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“It took my breath away.” —Dr. Drew on the new study shows 50% of young men who got myocarditis after the vaccine now have permanent heart damage and he doesn’t understand why this isn’t front page news. And he recommends injured students sue any school that mandated it.

Now, a scientific study reveals that the government's revised claim is false as well — heart damage caused by the COVID mRNA injections is often permanent. Dr. Drew (Drew Pinsky) came on the Megyn Kelly show to describe the legacy media blackout of the study, which found that heart damage was permanent in fully half of the young men who suffered myocarditis from the injections.

Dr. Drew wants the news of this study to get out and to be used as the basis of tort suits against schools which mandated the shots:

“It took my breath away.” —Dr. Drew on the new study shows 50% of young men who got myocarditis after the vaccine now have permanent heart damage and he doesn’t understand why this isn’t front page news. And he recommends injured students sue any school that mandated it.

This 50% does not include those who died from heart attacks after the shot, for whom the side effect was as permanent as can be. Dr. Drew added that a lot remains unknown about the damage from the injections to the living:

In my world, throughout my entire career, 40-year career, myocarditis is a medical emergency . . . a publication just came out five days ago in circulation, a major cardiology journal, excellent study. . . .

We don't know what percentage are going to be disabled by this as they get older; are gonna develop heart failure, or are gonna need cardiac transplants, some of them. It's breathtaking this study. . .

In a 27-year-old male, the [COVID] illness is a nothing. So the vaccine is all risk [with no benefit]. Why the push? [Emphases added].

Kelly on board

Kelly fully agreed with Dr. Drew, telling her audience to avoid the shots even if it means having to fake a vaccination certificate.

If anyone tries to force you from this point forward, get a fake card . . . Don't comply.

If they're gonna create these bullsh-t rules, you can create your bullsh-t way around them.

It's all just like a theater. Ok, so let's act. I'll act like I've gotten my 50th booster and you can act like you're satisfied I'm telling you the truth. [Emphases added].

‘Excess mortality’ continuing surge causes concerns

Despite some signs that excess mortality rates are declining, life insurance executives and actuaries believe the numbers are alarming and could continue to drag earnings and surge death claims for years to come.
Excess mortality is the difference between the total number of deaths for a specific time period and the number that would have been expected. The numbers were naturally forecasted to climb during the pandemic, but some industry and health authorities are concerned the rates haven’t greatly diminished as COVID infection rates have declined.

Others aren’t so sanguine and point to statistics from the U.S. Center of Disease Control that show mortality rates alarmingly rising for different categories. For example, younger adult mortality rates are up more than 20% in 2023, the CDC said. Cause of death data show increased cardiac mortality in all ages. And even as COVID-related causes declined in 2022, others rose, particularly stroke, diabetes, kidney and liver diseases.

Anomalous Patterns of Mortality and Morbidity in Pfizer’s Covid-19 Vaccine Trial

Importantly, the data reveals a statistically significant connection between mortality rate and time since injection, for both the placebo arm and the mRNA arm. Very few deaths happen during the first 80 days, while unexpectedly many deaths occur around 100 days since injection, in a manner that could not arise by chance.

Cardiac SAEs in the trial also display highly unusual data patterns. Firstly, nearly half of all the cardiac events occur during the first 50 days since injection, whereas the risk exposure should be constant for the first 140 days. Secondly, there is a dramatic spike in cardiac events around 100 days from first injection in both the placebo and the vaccine arms – at the same time as the elevated rate of mortality.

The observed patterns cannot be the result of random occurrence. The only explanation compatible with all the non-random patterns is that the records of vaccine recipients suffering adverse events and death may have been changed, moving them to the placebo arm after the event.

Perhaps unsurprisingly given the previous observations, this is not what we see. Instead, the same pattern of fewer deaths during the first three months after injection is visible (Figure 4). At 80 days since first injection (placebo or mRNA), there is a deficit of deaths compared to what would be expected based on the total number of deaths in the period, with test statistics p = 0.01 for the vaccine arm and p = 0.11 for the placebo arm, based on binomial testing (see dotted lines in Figure 4 chart A and B).

Similarly, for the 28-day period in chart C, both arms show clearly significant deviation from expected rates, with far too many of the total deaths occurring in the period around 100 days after injection (p < 0.05 for vaccine and p < 0.002 for placebo after Bonferroni correction).

At this point we have established beyond any doubt that the mortality rate is constant neither in calendar time nor in time since injection. Some might interject that mortality patterns vary by season, but if this were the explanation here, the connection should be weaker in the time since injection-dimension than in calendar time. Instead, the opposite is the case. Furthermore, seasonal mortality variability is only prevalent among the elderly, whereas the deaths in the trial are mainly among the people younger than 70 years as we shall see later.

This means that there is a connection between mortality rate and temporal vicinity to injection, for both the placebo arm and the mRNA arm. What could explain this? It could be that people displaying signs of frailty were excluded from the trial during recruitment, thus introducing a kind of healthy user bias which would gradually fade with time, pushing forward deaths to later in the trial. The increase in mortality at around 100 days is not compatible with this explanation, however.

What other explanation might there be? This peak might be more consistent with negative effects from the vaccine causing deaths with a delayed effect. In that case, the initial death rate during the first 80 days might represent the background death rate, whereas the rate between 80 and 110 days since injection might be caused by the vaccine. But why is there also an increase in deaths in the placebo arm? For this explanation to be make sense, it would require the effect of the vaccine to also impact the placebo arm.

We consider that this might occur in two possible ways - either by the mRNA being given also to participants in the placebo arm or by moving the deceased participants from the vaccine arm into the placebo arm.

One could also imagine a third possibility, that record exclusion or deletion, as described here, may have created this non-random pattern. However, this explanation cannot account for why adverse events in the placebo arm are associated with time since injection. Thus, it could only partially explain the observations.

Other SAEs (Serious Adverse Events)
If there were negative effects from the vaccine during the trial, then one might reasonably expect there to also be non-lethal adverse events in greater abundance than the lethal ones. Cardiac events such as myocarditis have even been accepted as linked to the vaccine (albeit after many months of denial), so one might also reasonably expect there to be such events in the trial if there were real concerns about the vaccine causing elevated mortality.

The recent documents list Other SAEs in addition to the fatal ones, accompanied by diagnostic code abbreviations. For cardiac-related events the code CARD is used.

Figure 5 shows the temporal distribution of such events, measured in time since first injection. The data patterns are highly unusual. Firstly, nearly half of all the cardiac events occur during the first 50 days, whereas the risk exposure should be constant for the first 140 days (Figure 3). Secondly, there is a period of time around 90-100 days after first injection with clearly elevated rates of cardiac events. We therefore see an elevated rate of cardiac events during the same period of time since injection when we saw an elevated rate of mortality.

The accumulation of events in the first days after injection is significant among the vaccine arm and the peak around 100 days is significant in the placebo arm (Figure 5 chart C). The period here is 10 days as opposed to the previously used 28-day period, since the peak at 100 days is very concentrated. One might observe that changing the period like this introduces a new risk of false discovery, but in this case the number of observations is greater and thus even the KS-test shows clear deviation from the expected distribution, at p = 0.02 and p = 0.002 for the vaccine arm and placebo arms respectively. In other words, there can be no doubt that the cardiac events do not occur at a constant background rate.

We have established that there is a connection between mortality rate and temporal vicinity to injection, for both the placebo arm and the mRNA arm. We have also established that there are elevated Cardiac Adverse Events at the same time as elevated mortality rates. Furthermore, we have seen that prior health status is different between the two arms, and that age distribution among the deceased participants are significantly different between the placebo and the vaccine arm.

We see no innocuous way by which the described patterns could occur. Instead, these data may be evidence of at best tinkering with the randomization scheme or at worst data may have been manipulated to achieve FDA-approval of a harmful product.

There are two big takeaways from the graph. The first is that throughout the course of the trial, the number of deaths in both arms of the trial nearly match each other. This is not what one would expect in a trial where one group was purportedly receiving a life-saving intervention and the other wasn’t.

The second is that the total number of deaths is actually well below what should have happened in a group of 44,000 people over this period of time, especially during the height of a pandemic. Based on age-adjusted U.S. death rates, the authors calculate that there should have been over 200 deaths in this period under normal circumstances.

The most likely explanation for this discrepancy is the large number of participants that were “discontinued subjects.” This group comprises 1 in 25 of the total number of people enrolled in the trial. Among that group are those who were “lost to follow-up.” Approximately 100 in each group were “lost to follow-up” prior to Nov. 14, 2020, the cutoff date for data submitted by Pfizer to the FDA in support of their request for EUA.

There were only 11 deaths reported at that time. There should have been 6 times as many. With so few deaths reported, only a handful of deaths in either group of those who were “lost to follow-up” would have skewed a key metric in one way or another.

Undoubtedly, some of those who were lost to follow-up died. How hard did Pfizer’s investigators investigate? Nevertheless, FDA regulators did not take issue with the missing participants.

Pfizer delayed death reports prior to authorization

The clinical trial narrative reports from individual trial sites demonstrate another suspicious pattern: The actual dates of death as reported in the narrative reports by investigators at each trial site do not match those of what Pfizer inserted in corresponding case reports.

Pfizer used dates of death in the case reports to summarize the results of the ongoing trial to FDA regulators.

More importantly, the average delay in case reports was nearly 3 times higher among the vaccinated than the control group prior to authorization. But after EUA was granted, reporting delays dropped significantly in both groups.

The end result was that two cardiac-related deaths in the vaccinated group were omitted from consideration at the critical time of FDA EUA approval.

Furthermore, there was a 25-day period prior to authorization when Pfizer, though aware of more fatalities, chose to not update the death count in the trial.

Once again the FDA was not interested in the latest numbers. As a result, six extra deaths were excluded from consideration at the time EUA was granted.

Had the six deaths been included, a clearer picture of possible cardiotoxicity would have emerged: 75% of deaths in the vaccine group were due to cardiac events compared to 33% of deaths in the placebo group.

This was a clear safety signal that was hidden and would have prompted a more detailed inquiry, assuming that the FDA was interested in doing its job.

Authors’ conclusions

The authors summarize (emphasis is mine):

The C4591001 placebo-controlled randomized clinical trial of 22,030 vaccinated and 22,030 placebo subjects was the world’s only opportunity for an unbiased evaluation of the Pfizer/BioNTech BNT162b2 vaccine.

Unblinding of placebo subjects starting in Week 20 terminated the placebo-controlled clinical trial, thereby ending all unbiased evaluation of possible adverse event signals.

The mRNA-LNP platform is novel, not previously phase 2/3 tested in humans, and the toxicity of PP-Spike protein was unknown. Taken together, a 20-weeks placebo-controlled clinical trial is NOT sufficient to identify any except for the most common safety concerns.

The number of all-cause deaths is NOT decreased by BNT162b2 vaccination.

Of the 38 deaths reported in the 6-Month Interim Report of Adverse Events, 21 BNT162b2 vaccinated subjects died compared to 17 placebo subjects.

Delayed reporting of the subject deaths into the Case Report Form, which was in violation of the trial protocol, allowed the EUA to proceed unchallenged.

The number of subject deaths was 17% of the expected number, based on age-adjusted US mortality. One possible explanation could lie in the 395 subjects that were“Lost to Follow-up”.

There was a 3.7-fold increase in cardiac events in subjects who received the BNT162b2 vaccine versus the placebo.

Of the 15 subjects who were Sudden Adult Deaths (SAD) or Found Dead (FD), 12 died of a cardiac event, 9 of whom were vaccinated.

The cardiac adverse event signal was obscured by delays in reporting the accurate date of subject death that was known to Pfizer/BioNTech in the subject’s Narrative Report.

Conclusion

Three years later, the results of the Pfizer trial are still hard to explain. With hundreds of thousands of pages of original data and narrative reports to examine, more clues may emerge with time.

We can certainly say that the FDA and CDC advisory panels could not have adequately assessed this much information in the 25 days they had prior to their decision to authorize this product for hundreds of millions of people.

Furthermore, a court order shouldn’t be necessary to impel the FDA to let the public know what was known. What possible excuse would an agency of public health have for hiding data from the public?

The software that assigned subject ID numbers for the Pfizer/BioNTech clinical trial generates ID numbers sequentially, which are assigned to volunteers when they are screened for inclusion in the study. We found 301 “gaps” in the subject ID numbers (missing numbers where there should be one), and in more than a few cases multiple sequential ID numbers in a row are missing.

Below, we start our in-depth investigation of this anomaly by reviewing how the software supervising the trial was functioning when a new subject was enrolled (“Enrollment” was the step prior to screening, where the subject was registered by the trial site, after the screening appointment had been coordinated through Pfizer’s subcontractor, ICON1).

Then we highlight why understanding this trivial detail matters as far as establishing a most concerning issue: the data of numerous subjects enrolled in the trial appears to be missing and may have been deleted.

We went in depth in verifying if the error we highlight was technically feasible and whether it could have an innocent explanation.

Why is Augusto Roux’s story terribly important here?

Well, as can be seen in the middle screenshot above, 17 subjects “disappeared” on a single day, August 21, 2020. That is by far the largest number of missing subject IDs at any site on any day. It is also the same day Augusto Roux was screened.

Since almost all subjects at the Argentina site were administered their first dose on the same day they were screened (if they passed screening), any subjects administered the first dose on that day would have been scheduled to receive their second dose three weeks later, the same date that Augusto received his, which caused him significant harm — possibly due to a bad batch.

Augusto Roux survived and was not erased from the study. Were there others, less fortunate, who were completely erased from the trial records? Or erased to cover up some problem? It’s possible. And it would not be far fetched to think that something could have gone wrong that affected 17 subjects on the same day, even 9 in a row. There was another major anomaly that occurred at the Argentina site just two days later, on August 23rd: 52 subjects on that day were given larger doses due to a preparation error and were subsequently unblinded a week later on August 31st. In the protocol deviation dataset,8 the reason given is “Dosing/administration error, subject did not receive correct dose of vaccine.” In other records there are other reasons given, but they are all product-related. We know from the trial records that 31 of them did not get the second dose, and of the 23 who did, four of them had significant adverse events recorded in the follow-up period after the second dose. So we know that there was a problem at this site that caused 52 consecutive subjects to be unblinded, which is a major screw-up and very anomalous. We also know that Augusto Roux's side effects were strangely re-defined (that is, covered up)9. In light of all this, it's reasonably to be suspicious when we see this huge anomaly of so many missing subjects on the same day that Augusto received his first dose.

The full table of 48 392 subjects (48 091 subject ids who remained, and the 301 subjects “simply deleted”), can be accessed (sorted by site & subject ID) on the following Google Spreadsheet (along with their randomization dates & treatment arm, when available)10.

Note there could very well be more subjects who have “been disappeared” (if for example a site’s last subject is 1198 but 1199 and 1200 were deleted, we would have no way to know it at this stage).

How Could Subjects Be Erased?
We can think of 3 ways in which these subjects could have been erased:

Directly in the database supervising the trial

Someone with database credentials (server, port, login, password) could have gained access, with or without ICON’s consent. Having such access would have allowed modification of any data of the trial (tests results, subjects data modification or erasing, etc.) directly to the database.

Upon the snapshot exports

In a similar fashion but leaving the “raw source data unaltered,” the .XPT data file exports or “snapshots” could have been altered, in order to fit a “predetermined result.” This would be easier to detect with an audit of the “core database” than method 1, but no such audit has ever been performed to our knowledge.

Via a request from the trial site to study sponsor

Below is a screenshot of a (redacted) request to Pfizer to delete a subject ID number originating from a trial site, which was provided to us by Pfizer whistleblower Brook Jackson. This is from the booster study, C4591031. As far as we know this request was granted. The reason given is: “SSID status was updated to SF [Screen Failure] but there is no subject attached to this subject number.” It’s unclear how this could have come about. It’s also possible this was an excuse used to delete a subject with problematic data. We don’t know. We also don’t know if the SSID would have been re-used by being assigned to another subject. But this is an example of the kind of error that might be expected to produce a handful of isolated, evenly distributed deletions.

Via the management software

The Principal Investigator on site could have been delegated “elevated privileges” allowing him or her to delete symptoms, or entire sets of subject data. If such privileges had been granted by ICON to Pfizer employees or site PIs, the only places where we could find evidence of the modifications would be the database logs & the audit trail accessible via the managing software. This constitutes, in our opinion, the most likely hypothesis, especially in light of the large number of deletions in Argentina.

Trial Sites where Subjects Disappeared
Most of the skipped subject ID’s are peppered here & there individually, and only 10 trial sites have more than 4:

9 subjects at site 1005 with 442 total subjects, Rochester Clinical Research, Inc. (Rochester, New York, USA), led investigator Matthew Davis.

5 subjects at site 1039 with 334 total subjects, Arc Clinical Research at Wilson Parke (Austin, Texas, USA), led by Gretchen Crook

5 subjects at site 1090 with 561 total subjects, M3 Wake Research, Inc (Raleigh, North Carolina, USA), led by Lisa Cohen

6 subjects at site 1109 with 557 total subjects, DeLand Clinical Research Unit (DeLand, Florida, USA), led by Bruce Rankin

6 subjects at site 1142 with 390 total subjects, University of Texas Medical Branch (Galveston, Texas, USA), led by Richard Rupp

5 subjects at site 1146 with 395 total subjects, Amici Clinical Research (Rajitan, New York, USA)

8 subjects at site 1147 with 340 total subjects, Ochsner Clinic Foundation (New Orleans, Louisiana, USA), led by Julia Garcia-Diaz

5 subjects at site 1166 with 107 total subjects, Rapid Medical Research, Inc. (Cleveland, Ohio, USA), led by Mary Beth Manning

5 subjects at site 1170 with 496 total subjects, North Texas Infectious Deseases Consultants, P.A. (Dallas, Texas, USA), led by Mezgebe Berhe

111 subjects (100 subjects at site 1231 with 4585 total subjects & 11 at site 4444 with 1,311 total subjects), Hospital Militar Central (Caba, Argentina), led by Fernando Polack

Such anomalies should happen extremely rarely if at all. And, if the problem was due to error, we would expect a fairly even or distribution across sites. But here we see 55% of deletions at 10 sites where only about 20% of all trial subjects were enrolled. And as we saw earlier, 37% of all deleted subjects were at a single site (Argentina) that enrolled only 12% of the trial subjects. The likelihood of such disproportionate deletions happening by chance is extremely low, far less than 1 in a million.

Concerning my risk/benefit estimations, one little thing that was bugging me was that there were apparently no vaccine related deaths in any of the clinical trials. I had no evidence of misreported deaths, although that would not be surprising in view of the criminal track records of companies like Pfizer. And we already found that Pfizer covered up the case of a girl who ended up in a wheelchair with a feeding tube.

Another thing that remained in the back of my mind was a disagreement in the reported number of deaths in Pfizer's placebo group - according to the main text of their publication there were 4 deaths in the placebo group, but according to the supplementary data p.2607 there were 3 (note that there were zero Covid deaths in either group). It was puzzling to me how such a mistake could occur if they had not messed with the data.
Since then, an accusation was made that in Argentina a vaccine death was covered up, but I have no idea how well founded that was (here and here). I had no hard evidence of anything.

But recently, thanks to a FOIA Request as described here,
the FDA was obliged to release a huge pile of documents. Buried inside that pile there's a document called fa-interim-narrative-sensitive.pdf
In that document a death in the vaccination group is recorded that Pfizer failed to mention or even account for in its publication.

I made the following overview, reduced to what I deem data of interest.

Reported deaths in BNT162b2 Pfizer vaccine group
C4591001 1007 10071101 - heart attack after 2 months
C4591001 1162 11621327 - died 3 days after dose 1, probably due to arteriosclerosis
C4591001 1152 11521497 - died in hospital after fainting at home. RECORDED BY PFIZER AS SUBJECT WITHDRAWAL. UNKNOWN CAUSE OF DEATH. NO AUTOPSY. Wrongly omitted from the published report!
Reported deaths in Placebo group
C4591001 1066 10661350 USA
C4591001 1081 10811194 USA
C4591001 1152 11521085 USA
C4591001 1231 12313972 Argentina. History of hypertension. Hemorrhagic stroke 14 days after Dose 2. No autopsy.
Following Occam's razor, the simplest explanation that I can think of is that the reported Argentina placebo group death was in reality in the vaccine group, and there was a slip-up in the falsification. If so, not one but two deaths were mislabeled.

Now why would Pfizer cover up one or two deaths? It can't be because of the small and rather balanced true numbers. As a matter of fact, the reported numbers in the main text of their published article (4 deaths in placebo group but only 2 in vaccine group, despite zero due to Covid) caught my attention, it was almost suspicious.
The only reason I can think of is that the reporting of any death that was possibly vaccine related but not investigated, could have made approval more difficult or complicated, risking a restricted approval for only the elderly. Billions of dollars were at stake.

This is much worse than the Boeing 737Max scandal, which also involved a government agency. Among other things, the FDA either overlooked or closed their eyes to an unexplained death in the vaccine group of Pfizer's clinical trial. Note that they tried to stall release of the documents by decades, but were forced to deliver.

So, governments were either lying or simply talking BS when assuring the public that all Covid19 vaccines were safe and effective. Of course, we already knew that but now it's a hard fact - the possible unsafety of at least Pfizer's vaccine was already swept under the rug in the clinical trial.

UPDATED: Marine Commandant Gen. Eric Smith Hospitalized After Heart Attack

Marine Corps Commandant Gen. Eric Smith was hospitalized after suffering an apparent heart attack on Sunday evening, two defense officials confirmed to USNI News on Monday.

The Marine Corps did not provide additional details on the hospitalization. Lt. Gen. Karsten Heckl is now performing the duties of Marine commandant, according to a statement from the service.

Heckl is the deputy commandant for combat development and integration. He is the most senior officer within Headquarters, Marine Corps, the service noted in the release. There is currently not a Senate-confirmed assistant commandant in place.

As of Monday afternoon, there were no additional details on Smith’s condition.

The Hot Zone: Cardiac Arrest

Understanding the catastrophe that is killing the young and fit.

Recent unexpected deaths of young athletes and a young, gifted church pastor in Texas prompted me to interview Dr. McCullough about the precise causes and mechanics of cardiac arrest. What exactly do we mean by “cardiac arrest,” how can (and should) these events be investigated, and what measures can be taken to prevent them from happening?

No one has done more investigative scholarship about this catastrophe than Dr. Peter McCullough. Please listen to him explain what is happening and what more can be done to understand this phenomenon.

Tragedy has struck the surf community of Ecuador.

One of their best surfers, and a potential candiate for qualification in the Paris 2024 Olympics, Israel Brona, has sadly and mysteriously passed away in El Salvador.

He was 34 years old.

High school junior Julia Black, 16, played in a varsity volleyball game on Wednesday and attended all of her classes on Friday. Then suddenly, inexplicably, she was gone.

Mark Groeneveld, 20, Becomes Fifth Dutch Cyclist to Die or Suffer Serious Heart Problems This Year