reviewers and approved by the editor for publication on the topic of myocarditis events after Covid vaccination in the journal “Current Problems in Cardiology”. Their study demonstrated an unacceptably high risk of myocarditis for those who receive the Covid-19 vaccine, particularly for children. Shockingly, the publisher (Elsevier) blocked the publication of the paper, and thus the data and analysis competently assembled by Rose and McCullough was eliminated from the literature.
One of the outcomes of this brazen act of censorship is the message it sends to other researchers in the area: If you wish to be published, you must avoid, or at least soften, negative findings regarding Covid-19 vaccination. The act of the publisher casts a pall on the process of producing high-quality research for medical journals, which ideally relies on honest data sources and frank analysis.
More recently, a pre-print titled “Risk of Myocarditis following sequential COVID-19 vaccinations by age and sex” was produced by several highly regarded researchers based at the University of Oxford, University of Leicester, University of Edinburgh, King’s College of London, and University of Nottingham. Data collected in the study appears to be robust, with over 42 million individuals who received at least one Covid vaccination considered. The article is accessible here: https://www.medrxiv.org/content/10.1101/2021.12.23.21268276v1
To assist in the improvement of this article, and in the spirit of collegiality, I offer my services by providing an open review of the article. Naturally, my input will have no weight on whether the paper is published since this critique falls outside the framework of the formal peer review process. Nonetheless, under the present unique circumstances wherein a substantially negative outcome for the vaccines would be censored, this review might provide the curious reader with some insight. Specifically, if a question raised herein is not addressed by the authors, then one may reasonably assume it would lead to a very negative conclusion for the vaccines. Thus, by considering the omissions, a clever reader might be able to ascertain outcomes which occurred but are not permissible for discussion in the present, heavily censored environment. I lay out 12 points as follows:
1. The manuscript compares rates of myocarditis following (1) Covid vaccine administration and (2) SARS-CoV-2 infection. An excerpt of the authors’ summary is as follows: “The risk of hospital administration or death from myocarditis is greater following COVID-19 infection than following vaccination… However, the risk of myocarditis following vaccination is considerably higher in young males…” This article is the second produced by the authors with the first being devoted to multiple heart ailments. The authors remark in their previous Nature Medicine article that “Myocarditis is underdiagnosed in practice… thus our use of diagnostic codes for myocarditis from routine data suggests that the ascertainment of cardiac inflammation after COVID_19 vaccination is likely to be under- rather than over- represented.” If this statement also applies to the methods used in the present article, the same statement should be included. The authors’ previous article also provided an analysis of the effects of SARS-CoV-2 infection on the heart, concluding that it “was associated with a substantial increase in the risk of hospitalization or death from myocarditis, pericarditis, and cardiac arrhythmia.” (See https://www.nature.com/articles/s41591-021-01630-0.pdf )
2. The authors include ChAdOx1 (Astrazeneca), BNT16b2 (Pfizer/BioNTech) and mRNA-1273 (Moderna) in their analysis. A strength of the study is that it involves a very large number of people. Outcomes of interest were hospital admission or death from myocarditis. A statistical approach (Self Controlled Case Series) was used to generate models which were fitted using conditional Poisson regression. Incident rate ratios (IRR) and relative rate ratios of hospital admissions or deaths were computed. Since the details of the model are opaque to this referee, this review will focus on comparisons of data provided in Table 1 and Supplementary Table 2.
3. There is an interesting trait related the number of people receiving vaccines doses in paragraph 5 of the main body of the paper. Of those receiving one dose of Astrazeneca (ChAdOx1), 97.1% ( 20,059,058 out of 20,646,456 ) went on to receive the second dose. However, the percentage receiving the Pfizer vaccine (BNT16b2) is quite a bit lower at 84.8% (17,294,004 out of 20,646,456), especially considering the large sample size. One might postulate that the percentage for the Pfizer vaccine is lower due to a higher number of adverse vaccine events. Do the authors have an alternate explanation for the difference in those who received the second dose of Pfizer compared to Astrazeneca? If so, please elaborate.
4. The authors selected a 28-day period for the exposure period after either documented Covid-19 infection or vaccination. Is there a reason why 28 days was chosen instead of, say, a 42-day period (which the authors note was used in their ref. 6)? Was the authors’ choice informed by the literature? If so, an appropriate a citation of the reference justifying the selection of a 28-day study period would be advisable.
5. Examining Supplementary Table 2 (top line), there were a total of 228 total cases of myocarditis reported for Astrazeneca, 234 for Pfizer, and 177 for a “Positive SARS-CoV-2 test.” Yet in Table 1, the IRR is shown to be much higher for a positive SARS-CoV-2 test (IRR= 8.40) than for the vaccines (with a range of IRR from 0.94 to 2.91, per dose). It seems as though the normalization approach within the statistical model leads one to interpret “177” to be a “large value” while “228” and “234” are much closer to “typical values.” While the normalization approach may in fact lead one to this conclusion, the outcome is non-intuitive to the reader and would benefit from more discussion by the authors. Additionally, Supplementary Table 2 shows there were 12 deaths due to myocarditis among those grouped under the “Positive SARS-Cov-2 test” column. Erstwhile, the number of deaths in the Astrazeneca totals 41, and the number of total deaths after the Pfizer vaccine is 38. No IRR is given for the number of deaths in Table 1. Is this an oversight? The concluding remarks by the authors include a statement which many will interpret as meaning that the number of deaths is higher following infection, and it seems that the authors could have analyzed the number of deaths separately from the number of otherwise hospitalized cases. Do the authors propose that the reader should interpret “12” in the SARS-CoV-test column to be a “large value” while the total deaths in the Astrazenca and Pfizer, respectively, at “41” and “38” as being much closer to “typical values?” Is it possible that the IRR computed deaths for the vaccines might yield a higher IRR than the value for the “Positive SARS-CoV-2 test” column.
6. Considering the large number of individuals in the study, it seems plausible that some individuals might have *both* (1) been vaccinated and (2) tested positive for SARS-COV-2 within the same 28-day window. How many of those individuals were there? How were those individuals classified? I speculate that there is a possibility the authors might have opted to classify any such individuals based on which occurred most proximal to diagnosis of myocarditis (vaccination or SARS-COV-2). As a result, a person who, in chronological order (1) received the vaccine, (2) got SARS-COV-2, and (3) was diagnosed with myocarditis (within the 28-day window) might be classified in the “Positive SARS-Cov-2 test group.” If in fact this approach was used, it seems counterintuitive that such a classification would provide the best method for fairly assessing how those who acquire myocarditis after Covid infection compare to those who received one or more doses of the vaccine. It is strongly recommended that he authors state how many individuals fall into this category, even if the number is zero.
7. In a similar vein, one might reason that a chronological ordering of (1) receiving the vaccine, (2) acquiring a SARS-COV-2 infection, and (3) being diagnosed with myocarditis might lead to erroneous conclusions about the safety of the vaccine, even if the vaccination falls *outside* the 28-day window. This problem might be remedied by splitting the far-right column of Supplementary Table 2 labeled “Positive SARS-Cov-2 Test” into two columns (indicated in the image below). One would be appropriate for the 113 individuals who were diagnosed with Covid prior to vaccination and the adjacent column would be for the remaining 64 (28 post-first-dose and 36 post-second dose) who acquired SARS-Cov-2 infection after vaccination. Such a parsing of the data would be instructive. For example, the careful reader might presently assume that all 12 deaths in the (presently) “Postitive-SARS-CoV-2 test” group might *all* have occurred from among the 64 who received the vaccine prior to getting infected. Such an inference is not entirely unfounded – after all, deaths rates among those diagnosed with myocarditis are higher for those who received the vaccine (18% for Astrazenca and 14% for Pfizer, combining doses) compared to only 6.8 percent for the “Postitive-SARS-CoV-2 test” group.
8. Let’s explore the chronology further: We know that: 4 events happened in some order for Vaccine (V), Myocarditis (M), Infection (I), Death (D). Clearly, Death must occur last. Furthermore, Myocarditis must be in the middle (otherwise neither the vaccine nor SARS-CoV-2 would have caused myocarditis). Also, to be in the “Positive SARS-CoV-2 Test” column, the death had to occur within 28 days of diagnosed infection. So chronologically the only options are:
(1) V > M > I > D. Here the vaccine likely led to myocarditis.
(2) V > I > M > D. Here, the vaccine allowed infection which led to
myocarditis. (Is it possible the vaccine made the cases worse?) (3) I > V > M > D. Here, the vaccine likely led to myocarditis since the infection preceded vaccination,
(4) I > M > V > D. Here, the vaccine directly precedes death within the 28-day window. Thus, vaccine injury, as opposed to myocarditis arguably caused the death - or at least it was likely a contributing factor. Ironically, the authors use the value of “12 deaths” in the sense that this is a “large” value. Yet, it is clear that all 12 either came after breakthrough infections or were more likely attributable to vaccine injury.
9. It is recommended that the authors address each of the above question of chronology simply by splitting the single “Positive SARS-Cov-2 Test” column into two columns. One column would represent “breakthrough cases” while the second would represent cases which occurred prior to vaccination. I fully expect that all 12 of the deaths will be represented as “breakthrough cases,” but perhaps the authors might enlighten me.
10. Of secondary interest, splitting the data in Column “Positive SARS-CoV-2” into two columns would also shed some light on how mean age differentiates between the two chronological orderings (I > M > V compared to V > I > M).
11. In the online methods section, the authors state that “Hospital admission for myocarditis often results in testing for SARS-CoV-2. Whilst these outcomes may well be caused by SARS-CoV-2 infection, reverse causality involved in their detection could over- or under- estimate the effect of infection on myocarditis.” I agree that it could overestimate the effect of SARS-CoV-2 infection on myocarditis. After all, someone who might suffer from myocarditis and subsequently pick up an (arguably) unrelated SARS-CoV-2 infection prior to being admitted to the hospital. This would be an example mentioned above wherein the chronology (using the terminology introduced above) would be M > I as opposed to I > M. Did any of the positive PCR test for any of the 177 cases occur one or more days *after* rather than *upon* hospital admission? If so, the authors should be very precise in stating how many of the 177 cases were diagnosed 1 or more days *after* hospital admission, which surely would lead to an over-estimation of the causation of myocarditis due to SARS-CoV-2. Related, I fail to understand how an underestimation, as described by the authors, might occur. Perhaps the authors might offer an example?
12. The authors’ opening sentence of their last paragraph of the main body states: “In summary, the risk of hospital admission or death from myocarditis is greater following COVID-19 infection than following vaccination…” If the value of “12 deaths” is “large” as implied in the summary by the authors, is it appropriate to draw the conclusion that SARS-CoV-2 by itself is the cause? After all, as described in points 5-9 above, it seems the authors should take into account whether those deaths occurred after a “breakthrough” infection. If the value is “large,” as computed by their sophisticated model, should the authors consider the possibility that the administration of the Covid vaccine might lead to a more severe form of myocarditis? Even for hospital admissions, it is unclear how the authors drew the conclusion that the IRR is larger for SARS-CoV-2 than for the Covid vaccines. The raw data in Supplementary Table 2 appears, at first blush, to counter this argument. Perhaps the statistical analysis section might be expanded to clarify the details of the model. For example, were any sensitivity studies performed using this complex model and if so, what was learned from them? Was there a reason the authors avoided using Supplementary Table 2, which seems to provide the means for a more direct comparison, to draw their conclusions?
It is quite unfortunate that the authors have been placed in such a difficult position. They may wish to provide clear and honest answers to all of the points raised above. However, if they do, the article itself might never see the light of day. Moreover, future funding opportunities may be lost and careers may be threatened. One option is to simply leave my questions and concerns unaddressed. Of course, if the authors fail to provide a complete and truthful account, many more people- including children- will certainly die from myocarditis caused by vaccine injury. At least there will be the consolation that astute readers might find this review and, with a wink and nod, understand that the authors’ omissions of truth indicate that their answers, if provided, would demonstrate that Covid vaccines cause significant harm. For example, if the authors do not change the “Positive SARS-CoV-2” column, one can simply assume that the 12 deaths should be properly categorized as vaccine injury instead of myocarditis resulting from SARS-Cov-2.
What about a 75+ male who had myocarditis when around 40, recovered and is currently seemingly healthy. Currently had Pfizer 1st, Moderna 2nd - 1st booster and is considering the 2nd booster (total of 4 shots). What are his chances of getting myocarditis at this point?
Hopefully Dr. Alexander will catch this article. A friggin science teacher obtained J&J vaccine and injected it into a minor, student's arm without parental consent or any medical background for her. https://www.dailymail.co.uk/news/article-10365977/Moment-science-teacher-no-medical-qualifications-vaccinates-sons-pal-without-parents-consent.html
While the authors shed some light on increased risk of myocarditis for the young in this pre-print, they still conclude by touting the benefits of vaccination. In my opinion, this is caused by the toxic environment where any criticism of the covid vaccine products has to be soft-pedaled or else it results in censorship.
For anyone interested, I performed the equivalent of a “peer review” for the pre-print- with no holds barred for critiquing the covid vaccines. The most important point the authors must clarify is that *all 12* of the deaths “post Sars-cov-2 infection” must have either been (1) due to “breakthrough infections” or else (2) the vaccination occurred after infection but well within 28 days of death. Either way, vaccine injury may have been a factor (perhaps *the* factor) in the death.
Formal peer review for anything related to Covid is clearly broken (see Lancet-gate). So maybe “review by social media” is the next best option.
https://t.me/arkmedic/2543?comment=21040
Here is the text (the figure refers to Supplemental Table 2) (1/n)
Approximately one month ago, a paper submitted by Dr. Jessica Rose and Dr. Peter McCullough was accepted by reviewers and approved by the editor for publication on the topic of myocarditis events after Covid vaccination in the journal “Current Problems in Cardiology”. Their study demonstrated an unacceptably high risk of myocarditis for those who receive the Covid-19 vaccine, particularly for children. Shockingly, the publisher (Elsevier) blocked the publication of the paper, and thus the data and analysis competently assembled by Rose and McCullough was eliminated from the literature.
One of the outcomes of this brazen act of censorship is the message it sends to other researchers in the area: If you wish to be published, you must avoid, or at least soften, negative findings regarding Covid-19 vaccination. The act of the publisher casts a pall on the process of producing high-quality research for medical journals, which ideally relies on honest data sources and frank analysis.
More recently, a pre-print titled “Risk of Myocarditis following sequential COVID-19 vaccinations by age and sex” was produced by several highly regarded researchers based at the University of Oxford, University of Leicester, University of Edinburgh, King’s College of London, and University of Nottingham. Data collected in the study appears to be robust, with over 42 million individuals who received at least one Covid vaccination considered. The article is accessible here: https://www.medrxiv.org/content/10.1101/2021.12.23.21268276v1
To assist in the improvement of this article, and in the spirit of collegiality, I offer my services by providing an open review of the article. Naturally, my input will have no weight on whether the paper is published since this critique falls outside the framework of the formal peer review process. Nonetheless, under the present unique circumstances wherein a substantially negative outcome for the vaccines would be censored, this review might provide the curious reader with some insight. Specifically, if a question raised herein is not addressed by the authors, then one may reasonably assume it would lead to a very negative conclusion for the vaccines. Thus, by considering the omissions, a clever reader might be able to ascertain outcomes which occurred but are not permissible for discussion in the present, heavily censored environment. I lay out 12 points as follows:
1. The manuscript compares rates of myocarditis following (1) Covid vaccine administration and (2) SARS-CoV-2 infection. An excerpt of the authors’ summary is as follows: “The risk of hospital administration or death from myocarditis is greater following COVID-19 infection than following vaccination… However, the risk of myocarditis following vaccination is considerably higher in young males…” This article is the second produced by the authors with the first being devoted to multiple heart ailments. The authors remark in their previous Nature Medicine article that “Myocarditis is underdiagnosed in practice… thus our use of diagnostic codes for myocarditis from routine data suggests that the ascertainment of cardiac inflammation after COVID_19 vaccination is likely to be under- rather than over- represented.” If this statement also applies to the methods used in the present article, the same statement should be included. The authors’ previous article also provided an analysis of the effects of SARS-CoV-2 infection on the heart, concluding that it “was associated with a substantial increase in the risk of hospitalization or death from myocarditis, pericarditis, and cardiac arrhythmia.” (See https://www.nature.com/articles/s41591-021-01630-0.pdf )
2. The authors include ChAdOx1 (Astrazeneca), BNT16b2 (Pfizer/BioNTech) and mRNA-1273 (Moderna) in their analysis. A strength of the study is that it involves a very large number of people. Outcomes of interest were hospital admission or death from myocarditis. A statistical approach (Self Controlled Case Series) was used to generate models which were fitted using conditional Poisson regression. Incident rate ratios (IRR) and relative rate ratios of hospital admissions or deaths were computed. Since the details of the model are opaque to this referee, this review will focus on comparisons of data provided in Table 1 and Supplementary Table 2.
3. There is an interesting trait related the number of people receiving vaccines doses in paragraph 5 of the main body of the paper. Of those receiving one dose of Astrazeneca (ChAdOx1), 97.1% ( 20,059,058 out of 20,646,456 ) went on to receive the second dose. However, the percentage receiving the Pfizer vaccine (BNT16b2) is quite a bit lower at 84.8% (17,294,004 out of 20,646,456), especially considering the large sample size. One might postulate that the percentage for the Pfizer vaccine is lower due to a higher number of adverse vaccine events. Do the authors have an alternate explanation for the difference in those who received the second dose of Pfizer compared to Astrazeneca? If so, please elaborate.
4. The authors selected a 28-day period for the exposure period after either documented Covid-19 infection or vaccination. Is there a reason why 28 days was chosen instead of, say, a 42-day period (which the authors note was used in their ref. 6)? Was the authors’ choice informed by the literature? If so, an appropriate a citation of the reference justifying the selection of a 28-day study period would be advisable.
5. Examining Supplementary Table 2 (top line), there were a total of 228 total cases of myocarditis reported for Astrazeneca, 234 for Pfizer, and 177 for a “Positive SARS-CoV-2 test.” Yet in Table 1, the IRR is shown to be much higher for a positive SARS-CoV-2 test (IRR= 8.40) than for the vaccines (with a range of IRR from 0.94 to 2.91, per dose). It seems as though the normalization approach within the statistical model leads one to interpret “177” to be a “large value” while “228” and “234” are much closer to “typical values.” While the normalization approach may in fact lead one to this conclusion, the outcome is non-intuitive to the reader and would benefit from more discussion by the authors. Additionally, Supplementary Table 2 shows there were 12 deaths due to myocarditis among those grouped under the “Positive SARS-Cov-2 test” column. Erstwhile, the number of deaths in the Astrazeneca totals 41, and the number of total deaths after the Pfizer vaccine is 38. No IRR is given for the number of deaths in Table 1. Is this an oversight? The concluding remarks by the authors include a statement which many will interpret as meaning that the number of deaths is higher following infection, and it seems that the authors could have analyzed the number of deaths separately from the number of otherwise hospitalized cases. Do the authors propose that the reader should interpret “12” in the SARS-CoV-test column to be a “large value” while the total deaths in the Astrazenca and Pfizer, respectively, at “41” and “38” as being much closer to “typical values?” Is it possible that the IRR computed deaths for the vaccines might yield a higher IRR than the value for the “Positive SARS-CoV-2 test” column.
6. Considering the large number of individuals in the study, it seems plausible that some individuals might have *both* (1) been vaccinated and (2) tested positive for SARS-COV-2 within the same 28-day window. How many of those individuals were there? How were those individuals classified? I speculate that there is a possibility the authors might have opted to classify any such individuals based on which occurred most proximal to diagnosis of myocarditis (vaccination or SARS-COV-2). As a result, a person who, in chronological order (1) received the vaccine, (2) got SARS-COV-2, and (3) was diagnosed with myocarditis (within the 28-day window) might be classified in the “Positive SARS-Cov-2 test group.” If in fact this approach was used, it seems counterintuitive that such a classification would provide the best method for fairly assessing how those who acquire myocarditis after Covid infection compare to those who received one or more doses of the vaccine. It is strongly recommended that he authors state how many individuals fall into this category, even if the number is zero.
7. In a similar vein, one might reason that a chronological ordering of (1) receiving the vaccine, (2) acquiring a SARS-COV-2 infection, and (3) being diagnosed with myocarditis might lead to erroneous conclusions about the safety of the vaccine, even if the vaccination falls *outside* the 28-day window. This problem might be remedied by splitting the far-right column of Supplementary Table 2 labeled “Positive SARS-Cov-2 Test” into two columns (indicated in the image below). One would be appropriate for the 113 individuals who were diagnosed with Covid prior to vaccination and the adjacent column would be for the remaining 64 (28 post-first-dose and 36 post-second dose) who acquired SARS-Cov-2 infection after vaccination. Such a parsing of the data would be instructive. For example, the careful reader might presently assume that all 12 deaths in the (presently) “Postitive-SARS-CoV-2 test” group might *all* have occurred from among the 64 who received the vaccine prior to getting infected. Such an inference is not entirely unfounded – after all, deaths rates among those diagnosed with myocarditis are higher for those who received the vaccine (18% for Astrazenca and 14% for Pfizer, combining doses) compared to only 6.8 percent for the “Postitive-SARS-CoV-2 test” group.
8. Let’s explore the chronology further: We know that: 4 events happened in some order for Vaccine (V), Myocarditis (M), Infection (I), Death (D). Clearly, Death must occur last. Furthermore, Myocarditis must be in the middle (otherwise neither the vaccine nor SARS-CoV-2 would have caused myocarditis). Also, to be in the “Positive SARS-CoV-2 Test” column, the death had to occur within 28 days of diagnosed infection. So chronologically the only options are:
(1) V > M > I > D. Here the vaccine likely led to myocarditis.
(2) V > I > M > D. Here, the vaccine allowed infection which led to
myocarditis. (Is it possible the vaccine made the cases worse?) (3) I > V > M > D. Here, the vaccine likely led to myocarditis since the infection preceded vaccination,
(4) I > M > V > D. Here, the vaccine directly precedes death within the 28-day window. Thus, vaccine injury, as opposed to myocarditis arguably caused the death - or at least it was likely a contributing factor. Ironically, the authors use the value of “12 deaths” in the sense that this is a “large” value. Yet, it is clear that all 12 either came after breakthrough infections or were more likely attributable to vaccine injury.
9. It is recommended that the authors address each of the above question of chronology simply by splitting the single “Positive SARS-Cov-2 Test” column into two columns. One column would represent “breakthrough cases” while the second would represent cases which occurred prior to vaccination. I fully expect that all 12 of the deaths will be represented as “breakthrough cases,” but perhaps the authors might enlighten me.
10. Of secondary interest, splitting the data in Column “Positive SARS-CoV-2” into two columns would also shed some light on how mean age differentiates between the two chronological orderings (I > M > V compared to V > I > M).
11. In the online methods section, the authors state that “Hospital admission for myocarditis often results in testing for SARS-CoV-2. Whilst these outcomes may well be caused by SARS-CoV-2 infection, reverse causality involved in their detection could over- or under- estimate the effect of infection on myocarditis.” I agree that it could overestimate the effect of SARS-CoV-2 infection on myocarditis. After all, someone who might suffer from myocarditis and subsequently pick up an (arguably) unrelated SARS-CoV-2 infection prior to being admitted to the hospital. This would be an example mentioned above wherein the chronology (using the terminology introduced above) would be M > I as opposed to I > M. Did any of the positive PCR test for any of the 177 cases occur one or more days *after* rather than *upon* hospital admission? If so, the authors should be very precise in stating how many of the 177 cases were diagnosed 1 or more days *after* hospital admission, which surely would lead to an over-estimation of the causation of myocarditis due to SARS-CoV-2. Related, I fail to understand how an underestimation, as described by the authors, might occur. Perhaps the authors might offer an example?
12. The authors’ opening sentence of their last paragraph of the main body states: “In summary, the risk of hospital admission or death from myocarditis is greater following COVID-19 infection than following vaccination…” If the value of “12 deaths” is “large” as implied in the summary by the authors, is it appropriate to draw the conclusion that SARS-CoV-2 by itself is the cause? After all, as described in points 5-9 above, it seems the authors should take into account whether those deaths occurred after a “breakthrough” infection. If the value is “large,” as computed by their sophisticated model, should the authors consider the possibility that the administration of the Covid vaccine might lead to a more severe form of myocarditis? Even for hospital admissions, it is unclear how the authors drew the conclusion that the IRR is larger for SARS-CoV-2 than for the Covid vaccines. The raw data in Supplementary Table 2 appears, at first blush, to counter this argument. Perhaps the statistical analysis section might be expanded to clarify the details of the model. For example, were any sensitivity studies performed using this complex model and if so, what was learned from them? Was there a reason the authors avoided using Supplementary Table 2, which seems to provide the means for a more direct comparison, to draw their conclusions?
It is quite unfortunate that the authors have been placed in such a difficult position. They may wish to provide clear and honest answers to all of the points raised above. However, if they do, the article itself might never see the light of day. Moreover, future funding opportunities may be lost and careers may be threatened. One option is to simply leave my questions and concerns unaddressed. Of course, if the authors fail to provide a complete and truthful account, many more people- including children- will certainly die from myocarditis caused by vaccine injury. At least there will be the consolation that astute readers might find this review and, with a wink and nod, understand that the authors’ omissions of truth indicate that their answers, if provided, would demonstrate that Covid vaccines cause significant harm. For example, if the authors do not change the “Positive SARS-CoV-2” column, one can simply assume that the 12 deaths should be properly categorized as vaccine injury instead of myocarditis resulting from SARS-Cov-2.