Type 2 diabetes and the largest part of the evidence base posts 31–60
This is a continuation of a long topic, addressed by post number rather than by page. Start at post 1.
What I want from this type 2 diabetes thread is the list of things that would need to be true for the claim to hold. If we can write that list, we can check it.
I had written a reply contradicting post #31 and deleted it. Here is what survived.
Asking about a population rather than about yourself is a legitimate framing and generally gets a better answer, because the general case is answerable.
A partial answer, offered because a partial answer beats none.
Two questions I would want answered before drawing anything from the type 2 diabetes data above: how were the cases selected, and what happened to the ones that dropped out.
That is the distinction I keep failing to hold on to. Written down now.
Coming back to post #35, because the follow-up matters more than the original answer.
Where two conditions pull in opposite directions, that is a clinical judgement rather than a lookup, and it is the kind of question a forum answers worst.
I have said this before in a thread nobody could find, so it is worth repeating.
Posting my type 2 diabetes numbers with the method attached so they can be discounted properly. Uncontrolled, unblinded, and collected by someone who wanted a particular answer.
Answering the question post #35 raises rather than the one it answers.
Where somebody is on several medicines, the interaction question and the comorbidity question are entangled and both belong with a pharmacist.
I would put this at better than even and not much better.
Practical experience of type 2 diabetes, offered as one case with the conditions stated, not as a general finding. Conditions first, because they are what make it interpretable.
I read post #38 twice before replying, because I had assumed the opposite.
Multiple comorbidities: a person with diabetes, kidney disease, and cardiovascular disease is outside the studied populations in most trials. Extrapolating to that person requires reasoning from the individual component trials and mechanisms.
That matches what I was told, which is not the same as knowing it.
I would be cautious about generalising from the type 2 diabetes example above. It is a good example. It is one example.
Narrowing post #44, because the general version has more than one answer.
Post-authorisation safety studies are the place where under-studied populations eventually appear, and they are public.
The variance between people here is larger than the effect being discussed.
Everything in post #42 holds. The case it does not cover is the one I have.
Asking about a population rather than about yourself is a legitimate framing and generally gets a better answer, because the general case is answerable.
Written in the hope of being told what I have missed.
Nothing to add on the substance. Thank you for taking the question at face value.
What I would check first on type 2 diabetes is whether the thing being measured moved or whether the way of measuring it moved. Those look identical in a graph.
Confirming post #48 from a second method, which matters more than confirming it from a second person.
The practical value of this subcategory is helping somebody frame the question they take to an appointment, and that is worth being explicit about.
A qualification I should have led with rather than closed on.
Agreed on all of that, and I have nothing to add to it.
Where two conditions pull in opposite directions, that is a clinical judgement rather than a lookup, and it is the kind of question a forum answers worst.
I am not the right person to answer the follow-up to this.
Narrowing post #49, because the general version has more than one answer.
Interactions between comorbidities: diabetes and kidney disease together change the risk calculation for hypoglycemia and for medication clearance. They are not independent variables.
That is the version I use. It may not be the version that is correct.
I would call the community position on type 2 diabetes likely rather than established, and I would be comfortable defending that hedge.
Type 2 diabetes is a question about a distribution, not about a value, and treating it as a value is what produces the confident wrong answers.
I read post #53 twice before replying, because I had assumed the opposite.
Cardiovascular disease: several compounds have cardiovascular outcome trials. SELECT was in people without diabetes; SUSTAIN 6 was in high-risk diabetes. Absolute benefit is largest in high-risk people.
Worth reading the earlier posts in this thread before acting on mine.
Appreciated. The plain phrasing does more work here than a longer post would.
Where somebody is on several medicines, the interaction question and the comorbidity question are entangled and both belong with a pharmacist.
The answer changed when I changed how I was measuring, which was informative.
Practical answer on type 2 diabetes, since the theoretical one is upthread: do the simplest check first, write down the result, and only then decide whether the complicated explanation is needed. It usually is not.
Coming back to post #57, because the follow-up matters more than the original answer.
Counterpoint on type 2 diabetes, offered without confidence: the same observation is consistent with a much duller explanation, and nobody has ruled the dull one out.
Where the honest answer is "nobody knows", giving it plainly is more useful than a confident synthesis of mechanism and anecdote.