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It’s a retrospective study with people having comorbidities. Right off the bat it’s flawed.

More importantly it’s from CNN which makes things up from whole cloth.

It appears to be neither randomized nor stratified.

The relevant question to ask is what criteria were used to assign a patient to the HCQ group and others to the non-HCQ group?

I’ll do a little arithmetic from CNN’s report to see if we can understand what’s going on a little better.

> “In the new study, among the 84 patients who took hydroxychloroquine, 20.2% were admitted to the ICU or died within seven days of taking the drug.”

So note that 17 patients went in the ICU or died who had taken HCQ.

> “Among the 97 patients who did not take the drug, 22.1% went to the ICU or died.”

So note that 21.4 patients went to the ICU or died who had not taken HCQ. Let’s check this arithmetic,

97 x 0.221 = 21.437

I wonder where they got the 0.437 dead or ICU patient from? Is this CNN math?

Let’s move on.

The difference was not determined to be statistically different. Without details on how patients were assigned to HCQ or not, without details about the overlap of ICU patients with patients who died, a statistical test result has no value worthy of publishing. I suspect CNN was doing what CNN does.

> “Looking just at deaths, 2.8% of the patients who took hydroxychloroquine died, and 4.6% of the patients who did not take it died. That difference was also not found to be statistically significant.”

According to CNN’s previous paragraph, there were 181 total patients, 84 on HCQ and 97 not on HCQ. Of these, 17 of the HCQ group went to the ICU or died (overlap was probable but not mentioned) and 21.4 of the non-HCQ went to the ICU or died.

The arithmetic yields:

84 x 0.028 = 2.4 deaths in the HCQ group
97 x 0.046 = 4.5 deaths in the non-HCQ group

Hmmm ... CNN uses some interesting math to come up with fractional deaths. I’m straining my eyes to make sure I see the reported numbers correctly. It’s probably the overlap of patients dying in the ICU. If all patients who died had died in the ICU or all had died outside the ICU, here should be no fractional deaths. There’s likely an overlap not reported.

So this was “Looking just at deaths” which are about 7 deaths (2.4 + 4.5) of a total of 181 patients taking into account those patients that were fractionally dead.

And so it appears that of the total 181 patients there were 181 - 7 = 174 who did not die.

CNN reports these patients had comorbidities and yet most survived.

> “In the study, eight patients who took the drug developed abnormal heart rhythms and had to stop taking it.”

CNN talks of a ‘doctor’ who goes off about heart side effects from HCQ yet says only that HCQ patients developed negative heart side effects, yet there is no mention of negative heart side effects of the non-HCQ group.

Why am I pointing this out? Because all these patients had pneumonia from presumably COVID-19 and how much you wanna bet when you’re struggling to breath, when you’re suffocating you don’t experience a whole lot of heart beating abnormalities?

So CNN reports the HCQ patients with heart problems were taken off HCQ. Well then, how many in the non-HCQ group experienced heart beat problems? How does one do a comparison and how to account for the 8 HCQ ‘dropouts’? That’s about 10% of the HCQ group taken out of the HCQ group. That adds 8 HCQ dropouts to the 97 non-HCQ group. That kind of movement could have am impact but regardless it’s still not worthy of publication because this retrospective study doesn’t pass muster.

I feel like I lost about 40 IQ points reading CNN math.

I should stop now before I get the CNN virus and die.

A few last blurbs from me, this ‘preprint’ went to Yale where a previous garbage study was performed on a handful of severely comorbid patients. Let’s be clear if you are dying of a heart attack or cancer, and you’re brought to the ER and put in the ICU. chances are you are going to die of your heart attack or cancer and if you test positive for SARS-COV-2, nothing is likely to save you. You will likely not die of COVID-19, you will die of your heart attack or cancer. Or if you are suffocating from COVID-19 ARDS and you wait too long to get to the ER and you have severe comorbidities, you are going to die with or without HCQ. Yet the Yale system of satellites is hyping HCQ ineffectiveness even though the studies they have are horribly underpowered, poorly designed, and attached to wild invalid inferences. It’s garbage.

I’ve tried to be as objective as possible without any bias but I just don’t see the ‘rig for failure’ studies here having any scientific merit. There’s just none. If I saw any, I would call it fairly like an umpire who understands very well the strike zone. Every pitch in this study that CNN reported was out of the strike zone or hit with a foul, and they are trying so hard to call it the exact opposite.

We are witnessing scientific misconduct which has over the past two decades entered a ‘tolerance’ zone like transsexism . This was made clear with the global warming misconduct discovering data alteration in East Anglia, with misleading inferences by Michael Mann at NASA, and so many other Gore-level ‘experts’. I fear the science discipline is taking a hit and we are witnessing it here.