What investigations are needed to determine the cause of suboptimal glucose control in a patient with an Hemoglobin A1C (HbA1c) of 9% and a 3-month Glucose Management Indicator (GMI) of 7.3, normal kidney function, and normal hemoglobin (Hgb) levels?

Investigating the Discrepancy Between A1C and GMI in Diabetes Management

Further laboratory testing is needed to investigate the significant discrepancy between the A1C of 9% and GMI of 7.3%, with specific focus on hemoglobin variants, red blood cell disorders, and iron studies, despite normal hemoglobin and kidney function. 1

Understanding the Discrepancy

The 1.7% difference between A1C (9%) and GMI (7.3%) is clinically significant and requires investigation. According to American Diabetes Association guidelines, such discordance is common but concerning when it exceeds 0.5-1% 1, 2.

Potential Causes for A1C-GMI Discrepancy:

1. Hemoglobin Variants:

   • Hemoglobin variants can interfere with A1C measurement without affecting complete blood count results
   • Recommend hemoglobin electrophoresis to identify variants 1

2. Red Blood Cell Turnover Issues:

   • Despite normal hemoglobin levels, investigate for:
     • Subclinical hemolysis (reticulocyte count, haptoglobin, LDH)
     • Early iron deficiency (ferritin, iron studies)
     • Medications affecting erythropoiesis 1

3. CGM Data Quality Assessment:

   • Verify CGM wear time (>70% of time during measurement period)
   • Check for calibration issues or sensor gaps
   • Confirm the 3-month timeframe aligns with A1C measurement period 3

4. Laboratory Error:

   • Consider repeating A1C measurement using NGSP-certified method
   • Verify A1C was performed using a method without interference from abnormal hemoglobins 1

Recommended Investigations

1. Hemoglobin Studies:

   • Hemoglobin electrophoresis
   • Complete iron studies (ferritin, iron, TIBC, transferrin saturation)
   • Reticulocyte count

2. Red Cell Turnover Markers:

   • Haptoglobin
   • LDH
   • Bilirubin (direct and indirect)

3. CGM Data Validation:

   • Verify percentage of time CGM was worn
   • Review calibration frequency and accuracy
   • Analyze time in range and glucose variability metrics 4

4. Medication Review:

   • Assess for drugs that may affect red blood cell lifespan
   • Review timing of medication changes relative to A1C measurement

Clinical Implications

The discrepancy between A1C and GMI has important clinical implications:

• An A1C of 9% suggests poor glycemic control requiring therapy intensification
• A GMI of 7.3% suggests moderate hyperglycemia closer to target range
• In cases of discordance >1%, the American Diabetes Association suggests that CGM-derived metrics may be more reliable for clinical decision-making 1, 2

Common Pitfalls to Avoid

1. Relying solely on A1C without investigating discrepancies

   • Up to 49% of patients may have A1C-GMI discordance >1% 5

2. Ignoring glucose variability

   • High glucose variability is independently associated with mortality risk, even with similar mean glucose levels 6

3. Failing to repeat A1C measurement

   • Laboratory error or pre-analytical issues can affect results 1

4. Overlooking subclinical hematologic conditions

   • Normal hemoglobin doesn't rule out conditions affecting red cell turnover 1

By systematically investigating these potential causes, you can determine whether to rely more heavily on A1C or CGM metrics for treatment decisions in this patient with discordant glycemic markers.