Evidence-Based Project on Diabetes

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Evidence-BasedProject on Diabetes


Hemoglobin A1c (A1C) can be used for various purposes suchas examining future occurrences of type 2 diabetes (Choi, Kim, Lim,Park, Jang, &amp Cho, 2011). In the sample population, an A1Cthreshold of 5.9% could pinpoint individuals with undiagnoseddisease. On the other hand, those with an A1C level over 5.6% had anincreased likelihood of developing type 2 diabetes (Choi et al.,2011). In this regard, the disease progresses independently of otherexternal factors. An analysis of the article shows the effectivenessof A1C in screening for type 2 diabetes among adults.

The cohort study used several criteria for diagnosing patients withdiabetes while evaluating the significance of A1C level duringscreening. Notably, the level of A1C also had a crucial role to playin the prediction of future bouts of disease (Choi et al., 2011). Theresearchers applied the oral glucose tolerance test (OGTT) to alladult participants. Furthermore, they utilized the same personnel andinstruments for all biochemical and clinical assessments in theduration of the study.

Previous studies had speculated on how the level of A1C could be usedin the screening for or diagnosis of diabetes. In many instances, A1Cassays are standardized. For example, the National GlycohemoglobinStandardization Program has proposed an A1C cutoff of 6.5% fordiagnosing the disease (Al-Ansary, L. et al., 2011). Reportsdeveloped by expert committees have also arrived at a similarconclusion. Current methods of screening use the concentration of 2-hglucose and FPG to diagnose diabetes after conducting an OGTT.However, the use of A1C level presents several advantages. Firstly,it has a more consistent association with diabetic microvascularcomplications than FPG concentration (Choi et al., 2011). Besides,A1C assay does not require a timed or fasting sample since it hasless preanalytic instability compared to FPG concentration. Moreover,A1C is a more reliable indicator of the level of chronic glycemia.Granted, using the A1C cutoff of 6.5% has lingering risks withregards to underdiagnosing individuals with overt diabetes (Choi etal., 2011).

Furthermore, various cross-sectional studies have attempted toexamine the accuracy of A1C level in the diagnosis of the disease.For example, one study analyzed data from the National Health andNutrition Examination Survey to show how an A1C cutoff of 5.8% hadthe highest specificity and sensitivity in highlighting undiagnoseddiabetes (Choi et al., 2011). Nonetheless, the study used FPGconcentration as the primary diagnostic test for the disease. On theother hand, the current study defined type 2 diabetes based onresults of plasma glucose. Notably, such outcomes were derived fromthe 75-g OGTT (Choi et al., 2011). Additionally, the A1C level of5.9% was deemed sufficient for diagnosing the disease among largesections of the Korean population. Contrariwise, an alternateJapanese study measured the OGTT results in almost 2,000 people todetermine the A1C cutoff of 5.6% (Choi et al., 2011). Consequently,this level was used by the Japanese Diabetes Society to identifyundiagnosed type 2 diabetes.

Granted, relatively few studies have examined the significance of A1Clevel during the prediction of new forms of the disease. In thisrespect, cohort studies in France and Japan have shown theeffectiveness of A1 cutoff in predicting type 2 diabetes (Choi etal., 2011). However, it has been less specific and sensitive comparedto FPG concentration in the screening of FPG-defined diabetes. Suchan anomaly is explained by the fact that individuals with irregular2-h glucose levels customarily manifest expected levels of FPG afterconducting an OGTT (Choi et al., 2011). The researchers used OGTT todefine the disease. Consequently, it was discovered that the A1Clevel was directly proportional to the enhanced risk of developingnew-onset diabetes. Similar results were obtained in persons withIFG at baseline levels (Choi et al., 2011). Therefore, theanticipated value of FPG concentration was less than the amount ofA1C.

Notwithstanding, the risk of contracting type 2 diabetes iscontinuous over several glycemic measures. Hence, it is quiteimpossible to outline the optimal level of A1C required for thediagnosis of the disease. In fact, the most suitable amount of A1Ccutoff should be determined with regards to both specificity andsensitivity (Tricco et al., 2012). The Youden Index specified thevalue of 5.6% during the identification of persons with an enhancedrisk of new-onset diabetes. However, it displayed less than 35% ofthe likely value (Choi et al., 2011). The researchers adopted suchparameters due to the high prevalence and incidence of diabetes.Furthermore, preventing the disease would yield plenty of benefits topatients while causing negligible harm to the healthier members ofthe population.

Inevitably, the study was hampered by several limitations. Forexample, the participants stemmed from Korean communities (Choi etal., 2011). Hence, it is highly unlikely that results from theseurban and rural groups could be applied to other populations.Moreover, the significance of racial differences in the levels of A1Ccould not be determined. Current recommendations did not consider theuse of various values of A1C based on ethnicity. Despite suchlimitations, the study proved the independence of A1C during theprediction of new-onset diabetes (Choi et al., 2011). Additionally,the researchers adopted a stringent method supplemented with thoroughfollow-up procedures to study a large community for over five years(Choi et al., 2011). Therefore, the obtained results had greatermerit compared to those from other studies.

Indeed, the researchers proved the convenience and effectiveness ofusing A1C level to screen for type 2 diabetes. In particular, thecutoff of 5.9% could identify many people with an undiagnoseddisease. Also, individuals with an A1C level greater than 5.6% wereshown to have a higher likelihood of developing new-onset diabetes(Choi et al., 2011). Consequently, it would be prudent to adoptmechanisms of early prevention.


Al-Ansary, L. et al. (2011). Point-of-care testing for HbA1c in themanagement of diabetes: a systematic review and metaanalysis.Clinical Chemistry, 57, 568-576.doi:10.1373/clinchem.2010.157586.

Choi, S. H., Kim, T. H., Lim, S., Park, K. S., Jang, H. C., &ampCho, N. H. (2011, Apr.). Hemoglobin A1c as a Diagnostic Tool forDiabetes Screening and New-Onset Diabetes Prediction. DiabetesCare, 34(4), 944-949. doi:10.2337/dc10-0644

Tricco, A. C. et al. (2012). Effectiveness of quality improvementstrategies on the management of diabetes: a systematic review andmeta-analysis. Lancet, 379, 2252-2261.doi:10.1016/S0140-6736(12)60480-2.

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