ABSTRACT
Liver injury caused by metoprolol is very rare with current reports limited to an isolated elevation in transaminases. We report the first case of severe icteric liver injury leading to hepatic encephalopathy secondary to metoprolol use in a patient diagnosed with coronary heart disease. We also describe the histopathology of metoprolol-related liver injury, discuss mechanisms of injury with new insights on the immunological phenomenon, and shed light on the successful utility of early plasmapheresis as a salvage therapy in metoprolol-induced severe liver damage.
ABSTRACT
OBJECTIVES: Body composition analysis is required for accurate assessment of nutritional status in patients with predialysis chronic kidney disease (CKD). The reference method for assessing body fat is dual-energy X-ray absorptiometry (DXA), but it is relatively expensive and often not available for widespread clinical use. There is only limited data on the utility of less expensive and easily available alternatives such as multifrequency bioimpedance assay (BIA) and skinfold thickness (SFT) measurements for assessing body fat in predialysis CKD. The study intends to assess the utility of BIA and SFT in measuring body fat compared to the reference method DXA in subjects with predialysis CKD. METHODS: Body composition analysis was done in 50 subjects with predialysis CKD using multifrequency BIA, SFT, and DXA. The agreement between the body fat percentages measured by reference method DXA and BIA/SFT was assessed by paired t-test, intraclass correlation coefficients (ICCs), regression, and Bland-Altman plots. RESULTS: Percentage of body fat measured by BIA was higher compared to the measurements by DXA, but the difference was not significant (30.44 ± 9.34 vs. 28.62 ± 9.00; P = .071). The ICC between DXA and BIA was 0.822 (confidence interval: 0.688, 0.899; P = .000). The mean values of body fat percentages measured by anthropometry (SFT) was considerably lower when compared to DXA (23.62 ± 8.18 vs. 28.62 ± 9.00; P = .000). The ICC between DXA and SFT was .851 (confidence interval: 0.739, 0.915; P = .000). Bland-Altman plots showed that BIA overestimated body fat by a mean of 1.8% (standard deviation, 6.98), whereas SFT underestimated body fat by 5% (standard deviation, 4.01). Regression plots showed a better agreement between SFT and DXA (R(2) = .79) than BIA (R(2) = .50). Overall, SFT showed better agreement with the DXA. Body mass index (BMI) showed a moderate positive correlation with body fat measured by DXA whereas serum albumin failed to show good correlation. CONCLUSIONS: SFT showed relatively better agreement with the reference method DXA, compared to BIA. SFT can be used as a tool for assessing nutritional status in predialysis patients with CKD.
