Read the primary source rather than the write-up and the two do not agree, so here is what is actually in it.
HbA1c reflects roughly three months of average glycaemia weighted toward the most recent weeks, which is why repeating it at six weeks tells you very little. The improvement on this class comes from two directions — direct glucose-dependent insulin secretion and glucagon suppression, plus the indirect effect of weight loss on insulin sensitivity — and the second continues after the first has plateaued.
Where I think it is weakest: the subgroup findings are the part I trust least — with enough subgroups something is always significant, and these were not all pre-registered.
What would genuinely help is knowing why A1C lags the way it does, and what to look at in the meantime if you want to know sooner. Not looking for reassurance. Looking for the part I have got wrong.
Figures above are from the primary publication rather than the press summary. If a number here disagrees with one you have, post yours and we will work out which of us is reading a secondary source.
sean_dublin said:HbA1c reflects roughly three months of average glycaemia weighted toward the most recent weeks, which is why repeating it at six weeks tells you very…
Insulin sensitivity test (HOMA-IR) on glycaemic control — arguably the most important metabolic marker most people aren't tracking:
HOMA-IR = (fasting insulin × fasting glucose) ÷ 405
My numbers: Baseline HOMA-IR = 4.8 (insulin resistant) → Current = 1.2 (insulin sensitive)
Anything above 2.0 indicates insulin resistance. The goal is below 1.5. GLP-1 agonists address the root metabolic dysfunction, not just the symptoms. This is why they work so much better than calorie restriction alone.
sean_dublin said:HbA1c reflects roughly three months of average glycaemia weighted toward the most recent weeks, which is why repeating it at six weeks tells you very…
Glycemic variability as the key metric for glycaemic control success: my coefficient of variation (CV) on CGM dropped from 35% to 21%. Target is <36%, with <30% being ideal.
Why this matters more than average glucose: large glucose swings cause oxidative stress, endothelial damage, and promote advanced glycation end-products (AGEs). A flat glucose line at 95 mg/dL is metabolically healthier than oscillating between 60 and 160, even if the average is the same.
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Browse GL BiochemDr.MetabolicMD said:Glycemic variability as the key metric for glycaemic control success: my coefficient of variation (CV) on CGM dropped from 35% to 21%.
Patient selection optimization for glycaemic control: emerging predictive biomarkers for GLP-1 agonist response include:
| Biomarker | Association | Evidence Level |
|---|---|---|
| Baseline BMI | Higher BMI → greater absolute weight loss | Strong |
| Fasting insulin | Higher insulin → better response | Moderate |
| GLP1R gene variants | rs6923761 → variable response | Preliminary |
| Baseline hsCRP | Higher CRP → greater CV benefit | Moderate |
| Early weight loss (4 wk) | ≥3% at 4 wks → strong predictor of ≥10% at 68 wks | Strong |
The 4-week early responder criterion is the most clinically actionable: if you haven't lost ≥3% by week 4 at a therapeutic dose, discuss optimization strategies with your provider.
mike.trainer_LA said:Insulin sensitivity test (HOMA-IR) on glycaemic control — arguably the most important metabolic marker most people aren't tracking: HOMA-IR = (fasting…
This matches mine closely enough to be worth saying so out loud. I had assumed I was the exception until I read this.