TrialNerd_Beth said:

PCOS success story with glycaemic control: as someone with polycystic ovary syndrome, this medication has been transformative beyond weight loss.

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.

nick_newbie 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.

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: 24 → 14 → 7 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.

kate.chem said:

Patient selection optimization for glycaemic control: emerging predictive biomarkers for GLP-1 agonist response include: Biomarker Association…

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 = 5.0 (insulin resistant) → Current = 1.0 (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.

Following on from LibrarianMeg — and this may be the naive question:

How long did you give it before you decided it was working?

Dr.NutriCornell said:

Insulin sensitivity test (HOMA-IR) on glycaemic control — arguably the most important metabolic marker most people aren't tracking: HOMA-IR = (fasting…

Glycemic variability as the key metric for glycaemic control success: my coefficient of variation (CV) on CGM dropped from 38% to 20%. 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.