Adding what did not work for me on Type 2 diabetes, since the failures never get written up and they are half the useful information.
Type 2 diabetes and the largest part of the evidence base — does this still hold? I have a specific reason for asking rather than idle curiosity, and the context is below.
Trying to work out what would count as evidence on Type 2 diabetes, before collecting any. This is the part I usually skip and it is the part that makes the rest useful.
If two explanations predict the same observation, observing it does not help. So: what observation would separate them?
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.
The bit of Type 2 diabetes that nobody enjoys is that the answer changes depending on what you are trying to decide with it. Say what the decision is and the thread will converge.
Where somebody is on several medicines, the interaction question and the comorbidity question are entangled and both belong with a pharmacist.
I have written this out at length because the short version keeps being misread.
Worth stating the null on Type 2 diabetes before we explain it: the observation may be nothing. That possibility deserves a sentence and usually does not get one.
Post #5 describes the usual case. This is about the unusual one.
Asking about a population rather than about yourself is a legitimate framing and generally gets a better answer, because the general case is answerable.
Adding thanks rather than a view. I do not have a view worth the space.
Adding what did not work for me on Type 2 diabetes, since the failures never get written up and they are half the useful information.
Type 2 diabetes has a well-known answer and a correct answer, and the interesting work is establishing that they are the same. Nobody has done that here yet.
The practical value of this subcategory is helping somebody frame the question they take to an appointment, and that is worth being explicit about.
Filing this under things that are true until someone shows me otherwise.
Confirming post #10 from a second method, which matters more than confirming it from a second person.
If someone has run Type 2 diabetes properly I would rather read that than my own reconstruction of it. Posting mine only because the thread has gone quiet.
I had written a reply contradicting post #12 and deleted it. Here is what survived.
Type 2 diabetes: the population with the largest evidence base for these compounds. The SURPASS and SUSTAIN programmes established glycaemic benefit. The renal and cardiovascular benefit evidence is separate from the glycaemic benefit evidence.
Adding the measurement that post #14 says would settle it.
Nothing here is medical advice and clinicians posting in this subcategory say so on their own account rather than because a rule requires it.
Reading back through the Type 2 diabetes threads from last year, the same three questions come up every time and only one of them has ever been answered properly. That seems like a documentation gap rather than a knowledge gap.
Type 2 diabetes is well covered in the tag pages, and the older discussions are better than the recent ones because they were argued out properly. Worth twenty minutes before adding to this one.
Where I part company with post #16, and it is a narrow parting.
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.
Taking post #18 at face value and following it one step further.
Interactions between comorbidities: diabetes and kidney disease together change the risk calculation for hypoglycemia and for medication clearance. They are not independent variables.
The strength of my opinion here exceeds the strength of my evidence.
Post #17 put the caveat in the right place and I want to underline it.
I would put moderate confidence on the mainstream reading of Type 2 diabetes and no more. That is not scepticism for its own sake; it is where the sourcing actually stops.
The question underneath Type 2 diabetes is usually "how would I tell?" rather than "what is true?", and that one has a method attached to it.
Write down what you would expect to see under each hypothesis before you collect anything. If they predict the same observation, collecting it will not help.
Nothing to add, except that this is the answer I would give if asked.
Where a condition is well controlled and where it is not are different questions and the published data rarely distinguishes them.
Adding it in case it saves somebody the afternoon it cost me.
Where I have landed on Type 2 diabetes, having got it wrong once in public: the direction is clear, the magnitude is not, and anyone quoting a precise magnitude has borrowed it from somewhere that did not measure it.
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