Cool paper from @keling-wang.com showing that 35% of randomly selected diabetes guideline recommendations use stronger causal language than the papers they cite. Such "causal jumps" are not necessarily unwarranted but, at best, lack of transparency in how causal conclusions were arrived at.

Should you include people in your study who have no opportunity to be exposed? Like someone with an absolute contraindication? Turns out the answer is...it depends. There are conditions under which excluding them can actually increase bias through bias amplification.

link.springer.com/article/10.1... So funny that "methodological limitations" are used for both pro-adolecent trans care and anti- sides to accuse the other. "Cass review used Ottawa scale to assess 102 observational studies and found only 2 of high quality" is the funniest joke ive seen this year.