{"id":79,"date":"2022-01-24T17:44:47","date_gmt":"2022-01-24T17:44:47","guid":{"rendered":"https:\/\/experimentalfrontiers.peachpuff-wolverine-566518.hostingersite.com\/?p=79"},"modified":"2022-01-27T00:16:25","modified_gmt":"2022-01-27T00:16:25","slug":"orwellian-science","status":"publish","type":"post","link":"https:\/\/scienceblog.com\/experimentalfrontiers\/2022\/01\/24\/orwellian-science\/","title":{"rendered":"Orwellian Science"},"content":{"rendered":"

It was January, 2020, the very beginning of COVID, when news articles began appearing that connected the genetics of the virus with gain-of-function research on bat coronaviruses at the Wuhan Institute of Virology. These speculations were put to rest by an authoritative statement in the prestigious journal\u00a0Nature Medicine<\/a>, echoed by a summary in\u00a0Science<\/a>\u00a0and an unusual affidavit in the\u00a0Lancet<\/a>\u00a0signed by an impressive list of prominent scientists. The message was dispositive: \u201cOur analyses clearly show that SARS-CoV-2 is not a laboratory construct or a purposefully manipulated virus.\u201d But where was the support for this confident conclusion in the article itself? The 2200 word article contained a lot of natural history and sociological speculation, but only one tepid argument against laboratory origin: that the virus\u2019s spike protein was not a perfect fit to the human ACE-2 receptor. The authors expressed confidence that any genetic engineers would certainly have computer optimized the virus in this regard, and since the virus was not so optimized, it could not have come from a laboratory.<\/p>\n

Of course, most readers, even most scientists, take in the executive summary and do not wade through the technical details. But for careful readers of the article, there was a stark disconnect between the Cliff Notes and the novel, between the article\u2019s succinct conclusion and its detailed scientific content.<\/p>\n

This was the beginning of a new practice in the write-up in medical research. Recent revelations in the\u00a0Fauci\/Collins emails<\/a>\u00a0shed light on the origins of this tactic and the motives behind it. In the past, if a company wanted, for example, to make a drug look more effective than it really was, they would choose a statistical technique that masked its down side, or they would tamper with the data.<\/p>\n

What they would\u00a0not<\/em><\/strong>\u00a0do, in the past, was to describe the results of a statistical analysis that proves X is false, then publish it with an Abstract that claimed X is true. But this strange practice has become common in the last two years. Academic papers are being published in which the Abstract, the Discussion section and even the title flatly contradict the content within.<\/p>\n

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\u201cIncreases in COVID-19 are unrelated to levels of vaccination across 68 countries and 2947 counties in the United States\u201d<\/strong><\/p>\n

This is the title of a\u00a0paper by two statisticians from Harvard School of Public Health<\/a>, published on Sept 30 in the European Journal of Epidemiology. The title makes the important claim that there is\u00a0no public health benefit<\/em><\/strong>\u00a0from vaccination. COVID-19 is spreading at the same rate in different populations, unrelated to whether the population is mostly vaccinated or mostly unvaccinated. It\u2019s a powerful counterpoint to the ubiquitous demand that more people should undergo vaccination for the sake of their community. It completely undermines the requirement of vaccination to attend meetings, concerts, theater, and other public gatherings. It says there is no legitimacy to the creeping government vaccine mandates for travel.\"Fig.<\/p>\n

But the data in the paper don\u2019t show that vaccination and spread of COVID-19 are \u201cunrelated\u201d. In fact, there is a paradoxical relationship, an insidious relationship: the more vaccinated countries had more new COVID cases (during the week when the survey was conducted). The correlation is significant (p=0.04). Still, the authors conclude by explicitly recommending propagandizing of the unvaccinated: \u201cIn summary, even as efforts should be made to encourage populations to get vaccinated it should be done so with humility and respect.\u201d<\/p>\n

It may sometimes be wrong to promote flawed health policy, but it\u2019s a good thing, so long as it is done with humility and respect.<\/p>\n

Why would these researchers take the trouble to publish data that is so damning to the vaccine narrative, and then pull punches in the title and in the conclusions? This seems to be a different case from the above, where shills for the pharmaceutical industry set out to create a deceptive narrative. I think it\u2019s probable that in this case, soft-pedaling the implications of these glaring data may not have been the authors\u2019 choice, but rather the journal editors\u2019. I know from personal experience how difficult it is to get an article through peer review at most \u201creputable\u201d medical journals when the results are out of sync withthe COVID narrative. It may well be that these authors fought hard to get their subversive message into print, and in order to get past peer review, they softened the language, especially, the title.<\/p>\n

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Phase I Study of High-Dose L-Methylfolate in updates Combination with Temozolomide and Bevacizumab in Recurrent IDH Wild-Type High-Grade Glioma\u00a0\u00a0<\/strong>Link<\/a><\/p>\n

This example is unrelated to the pandemic, but it typifies a common practice in the pharma-dominated world of medical research. If a remedy is cheap and out of patent, there is no one motivated to study its efficacy. But research practice has gone well beyond neglect. In fact, they are skewing statistics to make cheap, effective treatments look ineffective if they are in competition with expensive pharma products. This is ridiculously easy to do \u2014 literally, all it requires is incompetence. Using the wrong statistical test, using a weak test when a stronger one applies, or just about any mistake in parsing the data is far more likely to make compelling data appear random than the opposite. In the case of this article, a simple B vitamin has been shown to double the life expectancy of 6 out of 14 brain cancer patients who receive it, while the other half show no benefit (and no harm).<\/p>\n

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The purple jagged line extending out to the right represents 40% of patients who lived dramatically longer when treated with Methyl folate.<\/p>\n

The abstract reports that \u201cLMF-treated patients had median overall survival of 9.5 months [95% confidence interval (CI), 9.1\u201335.4] comparable with bevacizumab historical control 8.6 months (95% CI, 6.8\u201310.8).\u201d The increase in\u00a0median<\/em><\/strong>\u00a0survival time is just a few months and not statistically significant. But the\u00a0average<\/em><\/strong>\u00a0survival time of the folate-treated group was more than double, and the difference was statistically significant (by my calculation, not in the article). The average is what is more commonly reported, and most readers don\u2019t understand the difference between average and median.<\/p>\n

The longest surviving patient on the B vitamin was still alive at the end of the study (3\u00bd years) when every one of the patients treated only with traditional chemo was dead before 1\u00bd years. There were three different dosages in the study, (30, 60, 90 mg) and it was not reported whether the longest-living patients were receiving the highest dosages.<\/p>\n

This is, in fact, a hugely promising pilot study about treating a common, fatal cancer with a simple vitamin. If it were an expensive chemotherapy drug instead of a cheap vitamin, you can be sure it would have been hailed as a breakthrough. But this study will not create much excitement, and few oncologists will even know to prescribe methyl folate for their glioma patients.<\/p>\n

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Winter Statistical Report from Public Health Scotland\u00a0<\/strong><\/span>[<\/span>Link<\/a>]<\/span><\/p>\n

There is a section of this report comparing vaccinated and unvaccinated rates of disease, preceded by a warning to the reader not to take the data at face value.<\/span><\/p>\n

\u201cPLEASE READ BEFORE REVIEWING THE FOLLOWING TABLES AND FIGURES
\nThere is a large risk of misinterpretation of the data presented in this section due to the complexities of vaccination data\u2026\u201d<\/span><\/p>\n

The data they don\u2019t want us to misinterpret say that people who have been vaccinated with 1 shot or 3 shots are half again as likely to contract COVID, compared to people who are unvaccinated. People who receive 2 shots are more than twice as likely to contract COVID. This is according to the authors\u2019 own method of calculating age-standardized disease rates.<\/span><\/p>\n

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The authors emphasize that it\u2019s not about case numbers \u2014 it\u2019s about severe outcomes, hospitalizations and deaths.<\/span><\/p>\n

\u201cEvidence suggests the COVID-19 vaccines are 90% effective at preventing a severe outcome of COVID-19. COVID-19 hospitalisations and deaths are strongly driven by older age, with most deaths occurring in those over 70 years old and having multiple other illnesses. But overall, you are less likely to be hospitalised if you are vaccinated with a booster.\u201d\u00a0<\/span><\/p>\n

What data are they talking about? Here are results from their own data table:<\/span><\/p>\n

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The only substantial reduction is from people who received the third shot, which has only recently been available in Scotland. For the 3-shot cohort only, vaccination effectiveness is declining over the 4 weeks. This adds to previous evidence that protection from the vaccine is short-lived, and each injection provides a shorter window of protection than the previous one. Also note that the hospitalization statistics\u00a0<\/span>may have been gamed<\/a>.<\/span><\/p>\n

Since the publication of this article, England but not Scotland has backed off requirements for vaccination IDs.<\/span><\/p>\n

Clinically Suspected Myocarditis Temporally Related to COVID-19 Vaccination in Adolescents and Young Adults [<\/strong><\/span>link<\/strong><\/a>]<\/strong><\/span><\/p>\n

Myocarditis, or inflammation of the heart, is a severe and life-shortening diseases. It is virtually unknown in young people, but it is a recognized side-effect from the COVID vaccines, especially in boys and young men.\u00a0<\/span><\/p>\n

This article summarizes the experience of 139 patients who were hospitalized for myocarditis following vaccination. 19% of them were taken into Intensive Care.<\/span><\/p>\n

\u201cConclusions: Most cases of suspected COVID-19 vaccine myocarditis occurring in persons <21 years have a mild clinical course with rapid resolution of symptoms.\u201d<\/span><\/p>\n

\u201cMild clinical course\u201d \u2014 I suppose this refers to the 81% who did not go to the ICU.<\/span><\/p>\n

\u201cRapid resolution of symptoms\u201d \u2014\u00a0<\/span>How would anyone know this? Myocarditis in older patients\u00a0<\/span>doubles the probability of death for the long term<\/a>. We don\u2019t know what it will do to young boys, because myocarditis has been unknown in this population before the mRNA vaccines. We don\u2019t understand the mechanism by which the vaccines cause myocarditis, and we don\u2019t know whether the\u00a0<\/span>mRNA permanently integrates into the human genome<\/a>\u00a0so that it causes ongoing production of the spike protein.\u00a0<\/span><\/p>\n

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Receipt of COVID-19 Vaccine During Pregnancy<\/strong><\/p>\n

Earlier this year,\u00a0MacLeod et al<\/a>\u00a0used data from a\u00a0prominent CDC study<\/a>\u00a0to calculate that for women in their first trimester, the rate of miscarriage was an alarming 82%. Last week, the CDC put out a\u00a0report<\/a>\u00a0designed to dispel our misgivings about vaccinating pregnant women. Its conclusions were unequivocal: \u201cThese data support the safety of COVID-19 vaccination during pregnancy. CDC recommends COVID-19 vaccination for women who are pregnant, recently pregnant, who are trying to become pregnant now, or who might become pregnant in the future.\u201d<\/p>\n

Here are three problems with the analysis of vaccine side-effects related to pregnancy.<\/p>\n