Update: Wow. I honestly am a bit surprised at this. In my inbox just now, I was asked to comment on the ‘new’ Astrazeneca finding related to VITT. There’s a new paper out in the NEJM called Adenoviral Inciting Antigen and Somatic Hypermutation in VITT.

It comes down to this:

They are claiming here that an autoimmune condition (molecular mimicry) arises as a result of the shots that involve adenoviral vectors - more precisely - it’s tied to the vector’s own core protein pVII. So it’s not just Astrazenenca implicated here, it’s Janssen as well. So this is very valid as a explanation for the TSS/VITT arising in some people, but on the other hand: why the hell was this allowed to happen in the first place? Didn’t the people who designed these products do any bioinformatics ahead of time to assess potential human homologs?

I mention at the end of this article that I would like to know what extra stuff See et al. had to narrow down the TSS/VITT cases to Janssen. I guess this works as a good explanation for that. But nonetheless, the mRNA shots are implicated as well. Perhaps by a different protein but given what I know about the spike protein and the molecular mimicraziness going on, I wouldn’t be surprised if there wasn’t a beautiful analogy lurking around.

Read this:

Read the paper entitled: “Case Series of Thrombosis With Thrombocytopenia Syndrome After COVID-19 Vaccination - United States, December 2020 to August 2021”.1 It was published in the Annals of Internal Medicine on January 18, 2022 by a group of MDs with the help of CDC staff (and the study was funded by CDC). It does not surprise me to see Tom Shimabukuro’s name in the list of authors, lemme tell ya. He was one of the authors in charge of data curation (collection and assembly).

The conclusion of this paper - which basically ultimately “steered the vibe” on Janssen as a COVID shot - was that Janssen was associated with Thrombosis with Thrombocytopenia Syndrome (TTS) according to VAERS data, and the Moderna and Pfizer were not.

Thrombosis with thrombocytopenia syndrome is a rare but serious adverse event associated with Ad26.COV2.S vaccination.

This is strange because they indeed combed VAERS for TTS reports associated with the mRNA injectable products as well, but lo-and-behold, they didn’t find many that satisfied their criteria for TTS associated with them. Interesting that.

N.B. TTS is different from Thrombotic Thrombocytopenic Purpura (TTP) (also called Moschcowitz syndrome), in that the latter is often ascribed to vaccine context. It’s actually also called Vaccine-Induced Immune Thrombotic Thrombocytopenia (VITT) when it’s considered to be vaccine-related.

The term TTS is used by the Brighton Collaboration, an organization that develops consensus definitions for adverse events after immunization, and by various governmental agencies (6–8). Many clinical experts use the term vaccine-induced immune thrombotic thrombocytopenia (VITT) to refer to this syndrome (8). See et al.

TTP is a classic thrombotic microangiopathy (TMA) driven by ADAMTS13 deficiency that induces microclots + hemolytic anemia + organ ischemia (brain/kidney prominent), whereas TTS (especially VITT) is an immune HIT-like syndrome that induces macroclots (often unusual sites) + thrombocytopenia, but without significant hemolytic anemia or schistocytes.

This is an important distinction because where TTP is rare and not really thought of as being vaccine-associated, TTS is extremely rare and is. Let me take you through what See et al. did.

What did they do?

The authors extracted U.S.-based VAERS reports of AEs following COVID shots ranging from December 14, 2020 through to August 31, 2021. Then they sought out potential TTS from this date-adjusted data set using a wide thrombo net. It is noteworthy for the data nerds out there that I used the VAX_DATE variable in order to create the date range from 14/12/2020 - 30/09/2021. It is also noteworthy that if one decided to use the ONSET_DATE, the total number of reports for this timeframe changes quite dramatically (fewer data points).

N.B. You can probably imagine how easy it would be make the data appear one way or another by simply choosing a particular variable when selecting timeframes. For example, if you want fewer reports, choose the ONSET_DATE variable for time frame selection! I am keeping the VAX_DATE data by virtue of the fact that there are more data points to analyze. It’s impossible to know exactly how See et al. did their counting/data cleaning, but for my part, I used the same methodology I always use: R → merging the 3 .csv files → removing duplicates → counting AEs based on MedDRA code query. I’ll get back to this.

See et al. used what I would call a convoluted methodology; presumably so that they could throw a wide thrombotic net into VAERS for subsequent bottlenecking in the quest for “true” TTS reports. Please see their Appendix for their methodology.2

In a nutshell, they counted VAERS reports received after receipt of the COVID-19 shots, presumably up to an including the end of the study (December 2021 - all people included had to have been injected by August 31, 2021). Then from this pool, they counted reports with either thrombosis in unusual locations or common cases with thrombocytopenia up to and including August 31, 2021. Then from this smaller pool, they used “case definition criteria” - which presumably means medical record information like labs and “explert” “adjudication” to eliminate a whopping 95% of these reports to yield the final count of TTS reports of 57.

Most of these 57 reports were in the context of Janssen (54 after Ad26.COV2.S (Janssen/Johnson & Johnson adenoviral vector vaccine); 3 after mRNA-based (Pfizer-BioNTech or Moderna)). 976 of these reports “did not meet case definition criteria”. I wonder what that actually means?

Figure 1: Figure 1 extracted from See et al.. https://www.acpjournals.org/doi/10.7326/M21-4502?url_ver=Z39.88-2003&rfr_id=ori:rid:crossref.org&rfr_dat=cr_pub%20%200pubmed#appendix

I don’t have access to medical records because I’m not an MD, so take that into consideration for this next part. But this is in itself is a point of contention because we have to trust them. And the problem is: I do not, anymore.

So the See et al. initial thrombo net was “very wide” and included reports that had unusual-site clots (even without low platelets mentioned) or common-site clots + low platelets. Fine. Let’s try to understand better the clinical review and case definition application. “Trained clinical abstractors” reviewed the reports, requested medical records when possible, and applied the formal TTS case definition criteria which was:

• Thrombocytopenia (new-onset, platelet count <150 × 10⁹/L (or <150,000 per microliter)) AND
• Thrombosis (at any site)
• Plus, for Tier 2 cases (common sites only), positive anti-PF4 ELISA or functional HIT assay

N.B. A positive anti-PF4 ELISA indicates the presence of antibodies against platelet factor 4 (often in complex with heparin), which is a key laboratory finding suggestive of heparin-induced thrombocytopenia (HIT) or related conditions like vaccine-induced immune thrombotic thrombocytopenia (VITT). By the way, in light of the new NEJM paper mentioned above in the update, I checked how many Platelet factor 4 MedDRA-coded AEs there were in the SYMPTOM_ field from VAERS from my own “reduced TTS list”, and there were 6 reports in total - 2 of them were in the context of Pfizer. The other 4 were for Janssen.

That seems restrictive, but fine. But, in addition to this, they discounted people who had COVID-19 concurrently reported with their thromboticality. I personally think this is a stupid thing to do for many reasons. Here are some:

1. The moment that injection is delivered into your body, any AE that presents itself subsequently COULD BE due to that injection. Period. It does not matter if someone had COVID-19 before or during because we’re talking about vaccine-induced TTS.
2. People weren’t screened for SARS-2 antibodies or “tested” for SARS-2 antigen prior to being injected, so we couldn’t know if they had a resolved infection, and in that case, why exclude these cases?
3. The shots predispose people to being more susceptible to COVID-19 anyway - this is well-documented - and indeed (to date) the #1 AE reported to VAERS in the context of the COVID-19 shots is: COVID-19. This means that you’re going to be getting rid of a lot of potential TTS reports for a bad reason. Besides the fact that a COVID-19 “diagnosis” was dependent on that bloody idiotic SARS-2 antigen test which, of course, picks up everything, especially when you leave the cycler running for 45 cycles. Duh.

I get it. They don’t want to include TTS that was brought on by SARS-2. But really? Everybody was exposed. A huge percentage of people got at least one COVID-19 shot, and NOW you don’t want to be inclusive? To exclude reports based on active COVID-19 infection documented at the time of TTS diagnosis seems pointless especially considering these folks probably had COVID-19 because they were on their 2nd or 3rd shot due to a tolerized immunological environment.

I would also like to point out that 5 concurrent COVID-19 cases that See et al. excluded seems: off, to me. That’s because COVID-19 is reported concurrent to a huge percentage of reports in VAERS in the COVID-19 shot context. Round and round it goes.

For argument’s sake, I did exclude the reports with concurrent COVID-19 AEs to see where my count would lie.

What did I do?

I used specific MedDRA codes from VAERS right off the bat. Why not cut to the chase? I didn’t cast a trawling net: I went fly fishing.

For my analysis of TTS reports in VAERS, I went straight for TTS and queried using the following MedDRA codes: TTS, Thrombosis with thrombocytopenia syndrome, Platelet count decreased, Low platelet (new-onset thrombocytopenia: platelet count <150 × 109 cells/L occurring any time after receipt of a COVID-19 shot), Vaccine induced immune thrombotic thrombocytopenia, and VITT.

You should also know that I checked the LAB_DATA for the individuals who had low platelet counts and I saw consistently low counts that qualify them for TTS → ie: < 150. You should also also know that I omitted any report where the HISTORY variable indicated previous TTS-like situation.

So I got 1,513 reports for potential TTS using the above-mentioned MedDRA codes. 1,299 reports remained after sifting out “COVID-19” as an AE from the SYMPTOM variable (a concatenated variable of all SYMPTOM_ variables). The See et al. COVID-19 report loss (“Had concurrent COVID-19”) was only 5 as I mentioned; my loss (214) seems far more realistic.

Moving on…

Let’s hit that “Did not meet case definition criteria” point where apparently, 976 reports were tossed by See et al..

Allow me to use the VAERS variables LAB_DATA, CUR_ILL (any current illnesses) and HISTORY (like if they had cancer) for my vetting. Cancer (especially active or metastatic disease) and many of its treatments create a hypercoagulable state + thrombocytopenia that can look very similar to TTS/VITT on initial presentation. I would agree that someone who had a history, or cancer (were on certain medications) or who had some kind alternate reason for having reported TTS might had their diagnosis conflated with vaccine-induced TTS.

Cancer/treatment keywords can be found in either LAB_DATA, HISTORY, SYMPTOM or OTHER_MEDS and add up to 152 (~12 %). So that leaves us with 1,147 reports of TTS. We’re almost down to their starting N!

So now with 1,147 reports of TTS - where no one has cancer or COVID-19 or prior TTS (all remaining reports are new or not artifactual), where do we go?

Where can we go from here? Well I think it would be prudent (and in-line with See et al.) to ensure that all the reports so far involve Thrombosis or Thrombocytopenia. So let’s grab those. Wow! Down to 224. Of the potential 1,147, only 224 have Thrombosis or Thrombocytopenia as MedDRA-coded AEs, so they are very likely TTS reports.

Let’s head to platelet counts in LAB_DATA. Wow, wow! This surprised me! Of the 224 remaining reports, reports with ANY platelet count mention in LAB_DATA was 163 (72.8%) and reports with platelet count <150 (or explicitly below 150) in LAB_DATA was 96 (42.9%). VAERS_ID 1036489 had this written in their LAB_DATA: 2/4/2021 - Platelets 156K on day of vaccine 2/8/2021 - Platelets at 56K four days later. So 4 days after her second Moderna shot, her platelets tanked. To be fair, this person had Immune Thrombocytopenia (ITP) listed in her history which indeed could have been vaccine-induced, so maybe she was subjected to this condition from a previous vaccine. Again, this was her second dose of Moderna. I am going to keep her in.

So we’re down to 96 reports of TTS, but that’s still a bit higher than 57. What can we do next?

Duplicate reports? Not sure that’s going to get rid of any since I remove duplicates at the start. But let me look through the remaining 96 reports where there’s no COVID-19, no cancer/cancer meds, and platelet counts are reported to be 150 × 109 cells/L. Nope. No dups.

I’m not sure what else I can cut out. We’re left with 96 reports. Hmm. I don’t know what else I can do with only VAERS data but you know what? I think I’ve done well to get rid of any non-TTS reports. So let’s look closer at this data with respect to age distribution and most importantly, how many reports are associated with each vaccine manufacturer. Let’s just see if this is a Janssen thing.

Amazingly, the distribution of reports of TTS with relevant age data after cleaning3 (94 reports have relevant age data) are not strictly for Janssen. In fact, Janssen has the least number of reports at 24 (green - top graph), with Moderna at 30 (orange - top graph) reports and Pfizer-BioNTech at 40 (blue - top graph).

Here are plots of the 94 reports left over after serious vetting.

This is quite stunning and contradicts the See et al. conclusion about Janssen. Besides there being almost twice as many reports of TTS according to my analysis, 74% were in association with Moderna and Pfizer. 74%! So what happened? Did Moderna and Pfizer get included in the “Did not meet case definition criteria” because they are mRNA-based? I am only half-joking. I honestly don’t understand how See et al. reduced the reports of TTS down to 57 with the majority being in the context of Janssen.

I have written before about how I think Janssen was thrown under the bus to usher in the age of the nucleoside modified RNA-LNP (gene-based) platform.

I still think I was right.

By the way, according to my analysis, 2 (8% 2/24) died in the context of Janssen products and 6 (8.6% - 6/70) died in the context of the mRNA shots.

The See et al. (2022) paper was one of the earliest and most influential U.S.-based case series studies using VAERS data to describe TTS (VITT). The paper concluded that TTS was a rare but serious AE associated with the adenoviral vector vaccine (Janssen), with a negligible signal for mRNA.

If they were wrong, this is highly problematic? And everybody looking at the data and everybody working on the ground as clinicians KNOWS that thrombotic AEs are exceedingly prevalent among the people who got the mRNA shots.

Without having access to full medical charts, imaging reports (confirming thrombosis via CT/MR venography), serial platelet counts, anti-PF4 ELISA results, functional HIT assays, or provider notes, any VAERS-based analysis (mine included) can only go so far. It captures TTS AEs in reported data but can’t definitively confirm or exclude true TTS/VITT cases.

Nonetheless, my reports were for TTS with platelet counts < 150 × 109 cells/L (this defines thrombocytopenia). Steve Kirsch had this happen to him following his shots. I believe he got Moderna.

For shits and giggles, I also used the See et al. protocol (as outlined in the Appendix) and my result was the following: N = 102 → not 57, but not far away, again. But the numbers aren’t the thing that bother me about this; it’s the distribution of [potential] TTS cases among COVID-19 shot manufacturers. It’s clear that the Moderna and Pfizer association with [potential] TTS is present, and that’s the point.

I did this 2 ways (and played with many variations along the way), and the result was always the same: Moderna and Pfizer and not exculpated.

I can’t imagine what they actually did to exculpate the nucleoside modified-mRNA-LNP injectable products from TTS (VITT). And again, I repeat, these analyses are always going to be subjective to some degree: it almost only depends on what your goals are going into data unless you go in completely unbiased and non-conflicted. That is a disturbing thing to admit, but it’s true.

I am unbiased and non-conflicted. That’s why I make my analyses very simple and transparent.

Here are the similar plots that demonstrate the See et al. methodology from the Appendix.

One last thing I would like to add here is that whilst doing these analyses, it is absolutely vital that analysts not be conflicted financially or otherwise, and that they go in to any dataset as unbiased as possible. It is also vital to have an eye and ear to the ground so as not to dismiss “reality” - no matter what the statistics say. Sometimes you don’t like what your data are telling you! It’s a fact of life. But you have to report it anyway.

I know those two statements might seem contradictory - but they stand well together. For example, I am not paid to do this, and although I have a sneaking suspicion that Janssen got thrown under the bus intentionally, I had no problem spending a lot of time to use the See et al. methodology to “see” (hardy har har) if their conclusions aligned with reality. They don’t. They don’t align with my own analysis, and they don’t align with clinical observations or other pharmacovigilance data. At all.

In light of the fact that everything I try to publish these days has a retraction mob a-fixed, I would like to suggest that much like the Surgisphere debacle, perhaps the See et al. paper could use a little investigation and/or retraction. By the way, I am not saying that Janssen is a good product. At all. I stand by my original claims that no one needed an injection of any kind in the context of SARS-2. The whole COVID-19 thing was a scam, in my opinion, and as time passes, and more documents are un-redacted and presented to the public, the public en masse will come to know this.

We were never conspiracy theorists. We were always common sense-driven, grounded and ethical scientists.

Please feel free to add some points of interest or suggestions on how I can adjust my vetting to suit the See et al. methodology better if you think I am missing something vital.

1

Isaac See, Allison Lale, Paige Marquez, et al. Case Series of Thrombosis With Thrombocytopenia Syndrome After COVID-19 Vaccination—United States, December 2020 to August 2021. Ann Intern Med.2022;175:513-522. [Epub 18 January 2022]. doi:10.7326/M21-4502

2

Potential reports of TTS were identified using combinations of searches among VAERS reports in which each search used a group of selected PTs or text strings.

Search 1 searched for the words “thrombocytopenia” or “low platelets” in the text of the symptom or laboratory test fields or for 1 or more of the following PTs: autoimmune heparin-induced thrombocytopenia, heparin-induced thrombocytopenia, immune thrombocytopenia, non-immune heparin associated thrombocytopenia, spontaneous heparin-induced thrombocytopenia syndrome, thrombocytopenia, or thrombocytopenic purpura.

Search 2 searched for 1 or more of the following PTs: acute myocardial infarction, basal ganglia stroke, brain stem stroke, hemorrhagic stroke, hemorrhagic transformation stroke, ischemic stroke, lacunar stroke, myocardial infarction, perinatal stroke, silent myocardial infarction, spinal stroke, thrombotic stroke, or vertebrobasilar stroke.

Search 3 searched for 1 or more of the following PTs: axillary vein thrombosis, deep vein thrombosis, or pulmonary embolism.

Search 4 searched for 1 or more of the following PTs: aortic embolus, aortic thrombosis, aseptic cavernous sinus thrombosis, brachiocephalic vein thrombosis, brain stem embolism, brain stem thrombosis, carotid arterial embolus, carotid artery thrombosis, cavernous sinus thrombosis, cerebral artery thrombosis, cerebral venous sinus thrombosis, cerebral venous thrombosis, femoral artery embolism, hepatic artery embolism, hepatic artery thrombosis, hepatic vein embolism, hepatic vein thrombosis, iliac artery embolism, jugular vein embolism, jugular vein thrombosis, mesenteric artery embolism, mesenteric artery thrombosis, mesenteric vein thrombosis, obstetrical pulmonary embolism, portal vein embolism, portal vein thrombosis, portosplenomesenteric venous thrombosis, pulmonary artery thrombosis, pulmonary thrombosis, pulmonary venous thrombosis, renal artery thrombosis, renal embolism, renal vein embolism, renal vein thrombosis, splenic artery thrombosis, splenic embolism, splenic thrombosis, splenic vein thrombosis, spontaneous heparin-induced thrombocytopenia syndrome, subclavian artery embolism, subclavian vein thrombosis, superior sagittal sinus thrombosis, thrombosis mesenteric vessel, transverse sinus thrombosis, truncus celiacus thrombosis, vena cava embolism, vena cava thrombosis, or visceral venous thrombosis.

Search 5 searched for 1 or more of the following PTs: autoimmune heparin-induced thrombocytopenia, heparin-induced thrombocytopenia, heparin-induced thrombocytopenia test positive, idiopathic thrombocytopenic purpura, immune thrombocytopenia, immune thrombocytopenic purpura, non-immune heparin associated thrombocytopenia, platelet count decreased, severe fever with thrombocytopenia syndrome, spontaneous heparin-induced thrombocytopenia syndrome, thrombocytopenia, thrombocytopenic purpura, or thrombotic thrombocytopenic purpura.

Search 6 searched for an extensive list of PTs describing various additional conditions or procedures that could indicate thrombosis (available on request).

Potential reports of TTS were identified as reports containing PTs and/or text for both search 1 and search 2, both search 1 and search 3, both search 1 and search 4, or both search 5 and search 6. Reports identified by these preliminary searches were then reviewed by trained clinical abstractors. Reports with COVID-19 vaccine receipt date through 31 August 2021 were included in this review. Some cases were first identified through CDC’s CISA Project (24) when health care providers requested clinical consultation about a patient and then subsequently a VAERS report was made.

3

I fill as many field entries that are missing from AGE_YRS using SYMPTOM_TEXT data.