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    Review of 'Cerebral venous thrombosis and portal vein thrombosis: A retrospective cohort study of 537,913 COVID-19 cases'

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    Cerebral venous thrombosis and portal vein thrombosis: A retrospective cohort study of 537,913 COVID-19 casesCrossref
    This study's comparison between COVID-19 injury rate and COVID-19 vaccine injury rate is incorrect.
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    Cerebral venous thrombosis and portal vein thrombosis: A retrospective cohort study of 537,913 COVID-19 cases

    Background There are concerns about a link between the ChAdOx1 nCoV-19 and Ad26.COV2.S vaccines against COVID-19 and cerebral venous thrombosis (CVT) and other thrombotic events. One key missing component of the risk-benefit analysis of using such vaccines is the risk of these severe thrombotic events following COVID-19. Methods Using a retrospective cohort study based on electronic health records primarily in the USA, the absolute risks of CVT and portal vein thrombosis (PVT) in the two weeks following a diagnosis of COVID-19 (made between January 20, 2020 and March 25, 2021) were calculated. The risks were compared to cohorts of patients with influenza (diagnosed within the same period) and people receiving an mRNA vaccine (i.e. not the ChAdOx1 nCoV-19 and Ad26.COV2.S vaccines) against COVID-19 (matched for demographics and the main risk factors for CVT and PVT). Findings A total of 537,913 patients with a COVID-19 diagnosis were included. The incidence of CVT in the two weeks after a COVID-19 diagnosis was 42.8 per million people (95% CI 28.5–64.2). This was significantly higher than in a matched cohort of people who received an mRNA vaccine (RR = 6.33, 95% CI 1.87–21.40, P  = 0.00014) and patients with influenza (RR = 2.67, 95% CI 1.04–6.81, P  = 0.031). The incidence of PVT after COVID-19 diagnosis was 392.3 per million people (95% CI 342.8–448.9). This was significantly higher than in a matched cohort of people who received an mRNA vaccine (RR=4.46, 95% CI 3.12–6.37, P  < 0.0001) and patients with influenza (RR=1.43, 95% CI 1.10–1.88, P  = 0.0094).
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      The Importance of a Correct Infection Pool Estimation when Making a Comparison Between COVID-19 Injury Rates and COVID-19 Vaccine Injury Rates

      by Anette Stahel, MSc

       

      Summary

      On July 31, 2021 the above article, Cerebral Venous Thrombosis and Portal Vein Thrombosis: A Retrospective Cohort Study of 537,913 COVID-19 Cases, was published in EClinicalMedicine. Unfortunately, the study includes a method error which makes the comparisons between COVID-19 injury rates and COVID-19 vaccine injury rates in it incorrect. More specifically, the pool of people used as denominator when calculating the percentage of COVID-19 infected people who developed cerebral venous thrombosis, CVT, and portal vein thrombosis, PVT, is greatly inadequate. I'll here explain how come using a highly adequate infection pool estimation when conducting such a comparative study is of utmost importance. I'll also carry out a calculation of this infection pool based on what I consider to be more correct figures. In addition, I'll enclose an example of a COVID-19 infection pool estimation that I consider to be highly accurate, in the form of a section of a Swedish COVID-19 infection fatality rate study.

       

      Introduction and review

      On July 31, 2021 the above article, Cerebral Venous Thrombosis and Portal Vein Thrombosis: A Retrospective Cohort Study of 537,913 COVID-19 Cases, authored by Taquet et al from Oxford University, was published in EClinicalMedicine [1]. The title of the article describes its content very well, although in addition to investigating the occurence of cerebral venous thrombosis, CVT, and portal vein thrombosis, PVT, following COVID-19 diagnosis it also investigates the occurence of these conditions following influenza diagnosis and following administration of an mRNA vaccine against COVID-19.

      I've now gone through and reviewed this article and I'm sorry, but this study is not correct. That is, the pool of people used as denominator when calculating the percentage of COVID-19 infected people who developed CVT and PVT is greatly inadequate. I'll explain what I mean.

      On page 2 of the study, it's stated:

      "COVID-19 increases the risk of CVT and PVT compared to patients diagnosed with influenza, and to people who have received a COVID-19 mRNA vaccine."

      However, when comparing the risk of developing condition X from infectious disease Y with the risk of developing condition X from something else, e g vaccine Z, you first and foremost need to make a correct assessment of how how large the pool of people infected with Y is. And to do that, you need to make an estimate. Merely counting the number of people who've sought out primary or secondary care for their symptoms won't do. Not even if you include all the people who were asymptomatic but sought out the care center anyway in order to take a test to see if they were infected (simply because they wanted to know) and then tested positive. 

      No, you need to include all infected persons in the total pool of people belonging to the health care facility/facilities in question, including the ones who don't go test themselves because of being asymptomatic, or of not having the energy to do it due to their symptoms, or of being into alternative medicine, or of lacking interest/knowledge about the infection et c. There may be many of different reasons. This means you need do make an estimate, otherwise the denominator in the calculation of the percentage who develop condition X from infection Y becomes incorrect. 

      A study measuring the risk of developing condition X from infection Y using a smaller denominator than one including everyone infected may be useful at times, but it can not be used for comparison with a correctly calculated vaccine risk.

      I will use the study Estimation of the Lethality for COVID-19 in Stockholm County published by the Swedish Public Health Agency [2] as an example of a correctly calculated risk, based on an adequately defined denominator. The fact that this is a calculation of the lethality percentage from COVID-19 and not the CVT and PVT percentage is irrelevant, the point is that the same mathematics used in this study should've been applied in the present Oxford study. From page 13 in the Swedish study, in translation:

      "Recruitment was based on a stratified random sample of the population 0-85 years. In the survey we use, the survey for Stockholm County was supplemented with a self-sampling kit to measure ongoing SARS-CoV-2-infection by PCR test. The sampling took place from March 26 until April 2 and 18 of a total of 707 samples were positive. The proportion of the population in Stockholm County which would test positive was thus estimated at 2.5%, with 95% confidence range 1.4-4.2%."

      For a complex reason, which I won't go into but is described in detail in the study text, one needs to use a slightly higher percentage when multiplying it with the total number of people in the pool, but that's of minor importance. Anyway, in this study they had to use the figure 3,1169% and when they multiplied it with the number of people in Stockholm County, 2 377 000, they got 74 089. This estimate was then the correct denominator to use when calculating the percentage of people who died from COVID-19 in Stockholm County during this time period. 

      The numerator was the number of people who died in Stockholm County with a strong suspicion of COVID-19 as a cause, which was 432, no incorrectness there either - as long as a suspected cause number, not a diagnosed cause number, is also used as the numerator when calculating the lethality from the COVID-19 vaccine when the infection lethality and vaccine lethality rates are compared. 

      So, what they found was that the lethality from COVID-19 in Stockholm County was 0,58%. This is a correct figure, as long as we keep in mind the fact that some of the suspected COVID-19 deaths may later become diagnosed as unrelated to the infection. 

      The above is thus how the authors of the present study should've carried out their calculations but they didn't. From their text: 

      "Using a retrospective cohort study based on electronic health records primarily in the USA, the absolute risks of CVT and portal vein thrombosis (PVT) in the two weeks following a diagnosis of COVID-19 (made between January 20, 2020 and March 25, 2021) were calculated. (--) A total of 537,913 patients with a COVID-19 diagnosis were included."

      This excludes a considerable amount of infected persons in the total pool of 81 million people belonging to all of these primary and secondary care centers, who didn't go test themselves because of a number of reasons (being asymptomatic, being alternative medical, not having the energy or interest for it, et c). 

      If they'd used an adequate figure in the denominator, the percentage of people established to've developed CVT and PVT from COVID-19 would've gotten vastly lower. However, the percentage of people determined to've developed CVT and PVT from the mRNA COVID-19 vaccines was fully correctly carried out since there are no unregistered vaccinated cases and therefore the registered figure is to be used. Towards the end of the text the possibility is mentioned of a number of people having received their vaccination elsewhere and therefore not being included in the vaccinee pool, but that figure is likely to be very low.

      Via the study's Figure 2 and Table S2 from the OSFHome version [3], I calculated the following figures: First time CVT cases diagnosed after administration of the mRNA COVID vaccines amounted to 6.6 per million and first time PVT cases after same vaccines amounted to 12.5 per million.

      Now, there's a study titled Estimation of US SARS-CoV-2 Infections, Symptomatic Infections, Hospitalizations and Deaths Using Seroprevalence Surveys published by the American Medical Association [4], which has estimated the percentage of infected people in the US looking at roughly the same time period as the Oxford study. From the paper:

      "An estimated 14.3% (IQR, 11.6%-18.5%) of the US population were infected by SARS-CoV-2 as of mid-November 2020."

      With an infection rate around 14.3%, the estimated number of infected people of the 81 million patients in the healthcare database referred to in the study would've amounted to 11 583 000. This number gives us a hint as for the size of the denominator which should've been used in the calculation instead of the figure of 537 913 confirmed diagnoses. 

      However, since the Oxford study not only looked at CVT and PVT arising from people having the infection around mid-November 2020 but looked at a much longer time period, from January 20, 2020 to to March 25, 2021, a number far greater than 11 583 000 should be applied. What we need is to estimate how many of the 81 million patients were infected at least once during these 14 months in question. For the calculation to be really accurate, we need the total, accumulated number of infected people. But since that number isn't found without a very comprehensive and time consuming investigation, we instead have to use the signs ">" ("greater than") and "<" ("less than") here. So, the correct denominator, which should've been used instead of the 537 913 figure, is >11 583 000.

      Further, the study says that first time CVT was found in 19 of the patients following COVID-19 diagnosis and first time PVT in 94. This actually means that the rates of CVT and PVT elicited by COVID-19 were much lower than the rates of CVT and PVT elicited by the vaccines. COVID-19 elicited PVT cases, correctly calculated, amounted to <8.1 per million - only about two thirds of the 12.5 per million for the vaccines - and the CVT cases amounted to <1.6 per million - a mere fourth of the vaccines' 6.6.

      Interestingly, with their work including this method error, these authors have provided scientific validation of the growing suspicion that the COVID-19 vaccines give rise to thrombocytic complications to a much greater extent than does COVID-19 (which is the opposite of what's stated in the study), because even if the 537 913 figure is inadequate, the other figures in the study are most likely not.

      Finally, I'd like to suggest a reading through of the English translation of the Swedish COVID-19 lethality study that I took up in the beginning of my text as a correct, comparative example [5]. This is the main paper that the Swedish equivalent to the Centers for Disease Control and Prevention, the Public Health Agency (Folkhälsomyndigheten), refers to when talking about the COVID-19 lethality here and it's put up on one of the major information pages of their website. I really recommend reading all of it, because it explains so well and in such detail how come this model of denominator calculation without exception must be used in studies like these, which aim to investigate the rate of injuries/complications arising from an infectious illness.

       

      References

      1. Taquet, M, Husain, M, Geddes, J R, Luciano, S & Harrison, P J (2021) Cerebral Venous Thrombosis and Portal Vein Thrombosis: A Retrospective Cohort Study of 537,913 COVID-19 Cases EClinicalMedicine https://www.thelancet.com/action/showPdf?pii=S2589-5370%2821%2900341-2
      2. Svenska Folkhälsomyndigheten (2020) Skattning av Letaliteten för Covid-19 i Stockholms Län https://www.folkhalsomyndigheten.se/contentassets/da0321b738ee4f0686d758e069e18caa/skattning-letalitet-COVID-19-stockholms-lan.pdf
      3. Taquet, M, Husain, M, Geddes, J R, Luciano, S & Harrison, P J (2021) Cerebral Venous Thrombosis and Portal Vein Thrombosis: A Retrospective Cohort Study of 537,913 COVID-19 Cases OSFHome https://osf.io/a9jdq/
      4. Angulo FJ, Finelli L, Swerdlow DL. Estimation of US SARS-CoV-2 (2021) Infections, Symptomatic Infections, Hospitalizations and Deaths Using Seroprevalence Surveys (2021) JAMA Netw Open https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2774584 
      5. The Swedish Public Health Agency (2020) Estimation of the Lethality for COVID-19 in Stockholm County Online translation of [2] https://translate.google.com/translate?hl=en&sl=sv&tl=en&u=https%3A%2F%2Fwww.folkhalsomyndigheten.se%2Fcontentassets%2Fda0321b738ee4f0686d758e069e18caa%2Fskattning-letalitet-COVID-19-stockholms-lan.pdf 


       

      Comments

      Revised: The Importance of a Correct Infection Pool Estimation when Making a Comparison Between COVID-19 Injury Rates and COVID-19 Vaccine Injury Rates

      Anette Stahel, MSc

       

      Summary

      On July 31, 2021 the above article, Cerebral Venous Thrombosis and Portal Vein Thrombosis: A Retrospective Cohort Study of 537,913 COVID-19 Cases, was published in EClinicalMedicine. Unfortunately, the study includes two method errors which make the comparisons between COVID-19 vaccine injury rates and COVID-19 injury rates in it incorrect. More specifically, the vaccine injury rates among vaccinees are compared to disease injury rates among confirmed infected people when instead they should be compared to disease injury rates among the total pool of unvaccinated people. I'll here explain how come using a highly adequate infection pool estimation when conducting such a comparative study is of utmost importance. I'll also carry out a more correct calculation of this infection pool, based on official infection rate figures.

       

      Introduction and Review

      On July 31, 2021 the above article, Cerebral Venous Thrombosis and Portal Vein Thrombosis: A Retrospective Cohort Study of 537,913 COVID-19 Cases, authored by Taquet et al from Oxford University, was published in EClinicalMedicine [2]. The title of the article describes its content very well, although in addition to investigating the occurence of cerebral venous thrombosis, CVT, and portal vein thrombosis, PVT, following COVID-19 diagnosis it also investigates the occurence of these conditions following influenza diagnosis and following administration of an mRNA vaccine (BNT162b2 or mRNA-1273) against COVID-19.

      I've now gone through and reviewed this article and I'm sorry, but this study is not correct. That is, to begin with, the pool of people used as denominator when calculating the percentage of COVID-19 infected people who developed CVT and PVT is greatly inadequate. I'll explain what I mean.

      On page 2 of the study, it's stated:

      "COVID-19 increases the risk of CVT and PVT compared to patients diagnosed with influenza, and to people who have received a COVID-19 mRNA vaccine."

      However, when comparing the risk of developing medical condition X from infectious disease Y with the risk of developing condition X from something else, e g vaccine Z, you first and foremost need to make a correct assessment of how how large the pool of people infected with Y is. And to do that, you need to make an estimate. Merely counting the number of people who've sought out primary or secondary care for their symptoms won't do. Not even if you include all the people who were asymptomatic but sought out the care center anyway in order to take a test to see if they were infected (simply because they wanted to know) and then tested positive.

      No, you need to include all infected persons in the total pool of people belonging to the health care facility/facilities in question, including the ones who don't go test themselves because of being asymptomatic, or of not having the energy to do it due to their symptoms, or of being into alternative medicine, or of lacking interest/knowledge about the infection et c. There may be many different reasons. This means you need to make an estimate, otherwise the denominator in the calculation of the percentage who develops condition X from infection Y becomes incorrect.

      A study measuring the risk of developing condition X from infection Y using a smaller denominator than one including everyone infected may be useful at times, but it can not be used for comparison with a correctly calculated vaccine risk.

      I’ll use the study Estimation of the Lethality for COVID-19 in Stockholm County published by the Swedish Public Health Agency [3] as an example of a correctly calculated risk, based on an adequately defined denominator. The fact that this is a calculation of the lethality percentage from COVID-19 and not the CVT and PVT percentage is irrelevant, the point is that the same mathematics used in this study should've been applied in the present Oxford study. From page 13 in the Swedish study, in translation:

      "Recruitment was based on a stratified random sample of the population 0-85 years. In the survey we use, the survey for Stockholm County was supplemented with a self-sampling kit to measure ongoing SARS-CoV-2-infection by PCR test. The sampling took place from March 26 until April 2 and 18 of a total of 707 samples were positive. The proportion of the population in Stockholm County which would test positive was thus estimated at 2.5%, with 95% confidence range 1.4-4.2%."

      For a complex reason, which I won't go into but is described in the study text, one sometimes needs to use a slightly higher percentage when multiplying it with the total number of people in the pool, but that's of minor importance. Anyway, in this study they had to use the figure 3,1169% and when they multiplied it with the number of people in Stockholm County, 2 377 000, they got 74 089. This estimate was then the correct denominator to use when calculating the percentage of people who died from COVID-19 in Stockholm County during this time period.

      The numerator was the number of people who died in Stockholm County with a strong suspicion of COVID-19 as a cause, which was 432, no incorrectness there either - as long as a suspected cause number, not a diagnosed cause number, is also used as the numerator when calculating the lethality from the COVID-19 vaccine when the infection lethality and vaccine lethality rates are compared.

      So, what they found was that the lethality from COVID-19 in Stockholm County was 0,58%. This was a correct figure, as long as we keep in mind the fact that some of the suspected COVID-19 deaths may later have become diagnosed as unrelated to the infection.

      The above is thus how the authors of the present study should've carried out the first part of their calculation but they didn't. From their text:

      "Using a retrospective cohort study based on electronic health records primarily in the USA, the absolute risks of CVT and portal vein thrombosis (PVT) in the two weeks following a diagnosis of COVID-19 (made between January 20, 2020 and March 25, 2021) were calculated. (--) A total of 537,913 patients with a COVID-19 diagnosis were included."

      This excluded a considerable amount of infected persons in the total pool of 81 million people belonging to all of these primary and secondary care centers, who didn't go test themselves because of a number of reasons (being asymptomatic, being alternative medical, not having the energy or interest for it, et c). In short, the pool of participants should've been added with a vast amount of both symptomatic and asymptomatic SARS-CoV-2 positive people who didn't develop these medic care necessitating conditions.

      If they'd used an adequate figure in the denominator, the percentage of people established to've developed CVT and PVT from COVID-19 would've gotten vastly lower. However, the percentage of people determined to've developed CVT and PVT from the COVID-19 vaccine was fully correctly carried out since there are no unregistered vaccinated cases and therefore the registered figure is to be used. Towards the end of the text the possibility is mentioned of a number of people having received their vaccination elsewhere and therefore not being included in the vaccinee pool, but that figure is likely to’ve been very low.

      Via the determined COVID-19 CVT and PVT risks in the study along with the online verson’s Figure 2 [4], I calculated the following figures: First time CVT cases diagnosed after administration of the COVID vaccine amounted to 6.6 per million and first time PVT cases diagnosed after vaccination amounted to 10.7 per million. As for the infection derived forms of the diseases, the study’s figures were 35.3 per million for first time CVT and 175.0 per million for first time PVT.

      Now, the study looked at the time period from January 20, 2020 to to March 25, 2021, and what we need for a first step in determining the correct denominator is to estimate how many people in the US were infected at least once during these 14 months in question. For the calculation to be really accurate, we need the total, accumulated estimated number of infected people.

      And this figure is found by means of the statistical online resource Our World in Data, via the page presenting daily new estimated COVID-19 infections in the United States [5]. If we download the file and look at the figures, we find that the total number of estimated infections in the country during these 14 months amounted to 83 098 301. Prevalence studies of the latter part of this period indicate that the adequate estimate to use here is the upper one [6].

      If we then look at the data for confirmed infections in the country during this period, we see that they amounted to 29 562 445. This means that the estimated number of infections was 2.8 times higher than the number of confirmed. And this, in turn, means that we have to multiply the incorrect denominator of 537 913 used in the study by 2.8 to get the correct denominator, which should've been used instead. That multiplication gives us the figure of 1 506 156 estimated COVID-19 infections.

      Further, the study says that first time CVT was found in 19 of the patients following COVID-19 diagnosis and first time PVT in 94. This means that in reality, the rates of CVT and PVT elicited by COVID-19 were much lower than the present study claims. Infection elicited CVT cases, correctly calculated, amounted to 12.6 per million and the PVT cases amounted to 62.4 per million; far from the study’s 35.3 per million and 175.0 per million for CVT and PVT, respectively.

      Now to the second part of the risk calculation, a part which the authors of the present study didn’t miscalculate but simply left out.

      Let me first clarify what this study by Taquet et al makes a comparison of. It makes a comparison between the CVT and PVT risks among [confirmed] COVID-19 infected people and the CVT and PVT risks among COVID-19 vaccinated people. However, when referring to this paper within the context of making a risk/benefit assessment regarding decisions about administration of the COVID-19 vaccine, these risk figures among infected people cannot be used in their "raw" form, not even if you correct the numbers from confirmed cases to total cases as I did above.

      The reason why these "raw" figures cannot be used is that the alternative to taking a vaccine is to not take the vaccine, the alternative isn't to get the infection. When you take a vaccine, there's a 100% risk of getting the "infection" (in this case with viral RNA), while in the case of not taking the vaccine, it doesn't imply a 100% risk of getting the infection (with the virus) but a risk which is much lower.

      And as we’ve seen, in the US during the analysis period in question, the accumulated number of estimated COVID-19 infections in the end of the study period was 83 098 301. According to same source, Our World in Data, the accumulated number of estimated infections in the beginning of the period was 510. Based on the size of the country’s population in 2021 [7] and in accordance with the laws of mathematics, this means that the infection risk was 0.00015% in the beginning of the study period and 25% towards the end of it. Thus, the average infection risk during this period was 12,5%.

      This means that we have to multiply the recalculated infection derived CVT and PVT risk figures in the study by 0.125 to get the correct risks for people of acquiring COVID-19 derived forms of these conditions if they stayed unvaccinated. We thus get a risk of 1.6 per million for CVT and a risk of 7.8 per million for PVT. And this means, that taking the COVID-19 vaccine during this time period entailed a 4.1 times (310%) higher risk of developing CVT and a 1.4 times (40%) higher risk of developing PVT than if you abstained from taking it.

       

      Conclusion

      In the Introduction of the Taquet et al study, it's stated:

      "Here, using an electronic health records network primarily based in the USA, we estimated the incidence of CVT and PVT occurring in confirmed COVID-19 cases (both hospitalized and non-hospitalized) and compared this incidence to two other groups: people who received a COVID-19 mRNA vaccine (i.e. the BNT162b2 or mRNA-1273 vaccine), and a cohort of patients with influenza."

      And the final passage of the Discussion states:

      "In summary, COVID-19 is associated with a markedly increased incidence of CVT compared to patients with influenza, people who have received BNT162b2 or mRNA-1273 vaccines and compared to the best estimates of the general population incidence."

      Well, I've now shown that when making a truly correct comparison, i e not between vaccinees and [confirmed] infected but between vaccinees and unvaccinated individuals, we can see that taking the vaccine actually entailed a much greater risk for aquiring virus/mRNA derived forms of these conditions vs if you abstained from taking it. Both of the above quotes from the present study imply that it's methodically correct to compare vaccinees to infected individuals in a risk/benefit context. But it's not, in fact it's hugely incorrect.

      At the very least the authors should've included a longer passage in which they carefully explained the importance of comparing vaccinees to unvaccinated individuals in such contexts, instead of using the "raw" form from their study, but they didn't. Unfortunately, this has led to references to this paper by both laymen and medical professionals over the world in texts contending that the benefits of COVID-19 vaccinating the population outweigh the risks connected to it. Because apparently it's not obvious to everyone that this recalculation including infection rate figures needs to be done.

      In this particular case, there's a reason why the method inadequacies discussed above have especially serious consequences. That is, the Centers for Disease Control and Prevention (CDC), the major public health organization in the US and an organization with profound influence on public health officials worldwide, refers to this study and its figures in their documents as a source to support their view that the benefits of COVID-19 vaccinating the population outweigh the risks [8, 9]. Of course, had the present study been correctly performed, it would've pointed the CDC in the direction of determining the opposite; that in regard to CVT and PVT, the risks of vaccinating are far greater than abstaining.

      Interestingly though, with their work including these method errors, these authors have actually provided scientific validation of the growing suspicion that the COVID-19 vaccinated state gives rise to thrombocytic complications to a greater extent than does the unvaccinated (which is the opposite of the message of the paper), because even if the 537 913 figure is inadequate, the other figures in the study are most likely not.

      Finally, I'd like to recommend a reading through of the Swedish COVID-19 lethality study that I took up in the beginning of my text as a correct, comparative example [3]. The PDF is easily translated into any language via Google Translate. This is the main paper that the Swedish equivalent to the CDC, the Public Health Agency (Folkhälsomyndigheten), refers to when talking about COVID-19 lethality here and it's put up on one of the major information pages of their website. I really recommend reading all of it, because it explains so well and in such detail how come this model of denominator calculation without exception must be used in studies like these, which aim to investigate the rate of injuries/complications arising from an infectious illness.

       

      References

      1. Stahel, A (2021) The Importance of a Correct Infection Pool Estimation when Making a Comparison Between COVID-19 Injury Rates and COVID-19 Vaccine Injury Rates: Peer Review of Cerebral Venous Thrombosis and Portal Vein Thrombosis: A Retrospective Cohort Study of 537,913 COVID-19 Cases ScienceOpen DOI: 10.14293/S2199-1006.1.SOR-UNCAT.A8324974.v1.RUJZBA https://www.scienceopen.com/document/review?review=44831b83-8336-4642-9d1d-bfef514960ec&vid=02c7c05a-485d-4666-9c5c-e1dcc93fabc4

      2. Taquet, M, Husain, M, Geddes, J R, Luciano, S & Harrison, P J (2021) Cerebral Venous Thrombosis and Portal Vein Thrombosis: A Retrospective Cohort Study of 537,913 COVID-19 Cases EClinicalMedicine https://www.thelancet.com/action/showPdf?pii=S2589-5370%2821%2900341-2

      3. Svenska Folkhälsomyndigheten (2020) Skattning av Letaliteten för Covid-19 i Stockholms Län https://www.folkhalsomyndigheten.se/contentassets/da0321b738ee4f0686d758e069e18caa/skattning-letalitet-COVID-19-stockholms-lan.pdf

      4. Taquet, M, Husain, M, Geddes, J R, Luciano, S & Harrison, P J (2021) Cerebral Venous Thrombosis and Portal Vein Thrombosis: A Retrospective Cohort Study of 537,913 COVID-19 Cases EClinicalMedicine https://www.thelancet.com/journals/eclinm/article/PIIS2589-5370(21)00341-2/fulltext

      5. Our World in Data, Global Change Data Lab (2021) Daily New Estimated COVID-19 Infections from the IHME Model, United States https://ourworldindata.org/grapher/daily-new-estimated-covid-19-infections-ihme-model?country=~USA

      6. Wiegand, R E, Deng, Y, Deng, X, Lee, A, Meyer, W A 3rd, Letovsky, S, Charles, M D, Gundlapalli, A V, MacNeil, A, Hall, A J, Thornburg, N J, Jones, J, Iachan, R & Clarke, K E N (2023) Estimated SARS-CoV-2 Antibody Seroprevalence Trends and Relationship to Reported Case Prevalence from a Repeated, Cross-sectional Study in the 50 States and the District of Columbia, United States - October 25, 2020 - February 26, 2022 Lancet Reg Health Am 18: 100403 https://www.sciencedirect.com/science/article/pii/S2667193X22002204?via%3Dihub

      7. Trading Economics (2023) United States Population (2021) https://tradingeconomics.com/united-states/population

      8. Centers for Disease Control and Prevention, Advisory Committee for Immunization Practices [ACIP Workgroup Presentation] ACIP Meeting, Atlanta, GA, United States (2021, April 23) Risk/Benefit Assessment of Thrombotic Thrombocytopenic Events after Janssen COVID-19 Vaccines https://www.cdc.gov/vaccines/acip/meetings/downloads/slides-2021-04-23/06-COVID-Oliver-508.pdf

      9. Centers for Disease Control and Prevention (2021) CDC Library: COVID-19 Science Update May 21 https://www.cdc.gov/library/covid19/pdf/public_pdfs/05-21-2021-Science-Update-Final-public.pdf

      2023-04-13 19:36 UTC
      +1

       

      Addendum

      After making some further investigations and considerations, I've decided that an Addendum to my above review [1] is required. 

      Let me first clarify what this study by Taquet et al makes a comparison of. It makes a comparison between the CVT and PVT risks among [confirmed] COVID-19 infected people and the CVT and PVT risks among COVID-19 mRNA vaccinated people. However, when referring to this paper within the context of making a risk/benefit calculation regarding decisions about administration of the COVID-19 vaccine, these risk figures among infected people cannot be used in their "raw" form, not even if you correct the numbers from confirmed cases to total cases as I did in my review. 

      And the reason why these "raw" figures cannot be used is that the alternative to taking a vaccine is to not take the vaccine, the alternative isn't to get the infection. When you take a vaccine, there's a 100% risk of getting the "infection" (in this case with viral RNA), while in the case of not taking the vaccine, it doesn't imply a 100% risk of getting the infection (with the virus) but a risk which is much lower.

      And as we have seen, in the US during the analysis period in question, the infection rate was around 14.3% [2]. This means that you have to multiply the recalculated infection derived CVT and PVT risk figures in the study by 0.143 to get the correct risks for people of acquiring COVID-19 derived forms of these conditions if they stay unvaccinated. We thus get a risk of <0.2 per million for CVT and a risk of <1.2 per million for PVT. This means, that taking the COVID-19 vaccine entails a >33 times higher risk of developing CVT and a >10 times higher risk of developing PVT than if you abstain from the vaccine.

      In the Introduction of the Taquet et al study, it's stated:

      "Here, using an electronic health records network primarily based in the USA, we estimated the incidence of CVT and PVT occurring in confirmed COVID-19 cases (both hospitalized and non-hospitalized) and compared this incidence to two other groups: people who received a COVID-19 mRNA vaccine (i.e. the BNT162b2 or mRNA-1273 vaccine), and a cohort of patients with influenza."

      And the final passage of the Discussion states:

      "In summary, COVID-19 is associated with a markedly increased incidence of CVT compared to patients with influenza, people who have received BNT162b2 or mRNA-1273 vaccines and compared to the best estimates of the general population incidence."

      Now, the latter statement here is incorrect, because, as I showed in my review, when the pool of infected people is adequately calculated using an estimation of both confirmed and unconfirmed cases instead of merely using confirmed cases, the figures establish that the vaccine elicits more CVT and PVT cases than does the COVID-19 infected state. And in addition, I've now shown that if we make a truly correct comparison, i e between vaccinees and unvaccinated individuals, we can see that taking the vaccine entails an even greater risk than that for aquiring virus/mRNA derived forms of these conditions vs if you abstain from taking it. Which leads me to the former quote above, because both that and the latter one imply that it's methodically correct to compare vaccinees to infected in a risk/benefit context. But it's not, in fact it's hugely incorrect.

      At the very least the authors should've included a longer passage in which they carefully explained the importance of comparing vaccinees to unvaccinated individuals in such contexts, instead of using the "raw" form from their study, but they didn't. Unfortunately, this has led to references to this paper by both laymen and medical professionals over the world in texts contending that the benefits of COVID-19 vaccinating the population surpass the risks. Because apparently it's not obvious to everyone that this recalculation including infection rate figures needs to be done. 

      In this particular case, there's a reason why the method inadequacies discussed above have especially serious consequences. That is, the Centers for Disease Control and Prevention (CDC), the major public health organization in the US and an organization with profound influence on public health officials worldwide, refers to this study and its figures in their documents as a source to support their view that the benefits of COVID-19 vaccinating the population outweigh the risks of not vaccinating [3, 4]. Of course, had the present study been correctly performed, it would've pointed the CDC in the direction of determining the opposite; that in regard to CVT and PVT, the risks of vaccinating are far greater than abstaining. 

       

      References

      1. Stahel, A (2021) The Importance of a Correct Infection Pool Estimation when Making a Comparison Between COVID-19 Injury Rates and COVID-19 Vaccine Injury Rates: Peer Review of Cerebral Venous Thrombosis and Portal Vein Thrombosis: A Retrospective Cohort Study of 537,913 COVID-19 Cases ScienceOpen DOI: 10.14293/S2199-1006.1.SOR-UNCAT.A8324974.v1.RUJZBA https://www.scienceopen.com/document/review?review=44831b83-8336-4642-9d1d-bfef514960ec&vid=02c7c05a-485d-4666-9c5c-e1dcc93fabc4

      2. Angulo, F J, Finelli, L & Swerdlow, D L (2021) Estimation of US SARS-CoV-2 Infections, Symptomatic Infections, Hospitalizations and Deaths Using Seroprevalence Surveys (2021) JAMA Netw Open 4(1): e2033706 https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2774584  

      3. Centers for Disease Control and Prevention, Advisory Committee for Immunization Practices [ACIP Workgroup Presentation] ACIP Meeting, Atlanta, GA, United States  (2021, April 23) Risk/Benefit Assessment of Thrombotic Thrombocytopenic Events after Janssen COVID-19 Vaccines https://www.cdc.gov/vaccines/acip/meetings/downloads/slides-2021-04-23/06-COVID-Oliver-508.pdf

      4. Centers for Disease Control and Prevention (2021) CDC Library: COVID-19 Science Update May 21 https://www.cdc.gov/library/covid19/pdf/public_pdfs/05-21-2021-Science-Update-Final-public.pdf 

      2021-11-26 21:23 UTC
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