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.

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.

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:

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.