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 population was selected and supported in ways a real cohort is not, so I would read the effect size as a ceiling rather than an expectation.
The narrow version of the question is why A1C lags the way it does, and what to look at in the meantime if you want to know sooner. I would rather have one careful answer than five confident ones.
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.
HealthEcon_DC 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 41% 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.
HealthEcon_DC 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…
Complete metabolic panel trending on glycaemic control — sharing because comprehensive data helps everyone:
| Test | Baseline | Month 3 | Month 6 | Month 12 |
|---|---|---|---|---|
| Glucose (fasting) | 125 | 107 | 89 | 85 |
| Insulin (fasting) | 21 | 15 | 9 | 5 |
| HOMA-IR | 5.5 | 3.1 | 1.7 | 1.4 |
| Uric Acid | 7.8 | 6.5 | 5.6 | 5.1 |
The insulin resistance improvement (HOMA-IR) is what my endo focuses on most. Going from 5.5 to near 1.0 is a metabolic transformation.
Janoshik Analytical — Independent Testing
Trusted third-party HPLC & mass spectrometry analysis. Verify peptide purity with the lab the community relies on. Independent. Accurate. Transparent.
Verify Your PeptidesGL Biochem (Shanghai) Ltd. — Direct Manufacturer
Est. 1998. The synthesis house behind the vials you send for testing. ISO 9001 and cGMP certified, 1,500+ staff, batch-specific COA with every order.
Browse GL BiochemJennaRN said:Complete metabolic panel trending on glycaemic control — sharing because comprehensive data helps everyone: Test Baseline Month 3 Month 6 Month 12…
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 = 5.4 (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.
Dr.ObesityLA said:Glycemic variability as the key metric for glycaemic control success: my coefficient of variation (CV) on CGM dropped from 41% to 21%.
This is my experience too, for whatever a second data point is worth. The detail I would add is minor and it is already implied above.