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"Coding Logic Error" and fun with ICD-10 codes
From p-flagrant lies to p-coding logic error to p-ICD-10 code-buggery
Update: Thank you to ‘That Day’ for the comment! Watch this short clip from Ivor Cummins.
I feel like it might be time to clear up this whole thing about ‘COVID deaths’.
Now we all know about the ‘Coding Logic Error’ kerfuffle that happened in March. If you do not, you can read this. To summarize, the death counts reported (and repeated incessantly) in kids in America due to COVID-19 were not correct. Once the ‘Coding Logic Error’ was corrected, at least 1/4 of all of the reported deaths were found to be erroneous. In other words, those kids didn’t die from COVID-19. If this doesn’t shake you up, check yourself.
Please go to this Substack article.
Now read the paragraphs in the following screenshot until you really and truly understand their meaning. And then call your MP, your Senator, your judge, everyone and start screaming fraud.
You can go here to confirm this atrociousness. One thing that struck me in particular (because of my love of the RAAS), was the part on the ‘changes and comparability ratios following dual coding by MUSE 5.5 and MUSE 5.8 for selected leading causes of death’. Take a look at Table 3 in the document and refer to E86 to E87. -44% change?
That’s huge. This applies to leading cause of death being: ‘Disorders of fluid, electrolyte’. Funny that the Renin Angiotensin Aldosterone System regulates electrolyte levels and depends on ACE-2 to do so. Just saying.
The data analysed in this paper is based on the original software coding without revision. This means that, unlike our finalised death registrations, this data has not been subject to full quality checks and any further information on the death that is provided that may revise the cause of death has not been included.
So what this means is that many of the so-called COVID-19 deaths, were in fact, not.
The following Table (Table 1) shows the differences between the counts of deaths (underlying cause of death (UCOD)) according to the versions of the software (there’s IRIS 4.2.3, MUSE 5.5 and MUSE 5.8). The updated version (MUSE 5.8) resulted in dramatic differences in causes of death. Well, I would call 599 dramatic. This is the difference in leading cause between MUSE 5.5 and 5.8. Imagine all 599 of these were COVID-19 deaths removed as the leading cause of death. In other words, person died ‘with COVID’ and not ‘from COVID’.
I have not for one iota of a second considered analyzing data involving ‘deaths’ and ‘cases’ because the data is sheit. Here’s proof. There’s no polite way to say it. The COVID-19 pandemic/panorama/circus is a farse - a bad board game that everyone is sick of playing. The shots that came as a ‘solution’? My God. The humanity.
The overall proportion of records with an underlying cause of death coded to a different leading cause by MUSE 5.5 and MUSE 5.8 was 1.4%.
Now you might be thinking, 1.4% doesn’t sound that bad right? Well, maybe not as a standalone alteration. But one of the things that keeps repeating in the context of data when it has anything to do with COVID is INCONSISTENCY. This is an example with a clear explanation of how inconsistencies in death counts can come about, but this is just one example of what we know about. And not many people know about it! What don’t we know about with regard to inconsistencies in COVID data? And in this particular case, how would the correct classifications of causes of death change the public health narrative? Would a single kid have died from COVID-19 at all? Marty Makary would probably say no. Would we have this so-called emergency? Of course not. You’ve been gamed.
Don’t even get me started on bloody ‘cases’.
Please also refer to this Substack article written by John Dee.