Introduction: This article is more of a conversation style blog than a research article. It is meant to ask a simple question to a Doctor. However for anyone following this blog, the information contained in the article will be very interesting to you if you have not been following Dr. Robert Malone. Dr. Robert Malone is an expert providing his opinions in real time on Twitter, and the mainstream media has been slow to keep up with him when they do at all.

Dr. Malone, I have followed you on Twitter for some time. As the Twitter format is limiting and you have a great deal of people trying to converse with you, I have attempted to consolidate my thoughts and a for you question into a single source.

The above screenshot has some very interesting information to me. The screenshot comes from a Nature article: Fructose in the diet expands the surface of the gut and promotes nutrient absorption. (A brief lament: the link to the Nature “article” has extremely limited information. It has only a few sentences. It would cost $199.00 to access the full Journal study, where the screenshot was apparently taken. We laymen are often criticized by those who say “you are not a doctor.” I am capable of reading and educating myself as any doctor would, however. The barriers to information that are created by the scientific community are disturbing. This is not the way Hippocrates would have it.)

As I said, I am not a doctor. However, when I see a picture showing “pathways that aid survival of hypoxic cell” relating to fructose, I can certainly raise a question about how fructose may or may not affect mortality rates from COVID-19. Dr. Malone noted that obesity rates are positively correlated with mortality rates. Of course, fructose is also positively associated with obesity.

The question becomes does fructose increase the likelihood of death from COVID-19 *ceteris paribus*, (all other things being equal). That is to say, is there a specific cellular effect of fructose that aids COVID-19 absorption or hinders the bodies response to the virus that is independent of body weight. In other words, would the “obese” die at a lower rate if they stopped consuming fructose but remained the same weight. This is a simple question to solve statistically, but in the absence of a good data set, we must rely on specific medical knowledge of medical experts.

The hypothesis that I hope the good doctor will address could literally save lives if it is true. The public could consume less high fructose drinks and have a better chance of survival. If it is not true, there is nothing wrong in the pursuit of the question.

The rest of the article is for those who do not follow Dr. Robert Malone on twitter. It has some relevant screenshots of his thoughts and how they changed in real time. History in the making.

The above tweet was related to Dr. Malone’s opinion on the efficacy of Ivermectin for COVID-19. Dr. Malone used Ivermectin himself. The screenshot is apparently an image derived from this study from Japan: Why COVID-19 is not so spread in Africa: How does Ivermectin affect it?

The above study shows that countries that countries in Africa that used Ivermectin fared far better than those that used the new mRNA vaccines. Dr. Malone would later note however that these same countries that used Ivermectin also had a much lower obesity rate, and thus, the question should remain as to whether Ivermectin or lower obesity rates should be credited for the positive results. I would add that both factors Ivermectin and lower BMI could be positive factors, and that synergistic effects between the two factors are possible if not likely.

The above tweet shows that Dr. Malone believed in Ivermectin enough to take it himself. For those who don’t know, he is an expert Doctor with specific medical knowledge on mRNA vaccines.

And here is where Dr. Malone noted that less obese countries also used Ivermectin more. Again this is information is being discovered and presented in real time. Dr. Malone added that the image above is a screenshot from the following source: World Population Review, Obesity Rates 2021.

And here above we see the problem that the medical community faces. There are an infinite number of positive and negative factors that influence COVID-19 mortality rates. No human could sort through these many “confounding variables” with specific medical knowledge alone. A computer could do it in the blink of an eye, however.

The concept is called regression analysis or ordinary least squares (OLS). Carl Friedrich Gauss is generally given credit for the concept in the early 19th century (but also Adrien-Marie Legendre). So it’s nothing new. Computers weren’t around back then. Quantum computers weren’t around back then. But Gauss figured out the coefficients that influenced the elliptical orbits of planets anyway.

So, if Gauss were to answer my hypothesis, based on what other information that Dr. Malone has discussed, he would gather the statistics of the following variables: A: Fructose consumption; B: Ivermectin Consumption; C: Body Mass Index; D: Parasitic Infection Exposure. I don’t know if Gauss would have used a probit model or not, but that’s the one I would start with.

As wikipedia says, “a **probit model** is a type of regression where the dependent variable can take only two values, for example married or not married.” In this case, dead or not dead. These two states are represented by the digits 1 (One) and 0 (Zero).

And then the model would simply be One or Zero = Constant +A +B +C +D. And you invert the “matrix” of rows and columns with matrix algebra. Simple stuff today, but undoubtedly took a lot of time to do manually back in Gauss’s day. The result will give you a regression coefficient per variable, in other words, the extent to which variable affected mortality. You will also get a statistic that tells you the likelihood that the variable affected the mortality rate. (This is the type of study used where people say things like “there is a 96% chance that (something)).

And of further note, many other variables besides A,B,C, and D will undoubtedly influence mortality rates. Which ones? So many. Want to find out? Add every other variable after A,B,C, and D that you can quantify. Gender, age, your entire diet, climate data, etc. Anything you can quantify that might possibly have an impact on mortality. Where to get the data? Google, for one. Google has quantum computers running artificial intelligence. It is possible that Google already know the positive and negative factors that influence COVID-19 mortality rates. Those with the data and computing power can solve the every question of (how does this influence COVID-19 mortality rates) at once, immediately.

It is time for the good people in the medical community to combine their specific medical knowledge with correct statistical approach. This approach has likely already been done by those who hoard the data and use it for purposes not in the general interest of humanity.

In the meantime though, what of the hypothesis that fructose increases death rates from COVID-19 exposure by some cellular process unrelated to BMI? What does specific medical knowledge suggest? It’s seems like an important single factor to consider…

I’ll end the article with the first page of “Gauss’s Contributions to Statistics.”

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