First thing to note: This was posted on Dropbox, not onto a regular preprint server such as @biorxivpreprint or @medrxivpreprint - not sure why.
And also important to point out that this is NOT a peer-reviewed paper. It is draft meant for others to comment on.
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You can see that several people left comments on the Dropbox document. One of them is an emoji of a weird gnome stroking his beard. Not sure what that is supposed to mean.
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Short summary of the study: 636 patients were enrolled by "telemedicine" or by ER doctor. They were offered treatment with HCQ+AZM. If they accepted they were the treatment group. If they refused, they were the control group. That is a strange set up, not randomized at all.
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Patients were recruited if they had persistent flu-like symptoms for 2 or more days, with a suspicion for COVID-19 infection, but no PCR test was done.
This is a big red flag. We are not sure if they had COVID-19 or if they had the sniffles.Show this thread -
Typical symptoms for COVID-19 are fever and cough.
Yet, at baseline, of these 636 patients only 6.6% had fever and 43% had a cough. These 2 symptoms also differed significantly between the 2 patients groups.Show this thread -
This brings me to another interesting fact. There are significant differences between treatment and control group. In general treatment group had higher incidence of fever, cough, diarrhea, muscle aches, etc. They appeared to be a bit sicker at baseline than the controls.pic.twitter.com/hXgI3OPDsY
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In light of the findings of this paper, that the treatment group did better (fewer hospitalizations), it is interesting that the treatment group was sicker at the beginning. So treatment might help. But in general it is not good that treatment groups differ at baseline.
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There are some inconsistencies/unclarities in the paper that need to be fixed. * Methods (page 7) say that patients were recruited at 2 or more days of symptoms, but later (page 8) it says over 3 days (so presumably 4 or more).pic.twitter.com/faKHxlo8Bj
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In the Methods it is stated that patients were followed for 14 days after symptom onset (by telemedicine). The Results state that average follow up was 5.0 days - not sure how these two numbers match. The authors need to provide a bit more clarity in these numbers.pic.twitter.com/OpSJiMk13N
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It seems important to do a longer follow up on these patients. Five days seems very short. If they were already sick for 2-3 days, and you follow them for only 5 days, who knows if they maybe got sicker.
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Here is a very interesting finding: the earlier patients were treated, the lower the chance they ended up in the hospital. However, it is not stated in Table 1 how/if the 2 treatment groups differed in days-of-symptoms at baseline. This is a big omission.pic.twitter.com/bRYJNUmNEP
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If the treatment group had a significantly shorter sick period than the control group, that could be an important, not disclosed, confounding factor. As of now, this important piece of data is missing.
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Table 2 shows findings of the CT scans done "according to medical judgement". WTF? 61% of the treatment group got a CT scan. Only 24% of the control group got a CT scan. This is fishy. If control group was more ill, why did only so few get a CT scan???pic.twitter.com/oNEzNkLbW6
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Also, looking at Table 2, it shows that the treatment group had more COVID-19 suggestive CT scans than the Control group. All these findings suggest that some people in the control group might have had an illness different than COVID-19.
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The paper is also very vague about why people were hospitalized. From Table 2 you could state that the Control group had fewer reasons to undergo a CT scan, and milder severity of lung involvement than the Treatment group. So why were so many Controls admitted to the hospital?
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Also of note, two patients in the Treatment group died, of underlying disease. Looking at that outcome, the Control group (no deaths noted) appeared to do much better.
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So let's recap. 1. No PCR confirmation, not clear how many people actually had COVID-19. 2. No randomization, patients could pick their group 3. Unclear if 2 groups differed in time between first onset and enrollment. 4. Treatment group appeared to be sicker/more COVID/deaths.
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Another weakness of the ms:
@houndcl did a simple stat test to show that the p<0.0001 from Figure 1 is not quite true. But then, I am not familiar with the "qui-square test". https://twitter.com/houndcl/status/1251556044729315330 … HT:@FilipeDeVadder (I deleted an earlier tweet with the wrong p value).pic.twitter.com/9VcLV46gwp
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And to conclude, here is another takedown of the study by
@GaetanBurgio , done earlier today: https://twitter.com/GaetanBurgio/status/1251476181989208066 … HT:@VerranDeborah and@tesoureiros (I hope I hat-tipped everyone appropriately; my notifications are going wild hahaha).Show this thread -
Ooooh, I just found another problem. Not everyone in the Control group appeared to have COVID-19. The percentages add up to only 71%. I am more and more convinced the control group on average was sick with something else. This stinks.pic.twitter.com/yYG7WwtMLA
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Here is a blogpost about the paper, which is basically a bit more polished version of this thread:https://scienceintegritydigest.com/2020/04/18/thoughts-on-the-prevent-senior-study/ …
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End of conversation
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