How To Reverse-Engineer "Missing" I-Tech Ivermectin Data?

How To Reverse-Engineer “Missing” I-TECH Ivermectin Data?

Ivermectin proponents are claiming that KKM hid some data in their I-TECH ivermectin study.

Find out if that’s true, and how you too can reverse-engineer the “missing” data!

 

Claim : I-TECH Ivermectin Mortality Data Missing!

On 4 Novembre 2021, the Malaysia Ministry of Health (KKM) released a summary of their I-TECH ivermectin study. It was immediately panned by ivermectin proponents, because it showed that ivermectin had no clinical benefit.

Soon after, they began to claim that KKM hid some data in their I-TECH ivermectin study, particularly the mortality data. Some even accused the Health Director-General, Dr. Noor Hisham Abdullah of lying.

Malaysian Ivermectin Trial Shows a 70% of Reduction in Deaths

HISHAM TIPU APA HARI INI (WHAT HISHAM LIED ABOUT TODAY)

MOH’s sham ivermectin trial has concluded and a brilliant mind (Steve Kirsch) has analysed the result.

The number of deaths in both groups is not stated in Hisham’s press release (why did he hide this???) but Steve’s people managed to reverse-engineer it from the statistics numbers. Damn great minds. I really take my hat off to them.

 

Did KKM Hide I-TECH Ivermectin Mortality Data?

It is true that the Malaysia Ministry of Health press release did not include details of the difference in mortality between the two groups.

However, it is false to claim that they lied, or are trying to hide the mortality data, because :

  1. The press release specifically mentioned that “there was a trend of reduced 28-day mortality, but it was not statistically significant (p=0.09).
  2. They sought independent analysis of the mortality results, but even the two experts could NOT determine if mortality was indeed reduced, due to the few deaths in this study.
  3. They released some data on the mortality of the study participants :
    13 deaths out of 490 participants, at the end of 28 days
    – the ivermectin group had lower mortality, OR 0.30 [95% CI 0.08-1.11]; p=0.09

It seems obvious that they wanted to avoid misinterpretation of the mortality data. I will explain and show you why that’s the case in a separate article after this.

 

How To Reverse-Engineer “Missing” I-TECH Ivermectin Data?

The mortality of each group can be, and have apparently been, reverse-engineered from the data above, which ivermectin proponents are claiming is incredibly difficult.

  • to make it look like there is a malicious attempt at hiding the truth
  • to make themselves look smarter than the real scientists and doctors

That’s not true at all. I reverse-engineered the data in less than 10 minutes, and so can you!

Let me show you how…

Prepare Known Data

First, list down what KKM publicly released in their summary of the I-TECH study results.

Total Study Participants : 490
Deaths After 28 Days : 13
Fewer people died in IVM group, compared to SOC group

OR 0.30 [95% CI 0.08-1.11]; p=0.09

Odds Ratio : 0.30
95% Confidence Interval : 0.08 to 1.11
P-value : 0.09

Use An Odds Ratio Calculator

Next, use an Odds Ratio calculator to reverse-engineer the study numbers, by simply filling in four numbers :

a = number of people who died in IVM group
b = number of people who survived in IVM group
c = number of people who died in SOC group
d = number of people who survived in SOC group

Start by assuming that there are equal number of people (245) in both groups, and since fewer people in the IVM group died, start by testing the 6-7 ratio (see first screenshot below).

Then work backwards until you see the results match the publicly-released KKM data – OR 0.30 [95% CI 0.08-1.11]; p=0.09.

You will only need FOUR tries :

  • 6-7 ratio : OR = 0.85
  • 5-8 ratio : OR = 0.63
  • 4-9 ratio : OR = 0.45
  • 3-10 ratio : OR = 0.30 (we have a winner!)

See? That didn’t take more than 2-3 minutes, did it?

Adjust The Group Sizes

But the 3-10 ratio with equal group sizes have a problem – the P-value is 0.06, not 0.09.

It would appear that there are fewer people in the IVM group, so this is the time to adjust the group sizes (b and d) further (without changing a and c).

  • 242-235 ratio : P=0.0635
  • 241-236 ratio : P=0.0653
  • 240-237 ratio : P=0.0672
  • 239-238 ratio : P=0.0691
  • 238-239 ratio : P=0.0710 (closest to OR 0.30 95% CI 0.08-1.11)
  • 237-240 ratio : P=0.0730
  • 236-241 ratio : P=0.0751
  • 235-242 ratio : P=0.0772
  • 234-243 ratio : P=0.0793
  • 233-244 ratio : P=0.0815
  • 232-245 ratio : P=0.0837
  • 231-246 ratio : P=0.0860 (closest to P=0.09)

Now we derive two results. The first is closest to the KKM results, but with P=0.07 (not P=0.09). See second screenshot above.

The second is the closest we can get to P=0.09 – with slightly different results of OR 0.32, 95% CI 0.09-1.12

This shows the limitation of reverse engineering, and why it is still best to obtain the actual data.

Fortunately, the Malaysia Ministry of Health is in the process of submitting the I-TECH study data for publication in a peer-reviewed journal. So we will eventually have the actual mortality results.

But I hope that you learned something new from this guide, at least come away with the understanding that there is nothing magical about this. It’s really just science and math.

 

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Dr. Adrian Wong has been writing about tech and science since 1997, even publishing a book with Prentice Hall called Breaking Through The BIOS Barrier (ISBN 978-0131455368) while in medical school.

He continues to devote countless hours every day writing about tech, medicine and science, in his pursuit of facts in a post-truth world.

 

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