PeptideChemSF 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 39% to 22%. 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.

LibrarianMeg said:

Glycemic variability as the key metric for glycaemic control success: my coefficient of variation (CV) on CGM dropped from 39% to 22%.

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

After 10 months: periods became regular for the first time in years, testosterone levels normalized, acne cleared significantly, and — unexpectedly — I got pregnant naturally after 4 years of trying.

GLP-1 agonists address the insulin resistance at the root of PCOS. For PCOS patients, this isn't "just" a weight loss drug — it's treating our underlying metabolic dysfunction.

PeptideChemSF 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.

From the other side of the consultation, briefly.

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.