In this study of a cohort of German patients recently recovered from COVID-19 infection, CMR revealed cardiac involvement in 78 patients (78%) and ongoing myocardial inflammation in 60 patients (60%), independent of preexisting conditions, this was a freak out statement if I have ever heard of one I mean Covid is doing something directly to the heart? and this thing it is doing to the heart is independent of preexisting conditions?? this study was viewed over 500K times and on 196 news outlets with 12,000 tweets this is in and of itself one of the main reasons that the BIG TEN shut down football. of course we will never know for sure but it has been cited in many of the articles as one of the biggest concerns for player safety and potential damage to the heart!! Nevermind the fact that this mean age in the study was almost 50 and the mean age of a college football player is around 20. That is just a small detail and we need to shut down sports for the safety of the athletes because we the big ten have a HEART and dont want to ruin theirs. BUT turns out that was not the only problem and twitter erupted with more errors- and you might say, wait twitter!? yep the authors even say-- We were made aware of the errors in our original report as they were discussed on Twitter through a journalist, who was covering the publication of the article. We immediately studied the Twitter discussion, which made note of 2 problems: the use of inaccurate metrics for the data analysis as well as inconsistencies between the reported data in the legend of Figure 1 and the data points provided for the patients with COVID-19 in Figure 2. As a result, we have reviewed the data and repeated the analysis. https://jamanetwork.com/journals/jamacardiology/fullarticle/2770026?fbclid=IwAR1ke0Afd5vLUhGMeGDggExbzvy8xy8j81OEMXnqg9aK5PNaq5RujkUnLqI part of the problem was the authors misuse of mean and median and standard deviation and (interquartile ranges) median is the middle number and mean is the average. the SD and the IQR The standard deviation takes into account all the values of a dataset, including any outliers. It is dependent on the mean, because the value is used to tell how much the data deviates from the mean of a dataset. the interquartile range (IQR), also called the midspread, middle 50%, --The Interquartile Range tells us how spread the data is. The larger this value is, the more spread out the data is, and the smaller the value, the less spread the data is. in the original paper The EF of the Covid 19 patients is shown as 56 (54-58) -- what weird is when the calculations were done on this 54-58 was not Not IQRs Not ± SD Not ± SE (standard error) Not ± 1.96 SD Not ± 1.96 SE Not ± 2 SD Not ± 2 SE but lets pretend it was an IQR- This means that half of the EF values lie between 54 and 58. So with a 100 people in the Covid arm that means that 50 people or 50% had an EF between 54-58. Obviously this is so insane its impossible or certainly so close to impossible it should make you says hold the phone another problem was blood pressures originally reported at median 129 with a range of (125-133)-- again was is the 125-133?? no way 50% of the people had a bp pressure in this rand so almost certainly not IQR and almost no way the standard deviation was only 8 blood pressure points. it was this mystery number range that still doesn't have a clear answer to it and has not been answered by the authors -- What about in age- the original paper had an age of 49 with IQR 45-53. that is 8 yr difference to account for 50% of the population. That is insane unless you are trying to account for a certain age. in the Original Investigation, “Outcomes of Cardiovascular Magnetic Resonance Imaging in Patients Recently Recovered From Coronavirus Disease 2019 (COVID-19),”1 published in JAMA Cardiology on July 27, 2020. We have recalculated all data according to dat(continued)