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Global health
SP4-11 Metabolic profile influence on HBA1C in diagnosing diabetes mellitus
  1. T Dzebisashvili
  1. Moscow Regional Research Clinical Institute named by M.F.Vladimirskiy, Moscow, Russia


Aims To evaluate the optimum HbA1c cut-off for lowing number of people with undiagnosed type 2 diabetes mellitus (T2DM).

Materiales and Methods Population-based screening for glucose metabolism impairments (GMI) among 661 adults in Moscow Country was conducted in 2009. HbA1c was determined in 39 subjects with GMI. T2DM was diagnosed according to WHO 1999 criteria. Receiver operating characteristics (ROC) analysis was performed to assess best predictive cut-off HbA1c for diagnosing T2DM.

Results Based on OGTT and HbA1c, 15% and 28% people had T2DM. Area under ROC curve (AUROC) was 0,727 (95% CI 0.490 to 0.964, p=0.080, sensitivity 66.7%, specificity 78.8%) using HbA1c cut-off >6.5%. Best predictive HbA1c in this cohort was 6.3% (AUROC 0.750, p=0.054, sensitivity 83%, specificity 67%). 33.0% of undiagnosed T2DM had HbA1c levels <6.5% (95% CI 0% to 71%) and 17% (95% Cl 0% to 45%) of people with T2DM had HbA1c levels <6.3%. Subjects with false negative HbA1c were predominantly with normal BMI (21.8+1.6 vs 42.9+7.8, p=0.025), false positives were predominantly with higher BMI (30.6+7.8 vs 28.4+5.9, p=0.273). In normal weight (BMI 18–25) individuals optimal HbA1c cut-point for detecting T2DM was >6.0% (AUROC 0.750, sensitivity 50%, specificity 100%). RR of T2DM was 7 (1.18–42.9) with HbA1c values 6.0–6.4%, than those with <6.0 in normal weight individuals.

Conclusion Choosing the HbA1c strategy rather than the OGTT strategy leads to diagnose more diabetes, although the consistency of both diagnostic criteria is low. The optimal HbA1c cut-point to detect T2DM was lower than HbA1c of 6.5% in normal weight individuals.

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