Methods: A total of 150 CKD patients and 64 non-CKD patients were enrolled. The type 2 diabetic patients in the recruited study participants were categorised based on their glycaemic control; poor glycaemic control (GC) with haemoglobin A1c (HbA1c) > 7% and good GC with HbA1c ≤ 7%. The levels or activities of GPx, SOD and sRAGE in plasma were measured. These biochemical parameters were analysed using Mann-WhitneyUtest and two-way analysis of variance (ANOVA).
Results: The activities of GPx and SOD as well as plasma level of sRAGE were not significantly different among the CKD patients with varying glycaemic control status. Irrespective of diabetes status and glycaemic control status, CKD patients also exhibited lower plasma SOD activities compared with non-CKD patients. Among the non-CKD patients, SOD activities were significantly higher in diabetic patients with good GC than diabetic patients with poor GC. Two-way ANOVA revealed that both CKD status and glycaemic control had an interaction effect on SOD activities in diabetic subjects with and without CKD. Follow-up analysis showed that SOD activities were significantly higher in non-CKD patients with good GC. There were no overall significant differences in GPx activities among the study participants. Furthermore, plasma sRAGE levels were higher in diabetic patients with CKD than those without CKD, regardless of glycaemic control status. There were no interaction effects between CKD status and glycaemic control status on GPx and sRAGE. Instead, CKD status showed significant main effects on these parameters, indicating significant differences between diabetic subjects with CKD and diabetic subjects without CKD.
Conclusion: Glycaemic control did not quantitatively alter GPx, SOD and sRAGE in diabetic CKD patients. Despite the advantages of good glycaemic control, a well-controlled diabetes in CKD did not modulate the activities of enzymatic antioxidants and sRAGE levels, therefore may not be the primary mechanism to handle oxidative stress.
METHODS: Demographic and clinical variables were assessed at baseline, after three and six months in 73 type 2 diabetes patients. Regression analysis, using SPSS, evaluated the concurrent and longitudinal association of medication adherence and glycemic control. Potential confounders of variables were identified using bi-variate correlation analyses.
RESULTS: Concurrent Medication adherence and HbA1c association were significant after adjusting for ethnicity (P = 0.005). For longitudinal observation at 3 months, the association was significant after adjusting for ethnicity (P = 0.016); however, it became non-significant when baseline glycemic control was included in the model (P = 0.28).
CONCLUSION: Easy to administer MALMAS significantly predicted concurrent glycemic control independent of potential confounders. This association persisted in longitudinal observation after 3 months when adjusted for confounders and became non-significant after adjusting for baseline glycemic control.