ArticleJournal of diabetes science and technology2015
Hemoglobin A1c and Self-Monitored Average Glucose: Validation of the Dynamical Tracking eA1c Algorithm in Type 1 Diabetes.
Article in Journal of diabetes science and technology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- GLM-DM: language model boosted neural networks for HbA1c trend prediction in diabetes mellitus.Future science OA · 2025Article
- Evaluation of HbA1c from CGM traces in an Indian population.Frontiers in endocrinology · 2023Article
- The calculated versus the measured glycosylated haemoglobin (HbAJournal of clinical laboratory analysis · 2021Article
- Estimation of Hemoglobin A1c from Continuous Glucose Monitoring Data in Individuals with Type 1 Diabetes: Is Time In Range All We Need?Diabetes technology & therapeutics · 2020Article
- 10th Annual Symposium on Self-Monitoring of Blood Glucose, April 27-29, 2017, Warsaw, Poland.Diabetes technology & therapeutics · 2018Article
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2 authors.
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Abstract
backgroundPreviously 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.
methodsReanalysis 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).
resultsThe 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.
conclusionsThe 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.
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