The paper discusses how the variables were handled and lists the error for estimates. Is your objection that they calculated it wrong? Or that/how they used a linear model for adjustments? What's the range for "huge"?

I'm saying that there's no reliable data to establish how those variables impacted the final results. The correction factors are mostly just guesswork. Signal to noise ratio is low.

Basically this is junk science. The only proper way to do such a study would be to compare the same subjects before and after infection. With so many cases such a study should be feasible.

We don't know what the SNR is. It would be great if the paper included the linear regression values and fit analysis. It could be rubbish or not - but we don't have the data to confirm or deny that.

I get the objection, but I'm getting annoyed at comments that state what's invalid with the study where we don't have the data available for that claim. What's wrong with "we don't know if the study is valid since we don't have details on X"?

That's not how real science works. The burden is on the paper authors to prove they have adequately controlled. From what I can see they haven't done so.

Overall the majority of COVID-19 clinical research has been rushed and very low quality.