Cardiovascular risk: reading the outcome trials as a set

Cardiovascular risk: reading the outcome trials as a set Writing it up because I had to work it out twice and would rather nobody else did.

Asking about a population rather than about a person.

The published trials in this class mostly enrolled a fairly specific group, and the questions here frequently come from people well outside it. I would like to understand what the honest position is when someone falls outside the studied population: not "it is fine" and not "there is no data", but what the reasoning actually looks like.

PCOS and metabolic overlap: polycystic ovary syndrome has metabolic overlap with obesity and insulin resistance. Data on compounds in this class in PCOS specifically is thin; most discussion is by mechanism.

Coming back to the opening post, because the follow-up matters more than the original answer.

Interactions between comorbidities: diabetes and kidney disease together change the risk calculation for hypoglycemia and for medication clearance. They are not independent variables.

Picking up the opening post: that is the part I would want checked first.

For anyone arriving from a search: the marked solution above is the direct answer, and the replies underneath it add the caveats that make it safe to use.

Two things before anyone answers the substance.

First, the context in the first post is clear and specific. Second, the question is framed so that an answer can actually address it. Both are the norm here and both matter more than they sound.