Great 🧵 on recent neuro-COVID paper making the rounds.
1. Nothing in the paper speaks to the veracity of CSF/grey matter volumes derived by T1/T2. (This is most definitely not like measuring the size of the aorta over time)
2. Whatever measure they do derive overlaps w controls a lot when looking at the box/scatter plot. While we use criteria with this type of poor discrimination not infrequently, we would seldom make a therapeutic decision with a diagnostic test with this much overlap with normal
3. These findings are derived based on defining regions of interest (ROI) in the brain. Anyone that’s done this in the heart to define EF, or in MUGA studies knows how fraught that is.. so would want a core lab, multiple interpreters b4 calling a real difference ..
4. These changes are not able to be discerned on individual patient pre/post MRIs by the naked eye.. differences rely on ‘objective quantification’ by an algo (thats based on some ROI that I assume they manually define)
5. These are all patients that happened to have had an MRI pre/during COVID .. that’s a pretty interesting group of patients youre selecting for.. “the thalamus of the patient who will later contract COVID appear to differ from controls years b4 infection 🤔
6. Really surprised to see this pumped heavily by respected folks like @ashishkjha@ScottGottliebMD .. seems incongruous to bang ivermectin because of level of evidence but then use this paper to argue for big policy decisions (like a hard prolonged lockdown until vaccine)
7. Btw : We Shld absolutely not censor jha/Gottlieb discussion about this paper or @BretWeinstein@PierreKory . discussion on iver.
This despite the fact my last review of ivermectin makes me think its hard to separate signal/noise with regard to effects. thehealthcareblog.com/blog/2021/03/0…
And it gets better. Two of the scatterplots are identical 😂
Ok. So my summary on the @Change_HC @Optum @UHC cyberattack debacle.
TL,DR : Govt. regulation creates billion dollar revenue streams for large corporations. Regulatory capture by large organizations means a healthcare system that is incredibly susceptible to single points of failure, and most of the players in the space have no clue/ don't really care!
🧵
Feb 21, 2024, cyberhackers compromise @Change_HC (formerly Emdeon, acquired a few years prior by @UHC for $13billion).
@Change_HC is the largest medical clearing house that takes electronic claims generated by hospitals and doctors offices , scrubs them, and puts them in a format that insurance companies accept. Insurance companies process claims, and make payments to hospitals and doctors.
The first reaction of @Change_HC is to disconnect from all of its clients, which means, no medical claims are processed to be delivered to insurance companies.
Change HC / United then proceeds to say absolutely nothing of substance for the next 2 weeks with regards to any timeline of coming back online
If the goal is truth, then the real bias everyone should lean into is against the academic-peer-review industrial complex that spends most of its time generating data that doesn’t replicate and then exacerbates the problem with hyperbolic conclusions
“If the only tool you have is a hammer, you tend to see every problem as a nail.”
Academia is full of people who have spent 20 years becoming masters of a particular domain that usually has no practical, real world application.
The coverage of this wildly speculative paper linking sars-cov2 is much worse than the actual paper is.
To give you a flavor.
The study is based on 8 autopsies of patients with a diagnosis of COVID.
Let’s take Patient 1.
🧵
59 year old black man with a history of CAD.
He was admitted to the hospital 3 times before dying.
Hospitalizations 1 was with a clot in his lungs. His only treatment was heparin and xarelto. This means he didn’t present with a COVID pneumonia.
Hospitalization 2 was listed for heart failure. His ejection fraction was 40-45%. He spent 5 days in the hospital. He was still COVID positive.
Hospitalization 3 was with an acute heart attack. A circumflex artery occlusion associated with rupture of a component of the mitral valve — the papillary muscle. He was now COVID negative. He died of the heart attack and resultant heart failure, I assume.
The authors of this study took coronary artery tissue and looked for evidence of sars-cov2
They show representative samples of tissue in their main figure. They do not , even in their supplement, show all tissue sampled and stained.
The presence of sars-cov2 rna In patients who were infected by itself doesn’t mean much, but researchers probed tissue for the antisense strand of the S gene (S antisense), which is only produced during viral replication.
One of the major issues of the last 3 years has been a seeming inability of US institutions to seek to answer basic questions like how extensive and how long a novel vaccine administered to humans lasts.
Well, these researchers tried to answer this question, and the results are really interesting!
Human bio-distribution studies are hard by nature.. it requires specimens of a variety of organs at various time point after administration of a therapeutic.
Preclinical animal studies of the mrna/LNP construct suggested a short duration (days)
The few human studies have suggested a much longer duration of action.
“Using human axillary lymph node biopsies, spike protein and vaccine mRNA were reported to persist up to 60 days from vaccination with either BNT162b2 or mRNA-1273 as detected by immunohistochem- istry and in-situ hybridization. In that study spike protein was also detected in the plasma up to 7 days from vaccination. BNT162b2 mRNA was detected in patients by PCR in circulating leukocytes up to 6 days from vaccination and in the plasma up to 15 days from vaccination. Using highly sensitive single-molecule array assays, spike protein derived from mRNA-1273 was detected in the plasma of patients up to 28 days from most recent vaccination20. Circulating exosomes containing spike protein derived from BNT162b2 were detected in patients 4 months after vaccination”
This study in Nature went one step further, comprehensively studying human tissue In patients dying after vaccination.
Importantly, NONE of the patients were deemed to have died from the vaccination.
Study from Basel, Switzerland that looks at myocardial injury as measured by routine measurements of cardiac biomarker (HsTn) after healthcare employees received a booster.
1. Excludes anyone who had myocarditis after dose 1 or dose 2 2. No baseline troponin checked prior to booster administration 3. 1871 Screened ---> 777 evaluated in trial 4. Average age 37, only 30% male
(Peak clinical myocarditis to date has been seen in 16-17 year old boys)
But still super useful to see how "cardioactive" booster is, grateful to researchers for taking a look.
20 women and 2 men had HsTn levels that were above the population reference ranges.
Most had repeat troponin levels done at 30 days (makes up a little for no baseline)