INTRODUCTION: Hypomagnesemia and glomerular hyperfiltration are commonly observed in patients with diabetes mellitus Type 2 (DM2). In the current study, we examined the relationship between hypomagnesemia and glomerular filtration rates in DM2 patients. MATERIALS AND METHODS: Data were obtained for DM2 patients without documented kidney disease seen at UCLAOlive View Medical Center during January through March 2001. Data for hemoglobin, hemoglobin A1C (HbA1C), routine electrolytes, lipid profiles, urinalyses, history of hypertension, and pharmacy profiles were retrieved. Estimation of glomerular filtration rate (eGFR) was based on the CKD-epi formula. Multivariate analyses were performed to determine the correlations between eGFR and clinical factors including age, gender, history of hypertension, the use of diuretics, renin angiotensin system (RAS) inhibitors, acetylsalicylic acid, and statins, serum calcium, magnesium, hemoglobin, HbA1C lipid profile, and degree of proteinuria. RESULTS: 550 patients (54% females) with mean age 57.5 ± 11.0 years and eGFR 95.7 ± 14.8 ml/min/1.73 m2 were included. Multivariate analysis revealed negative correlations with eGFR for age (Pearson-correlationcoefficient: -0.7, p < 0.0001), hypertension (-0.32, p < 0.0001), magnesium (-0.21, p < 0.0001), calcium (-0.13, p = 0.009), proteinuria (-0.17, p < 0.0001), and the use of RAS inhibitors (-0.21, p < 0.0001), and diuretics (-0.24, p < 0.0001) and a positive correlation for HbA1C (0.28, p < 0.0001). Further analysis of the interaction between serum magnesium and calcium, defined as magnesium × calcium (Mg × Ca), revealed a more significant correlation with eGFR than either cation alone (-0.24, p < 0.0001). CONCLUSIONS: Serum magnesium, calcium, and (Mg × Ca) all had significant negative correlations with eGFR. In particular, (Mg × Ca) had the strongest correlation with eGFR.
INTRODUCTION:Hypomagnesemia and glomerular hyperfiltration are commonly observed in patients with diabetes mellitus Type 2 (DM2). In the current study, we examined the relationship between hypomagnesemia and glomerular filtration rates in DM2 patients. MATERIALS AND METHODS: Data were obtained for DM2 patients without documented kidney disease seen at UCLAOlive View Medical Center during January through March 2001. Data for hemoglobin, hemoglobin A1C (HbA1C), routine electrolytes, lipid profiles, urinalyses, history of hypertension, and pharmacy profiles were retrieved. Estimation of glomerular filtration rate (eGFR) was based on the CKD-epi formula. Multivariate analyses were performed to determine the correlations between eGFR and clinical factors including age, gender, history of hypertension, the use of diuretics, renin angiotensin system (RAS) inhibitors, acetylsalicylic acid, and statins, serum calcium, magnesium, hemoglobin, HbA1C lipid profile, and degree of proteinuria. RESULTS: 550 patients (54% females) with mean age 57.5 ± 11.0 years and eGFR 95.7 ± 14.8 ml/min/1.73 m2 were included. Multivariate analysis revealed negative correlations with eGFR for age (Pearson-correlationcoefficient: -0.7, p < 0.0001), hypertension (-0.32, p < 0.0001), magnesium (-0.21, p < 0.0001), calcium (-0.13, p = 0.009), proteinuria (-0.17, p < 0.0001), and the use of RAS inhibitors (-0.21, p < 0.0001), and diuretics (-0.24, p < 0.0001) and a positive correlation for HbA1C (0.28, p < 0.0001). Further analysis of the interaction between serum magnesium and calcium, defined as magnesium × calcium (Mg × Ca), revealed a more significant correlation with eGFR than either cation alone (-0.24, p < 0.0001). CONCLUSIONS: Serum magnesium, calcium, and (Mg × Ca) all had significant negative correlations with eGFR. In particular, (Mg × Ca) had the strongest correlation with eGFR.