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I’m not sure what you mean by “real covid” because the epi case definition is the epi case definition. Here’s a systematic review of many tests for accuracy [0

I’m not sure what you mean by “real covid” because the epi case definition is the epi case definition. Here’s a systematic review of many tests for accuracy [0] and they describe how different tests determine sensitivity and they aren’t based on the epi definition. They do stuff like chest X-rays and none of them, that I read, rely on symptoms or any circular case definition. Here’s the surveillance case definition that CDC puts out from back on April 5 [1] and it’s not meant to be “real covid” for healthcare purposes but used to try to estimate incidence. So I think of it as the most likely to be useful. The lab test accuracy is closest to “real covid” in that they try to measure whether the disease actually exists and corresponds to the test result. For novel diseases there’s no gold standard so different tests attempt different techniques. I don’t think all these different tests are all politically biased especially since many report pretty bad sensitivity (50%). [0] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7457918/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7457918/ [1] https://wwwn.cdc.gov/nndss/conditions/coronavirus-disease-2019-covid-19/case-definition/2020/ https://wwwn.cdc.gov/nndss/conditions/coronavirus-disease-20...

mike_hearn 6y ago
Thanks for the links. I read the meta-study you cite. It seems to actually reinforce my points rather than rebut them. It does it so clearly I'm not entirely sure how you concluded the opposite. It's a good study. They reviewed a lot of papers: 130! Despite that, the paper abstract clearly states it cannot be used to conclude anything because despite reviewing a lot of papers, ALL of them were missing critical study details. Literally despite selecting 816 articles post-dedupe and then whittling it down to 130 articles, and then whittling it down again to 49 for the final paper, none of them were usable because all of them had methodology problems! That's prima facie evidence that the medical establishment has absolutely no idea how to answer a most basic question: what actually is COVID and how accurate are the tests? We can see the problems I'm talking about by reading further. You mention chest CTs and imply that calibrating the test against them is a common technique, vs relying on circular definitions or symptoms. That doesn't seem to be true. In fact only a single study looked at chest CTs and it had the following problem: "Ai et al. compared the positive rate of rRT-PCR (59%) with the positive rate of Chest CT in order to draw conclusions about the accuracy of Chest CT for the diagnosis of COVID-19,7 ... In terms of quality assessment, the studies lack specific details as to how patients were classified as having suspected COVID-19 infection" In other words, the study is useless. They calculate a false negative rate (not an FP rate) yet don't say what definition of COVID they used as the gold standard. This sort of thing seems to be totally rampant in medicine, it's ridiculous. You said, "none of them, that I read, rely on symptoms or any other circular case definition". I don't understand that statement because the paper clearly says that virtually all of the studies did rely on circular definitions. For example: "Eight studies ... attempted to determine the accuracy of rRT-PCR by comparing the initial rRT-PCR result to the result after multiple repeated samples from the patient submitted for rRT-PCR testing, which was called the reference standard ... Suo et al. considered a positive result of either repeated measurements of rRT-PCR or serology to indicate a positive test according to the reference standard" That's a circular definition because the test is being calibrated against itself. The paper concludes: "Clinical diagnosis by the case definition for COVID-19 used in the early period of the pandemic does not correlate well with positive rates of COVID-19 rRT-PCR" In other words, COVID as initially detected (unusual pneumonia) is in fact a totally different disease to current COVID, which speaking very pedantically and technically does not actually exist at all: a disease defined as testing positive for the disease cannot be said to really exist in a meaningful, logically coherent sense.

mike_hearn 6y ago

Thanks for the links. I read the meta-study you cite. It seems to actually reinforce my points rather than rebut them. It does it so clearly I'm not entirely sure how you concluded the opposite. It's a good study. They reviewed a lot of papers: 130! Despite that, the paper abstract clearly states it cannot be used to conclude anything because despite reviewing a lot of papers, ALL of them were missing critical study details. Literally despite selecting 816 articles post-dedupe and then whittling it down to 130 articles, and then whittling it down again to 49 for the final paper, none of them were usable because all of them had methodology problems! That's prima facie evidence that the medical establishment has absolutely no idea how to answer a most basic question: what actually is COVID and how accurate are the tests? We can see the problems I'm talking about by reading further. You mention chest CTs and imply that calibrating the test against them is a common technique, vs relying on circular definitions or symptoms. That doesn't seem to be true. In fact only a single study looked at chest CTs and it had the following problem: "Ai et al. compared the positive rate of rRT-PCR (59%) with the positive rate of Chest CT in order to draw conclusions about the accuracy of Chest CT for the diagnosis of COVID-19,7 ... In terms of quality assessment, the studies lack specific details as to how patients were classified as having suspected COVID-19 infection" In other words, the study is useless. They calculate a false negative rate (not an FP rate) yet don't say what definition of COVID they used as the gold standard. This sort of thing seems to be totally rampant in medicine, it's ridiculous. You said, "none of them, that I read, rely on symptoms or any other circular case definition". I don't understand that statement because the paper clearly says that virtually all of the studies did rely on circular definitions. For example: "Eight studies ... attempted to determine the accuracy of rRT-PCR by comparing the initial rRT-PCR result to the result after multiple repeated samples from the patient submitted for rRT-PCR testing, which was called the reference standard ... Suo et al. considered a positive result of either repeated measurements of rRT-PCR or serology to indicate a positive test according to the reference standard" That's a circular definition because the test is being calibrated against itself. The paper concludes: "Clinical diagnosis by the case definition for COVID-19 used in the early period of the pandemic does not correlate well with positive rates of COVID-19 rRT-PCR" In other words, COVID as initially detected (unusual pneumonia) is in fact a totally different disease to current COVID, which speaking very pedantically and technically does not actually exist at all: a disease defined as testing positive for the disease cannot be said to really exist in a meaningful, logically coherent sense.