A1C went from 7.4 to 5.6 over nine months and my prescriber was more interested in the fasting insulin, which I did not expect.
Because it is glucose-dependent, this class carries a low intrinsic hypoglycaemia risk on its own — the risk arrives when it is combined with insulin or a sulfonylurea, which usually need reducing.
So the question, as narrowly as I can put it: 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.
anna.melb_AU said:A1C went from 7.4 to 5.6 over nine months and my prescriber was more interested in the fasting insulin, which I did not expect.
Glycemic variability as the key metric for glycaemic control success: my coefficient of variation (CV) on CGM dropped from 35% to 19%. 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.
DebRD_ATL said:Glycemic variability as the key metric for glycaemic control success: my coefficient of variation (CV) on CGM dropped from 35% to 19%.
Fasting insulin is the lab my functional medicine doctor cares about most for glycaemic control: it's a much earlier marker of metabolic dysfunction than glucose or A1C.
My fasting insulin: 23 → 15 → 5 uIU/mL over 9 months. Target is <7. By the time your fasting glucose is elevated, your insulin has been elevated for YEARS trying to compensate.
Ask your doctor to include fasting insulin in your bloodwork panel. It's cheap (~$20) and incredibly informative.
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Shop Reference Standardsanna.melb_AU said:A1C went from 7.4 to 5.6 over nine months and my prescriber was more interested in the fasting insulin, which I did not expect.
This matches mine closely enough to be worth saying so out loud.
Clinical perspective, offered as context rather than as advice.
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.