If you didn't catch the update at the bottom of the 2nd article I'd posted:
Update, Monday Oct 10, 2022
Dr. Joseph Ladapo, the Florida State Surgeon General who originally put out this analysis, has provided a
response to some of the criticisms of the analysis, including some I made here. Overall, his rebuttals do not satisfactorily address the points I raised, and my concerns about the analysis remain. Below are his tweets and a brief explanation why I find them unsatisfactory.
The argument here is quite vague. He seems to be arguing that because they used the same method across different subgroups and only some were significant (with young men being more so), that means the methodological concerns are minimal.
This is not a valid rebuttal. One does not decide if a method is valid based on whether or not it yielded statistically significant results. Varying levels of risk/statistical significance across subgroups is also not validation that the methods were sound — this can occur even when the data are random noise. Methods validate results, not the other way around.
It was clear that the methods section states that subjects were excluded if they had a documented COVID-19 infection. My concern arises from the limitations section, which states the exact opposite: “COVID testing status was unknown for those who did not die of/with COVID.” This blaring contradiction is not addressed.
If COVID testing was in fact used to exclude participants, details should be included regarding: 1. How they linked COVID testing data to death certificates, 2. How robust their COVID testing data are (would it be likely to capture the majority of people who actually tested positive?), and 3. how many subjects were excluded due to a positive test. This type of information would undoubtedly be asked for in peer review. As it stands, the current analysis does not provide sufficient evidence that they controlled for COVID infection as a confounder.
For 3a, the argument seems to be that the results from one subgroup analysis (men age > 60) are evidence of reproducibility of the result in the smaller subgroup (age 18-39). This is not correct.
If they wanted to show reproducibility, they would need to reproduce the result in the relevant age group. For example, a second cohort from a different state showing the same result in the same age group for the same vaccines would be a mark of reproducibility. Furthermore, the 40-59 age group does not show a significant association. As it stands, two subgroups show one result, and the third shows the opposite. Overall this is not particularly robust.
In short, the result in the age > 60 subgroup does not overcome the issues with small sample size in the age 18-39 subgroup.
Regarding 3b: for the analysis of men age 18-39 who received a mRNA vaccine, there were 20 events during the “risk” period (the window assessed for vaccine side effects) and 52 events during the control period. My original criticism remains – if even just a few of those 20 men had deaths that were misclassified and/or clearly unconnected to the vaccine, the statistically significant result will likely vanish.
Regarding 3c, self-controlled case series are not immune to the problems of low statistical power (small sample size). Statistical significance (which helps assess if “clustering” is likely due to “chance”) is essentially always influenced by sample size, inclusive of this method.
Different types of heart problems are not interchangeable. This rebuttal seems to be switching back and forth between myocarditis and “cardiac death” as if these are highly related outcomes, but in reality there are hundreds of different diseases that affect the heart, and a signal surrounding “cardiac death” would not necessarily imply anything about myocarditis specifically.
If the hypothesis is that myocarditis leads to an increase in cardiac deaths after vaccination, then deaths caused by myocarditis should be evaluated. This analysis was not performed; instead the two ICD 10 codes for myocarditis and two ICD 10 codes for pericarditis were lumped in with a bunch of other unrelated cardiac diagnoses and the results were analyzed in aggregate.
We have no idea if myocarditis was the cause of any of the deaths included in this analysis because the ICD 10 codes listed on the death certificates are not provided. The word “myocarditis” is not present anywhere in the analysis. As it stands, this analysis tells us absolutely nothing about myocarditis after vaccination.
