Hemoglobin A1c and Self-Monitored Average Glucose

Background: Previously we have introduced the eA1c—a new approach to real-time tracking of average glycemia and estimation of HbA1c from infrequent self-monitoring (SMBG) data, which was developed and tested in type 2 diabetes. We now test eA1c in type 1 diabetes and assess its relationship to the hemoglobin glycation index (HGI)—an established predictor of complications and treatment effect. Methods: Reanalysis of previously published 12-month data from 120 patients with type 1 diabetes, age 39.15 (14.35) years, 51/69 males/females, baseline HbA1c = 7.99% (1.48), duration of diabetes 20.28 (12.92) years, number SMBG/day = 4.69 (1.84). Surrogate fasting BG and 7-point daily profiles were derived from these unstructured SMBG data and the previously reported eA1c method was applied without any changes. Following the literature, we calculated HGI = HbA1c – (0.009 × Fasting BG + 6.8). Results: The correlation of eA1c with reference HbA1c was r = .75, and its deviation from reference was MARD = 7.98%; 95% of all eA1c values fell within ±20% from reference. The HGI was well approximated by a linear combination of the eA1c calibration factors: HGI = 0.007552*θ1 + 0.007645*θ2 – 3.154 (P < .0001); 73% of low versus moderate-high HGIs were correctly classified by the same factors as well. Conclusions: The eA1c procedure developed in type 2 diabetes to track in real-time changes in average glycemia and present the results in HbA1c-equivalent units has shown similar performance in type 1 diabetes. The eA1c calibration factors are highly predictive of the HGI, thereby explaining partially the biological variation causing discrepancies between HbA1c and its linear estimates from SMBG data.

[1]  Sandeep Vijan,et al.  The relationship between knowledge of recent HbA1c values and diabetes care understanding and self-management. , 2005, Diabetes care.

[2]  D. Schoenfeld,et al.  Translating the A1C Assay Into Estimated Average Glucose Values , 2008, Diabetes Care.

[3]  B. Kovatchev,et al.  Effect of Automated Bio-Behavioral Feedback on the Control of Type 1 Diabetes , 2011, Diabetes Care.

[4]  P KovatchevBoris,et al.  Accuracy and Robustness of Dynamical Tracking of Average Glycemia (A1c) to Provide Real-Time Estimation of Hemoglobin A1c Using Routine Self-Monitored Blood Glucose Data , 2014 .

[5]  R. Landgraf.  The relationship of postprandial glucose to HbA1c , 2004, Diabetes/metabolism research and reviews.

[6]  E. Björk,et al.  Models for Plasma Glucose, HbA1c, and Hemoglobin Interrelationships in Patients with Type 2 Diabetes Following Tesaglitazar Treatment , 2008, Clinical pharmacology and therapeutics.

[7]  G. Treviño.  On the weighted-average relationship between plasma glucose and HbA1c. , 2006, Diabetes care.

[8]  J. Buse,et al.  The Hemoglobin Glycation Index Identifies Subpopulations With Harms or Benefits From Intensive Treatment in the ACCORD Trial , 2015, Diabetes Care.

[9]  S. Rodriguez-Segade,et al.  Translating the A1C Assay Into Estimated Average Glucose Values , 2009, Diabetes Care.

[10]  G. Treviño.  A nonlinear relation between glucose and A1c. , 2008, Diabetes research and clinical practice.

[11]  J. Delattre,et al.  A different approach to analyzing age-related HbA1c values in non-diabetic subjects , 2004, Clinical chemistry and laboratory medicine.

[12]  D. Owens,et al.  Contribution of fasting and postprandial plasma glucose to HbA1c , 2005, Diabetic medicine : a journal of the British Diabetic Association.

[13]  Robert J. McCarter,et al.  Biological Variation in HbA1c Predicts Risk of Retinopathy and Nephropathy in Type 1 Diabetes , 2004 .

[14]  H. Vesper,et al.  Assessment of the relationship between glucose and A1c using kinetic modeling. , 2006, Journal of diabetes and its complications.

[15]  B. Kovatchev,et al.  Accuracy and robustness of dynamical tracking of average glycemia (A1c) to provide real-time estimation of hemoglobin A1c using routine self-monitored blood glucose data. , 2014, Diabetes technology & therapeutics.

[16]  S. Chalew,et al.  Estimated Average Glucose and Self-Monitored Mean Blood Glucose Are Discordant Estimates of Glycemic Control , 2010, Diabetes Care.

[17]  Mahdi Kahrom,et al.  An Innovative Mathematical Model: A Key to the Riddle of HbA1c , 2010, International journal of endocrinology.