PLoS ONE (Jan 2024)

Prevalence of poor glycemic control and the monitoring utility of glycated albumin among diabetic patients attending clinic in tertiary hospitals in Dodoma, Tanzania: A cross-sectional study protocol.

  • George Gabriel Mkumbi,
  • Matobogolo Boaz

DOI
https://doi.org/10.1371/journal.pone.0289388
Journal volume & issue
Vol. 19, no. 9
p. e0289388

Abstract

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The burden of diabetes is rising in developing countries, and this is significantly linked to the increasing prevalence of poor glycemic control. The cost of glycated haemoglobin (HbA1c) testing is a barrier to timely glycemic assessments, but newer tests such as glycated albumin may be cheaper and tempting alternatives. Additional research must ascertain if glycated albumin (GA) can act as a viable supplement or alternative to conventional HbA1c measurements for glycemic control in diabetic individuals. GA as a biomarker is an emerging area of interest, particularly for those who display unreliable HbA1c levels or cannot afford the test. This study aims to investigate the prevalence of poor glycemic control in outpatient diabetic patients and the utility of glycated albumin in this population's monitoring of glycemic control. Method. A cross-sectional study of 203 diabetic patients will be conducted at the Dodoma Regional Referral Hospital and Benjamin Mkapa Hospital from August 1st, 2023, to August 31st, 2024. Patients diagnosed with diabetes mellitus for over six months will be screened for eligibility. Informed consent, history, clinical examination, and voluntary blood sample collection will be obtained from all eligible patients. Glycated Albumin levels will be obtained from the same blood samples collected. The glycemic status of all patients will be defined as per HbA1c, and a level of greater than 7% will considered as a poor control. The analysis will be computed with SPSS version 28.0, and a predictor variable, P<0.05, will be regarded as statistically significant, with the utility of GA determined by plotting the area under the ROC curve and the confusion matrix.