Preprint A Bayesian Survival Analysis on Long COVID and non Long COVID patients: A Cohort Study …, 2024, Jiang+

A Bayesian Survival Analysis on Long COVID and non Long COVID patients: A Cohort Study Using National COVID Cohort Collaborative N3C Data
Sihang Jiang; Johanna Loomba; Andrea Zhou; Suchetha Sharma; Saurav Sengupta; Jiebei Liu; Donald Brown; N3C consortium

Since the outbreak of COVID-19 pandemic in 2020, numerous researches and studies have focused on the long-term effects of COVID infection. The Centers for Disease Control (CDC) implemented an additional code into the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) for reporting 'Post COVID-19 condition, unspecified (U09.9)' effective on October 1st 2021, representing that Long COVID is a real illness with potential chronic conditions.

The National COVID Cohort Collaborative (N3C) provides researchers with abundant electronic health records (EHR) data by aggregating and harmonizing EHR data across different clinical organizations in the United States, making it convenient to build up a survival analysis on Long COVID patients and non Long COVID patients among large amounts of COVID positive patients.


Link | PDF (Preprint: MedRxiv)

 

74,000 / 7.4m is 1%.

 

The only thing worse than garbage data is corrupted data. And it's the people entering the data that corrupt it. On purpose. Not with a purpose to corrupt the data, their purpose just happens to completely corrupt it, as a choice. It's every bit as bad and corrupt as election poll workers fixing ballots, but without any verification mechanism and no recourse.

All official data on chronic illness is corrupted. All of it. None of it can be relied on, it's basically fiction. But it can't be fixed because the first step to solving a problem is acknowledging it, and medicine is incapable of that, prefers to sacrifice millions of lives than admit they got anything wrong. They don't even realize they're doing that, and simply deny and corrupt any data about it.

It's been 4.5 years and we can't even get reliable data. You can't do science without reliable data. The magnitude of this failure is so extreme it basically can't be discussed rationally, because there cannot be acknowledgement without major consequences, and, well, they don't want that, don't even understand that there's a problem at all and will refuse any step towards fixing it.

So what do you do when the people who are technically responsible for solving a problem are themselves the problem?