Prunus mume extract and choline treatment in patients with non-alcoholic fatty liver disease estimated by b-mode ultrasonography and hepatorenal index.

Background: The aim of this study was to find the difference between the liver function test (LFT) and hepatorenal index (HRI), before and after the administration of Prunus mume (PM) and choline i.e., to find the predictors of the non-alcoholic fatty liver disease (NAFLD) severity according its HRI, during the three-month follow-up period. Methods: LFT, glucose, and lipid tests were determined in 168 NAFLD patients, at baseline and after three-month drug treatment. HRI was calculated by Image J software analyzing the ultrasound images, and according its value, 3 groups of NAFLD were formed. Results: The HRI at baseline (1.3598±0.1744) and after 3 months therapy (1.3061±0.1923) differs significantly (p<0.0001). Plasma glucose (FPG) (p<0.0001), glycated hemoglobin (HbA1c) (P=0.002), alanine aminotransferase (ALT) (p<0.0001), aspartate aminotransferase (AST) (P=0.0006), gamma-glutamil transferase (γ-GT) (P=0.0053), high density lipoprotein cholesterol (HDL-Ch) (p<0.0001) and triglycerides (P=0.041) differ significantly, too. HRI is positively correlated with: HbA1c (P=0.035), ALT (P=0.002), AST (P=0.003), γ-GT (P=0.043), and triglycerides (P=0.002) and inversely correlated with HDL-Ch (P=0.011). In multiple regression results (standard coefficient and p-value), the independent predictors for HRI in NAFLD patients were: HbA1c (0.1443, 0.0004), ALT (0.001142, 0.0081), triglycerides (0.0431, 0.0235) and γ-GT (0.001376, 0.0329). Conclusion: Three-month administration of PM and choline have beneficial effects on the regulation of glucose and lipid metabolism (HDL-Ch), and on LFT. This plant extract significantly reduces the levels of FPG, HbA1c, ALT, AST, γ-GT, triglycerides and increases HDL-Ch. The triglycerides, ALT, γ-GT and HbA1c are positive independent predictors for the severity of NAFLD.

The Gamma Gap Predicts All-Cause Mortality in Chronic Dialysis Patients.

INTRODUCTION: The gamma gap (γ-gap) represents the total serum protein concentration minus the albumin concentration. The main aim of this study was to test whether the gamma gap is a predictor of mortality and whether it is associated with other predictors of mortality in chronic hemodialysis patients (CHPs). MATERIALS AND METHODS: We studied a cohort of 100 CHPs with a mean age of 59 ± 12.3 years with duration of dialysis 6.5 ± 4.7 years. Serum proteins were determined by electrophoresis. The association of the gamma gap with serum C-reactive protein (CRP), fibrinogen and albumin concentration was evaluated for correlation. Cox regression analysis was used to identify the predictors of mortality. RESULTS: The γ-gap correlates positively with CRP (r = 0.247, P = 0.013) and fibrinogen (r = 0.239, P = 0.016), and inversely with albumin (r = -0.430, P < 0.0001). The regression coefficients (b) and Exp (b) hazard ratio coefficients of covariates in Cox-regression survival analysis in all-cause outcomes were: b = 0.1486, Exp (b) = 1.1602 (P < 0.0001); b = 0.0655, Exp (b) = 1.0677 (P < 0.0015) and b = -0.118, Exp (b) = 0.8887 (P < 0.0009), for γ-gap, CRP and albumin, respectively. CONCLUSIONS: In patients on chronic hemodialysis, the gamma gap, along with serum albumin and CRP levels, is an independent predictor of mortality. Gamma gap levels correlate directly with serum CRP and fibrinogen levels and inversely with serum albumin levels.

The predictive value of the hepatorenal index for detection of impaired glucose metabolism in patients with non-alcoholic fatty liver disease.

BACKGROUND/PURPOSE: Non-alcoholic fatty liver disease (NAFLD) patients are at increased risk of liver-related as well as cardiovascular mortality, including diabetes, coronary heart disease, and stroke, independently of traditional cardiovascular risk factors and metabolic syndrome. The aim of this study was to find out the predictive impact of hepatorenal index (HRI) in the detection of impaired glucose metabolism in asymptomatic NAFLD patients. METHODS: B-mode ultrasound examinations were performed and ultrasound images from all 89 NAFLD patients aged 50.8 ± 10.1 years were analyzed by echogenicity analyzing software and HRI was acquired, and appropriate laboratory tests for liver, glucose, and lipid metabolism were undertaken. RESULTS: The mean HRI was 1.345 ± 0.189. 23.59% of patients had mild NAFLD (HRI = 1.167 ± 0.041), 64.04% moderate (HRI = 1.401 ± 0.102), and 12.36% patients severe NAFLD (HRI = 1.802 ± 0.098). Impaired glucose metabolism was present in 48.31% of patients. A positive correlation was present between HRI and impaired glucose metabolism (r = 0.335, p = 0.001). The coefficients of determinations R2 for linear regression for HRI and glycated hemoglobin (HbA1c) and oral glucose tolerance test (GTT) were 0.05841 and 0.07498, respectively. The cutoff values for HRI in the detection of diabetes and prediabetes, and prediabetes only, were 1.4 and 1.38, respectively. In logistic regression, the ß coefficients for oral GTT, HbA1c, or HRI were 0.62042 (p = 0.0002), 2.18036 (p = 0.0033), and 2.36986 (p = 0.012). The hazard ratio (HR) coefficients (exp [b]) for HRI, HbA1c, and oral GTT sorted according to their HR strength were 10.6958, 8.8494, and 1.8597, respectively. CONCLUSION: Ultrasonographically acquired HRI has a significant predictive impact on the detection of prediabetes and diabetes in patients with NAFLD.

Acute-phase proteins as promoters of abdominal aortic calcification in chronic dialysis patients.

The aim of this study was to find a correlation between acute-phase proteins (APPs) and abdominal aortic calcification (AAC) as well as the impact APPs on AAC in chronic dialysis patients (CDPs). Native lateral lumbar radiography and biochemical analysis were performed in 112 CDPs (aged 60.0 ± 5.43 years) to estimate and score AAC and biochemical values of APPs. The mean AAC score was 8.39 ± 5.43. We detected 16 (14.28%) CDPs without AAC and 96 (85.71%) CDPs with AAC (10 ± 5.43). The number of CDPs with AAC ≤4 was 34 (30.36%) with mean AAC score of 1.85 ± 1.94. By multiple regression analysis, we found positive correlation between AAC and ferritin (ß = 0.004398, P = 0.0085) and AAC and C-reactive protein [(CRP), ß = 0.1972, P = 0.0178]. Sensitivity/specificity pairs and criterion variables (CrVs) were as follows: for CRP: 44.21%, 100%, and CrV ≥6 and for ferritin: 83.16%, 56.25%, and CrV ≥196.32. The area under curve (AUC) for CRP and ferritin was 0.721 (P <0.0001) and 0.730 (P <0.0026), respectively. Fibrinogen and serum iron AUC in the prediction of AAC were 0.533 (P = 0.5749) and 0.618 (P = 0.0795), respectively. CRP and ferritin were the most powerful APPs involved in the promotion of AAC; serum iron and fibrinogen were shown as lower activity promoters in CDPs. Serum albumin showed inverse activity on AAC.

B - Flow assessment of femoral artery as predictor of coronary artery disease in patients evaluated for chest pain by radionuclide myocardial perfusion scintigraphy.

In the evaluation of patients with suspected coronary artery disease (CAD), the presence of the superficial femoral artery (SFA) plaque is more informative than a carotid plaque and at least as informative as coronary plaque in the identification of coronary death individuals. In 60 patients with chest pain with a normal electrocardiogram, B-flow ultrasound estimation of SFA plaque and radionuclide myocardial perfusion scintigraphy (MPS) estimation for CAD was performed. We found significant positive correlations between age and SFA plaque score (PS) (P = 0.0084), myocardial ischemia in rest and SFA PS (P < 0.0001), and between transient ischemic dilation (TID) and SFA PS (P = 0.0069), too. The TID correlates only with myocardial ischemia in rest (P = 0.0022) and SFA PS (P = 0.0069). The results we got by the receiver operating characteristics (ROC) curve analysis with TID/without TID were the area under curve (0.704, P = 0.0038). The multiple regression analysis showed standardized coefficient ß coefficients for SFA PS and TID (3.4577 and 1.9903, P < 0.001 and P = 0.0021), respectively. By proven correlative relationship of SFA atherosclerotic plaques and CAD, we can use B-flow as a screening method for triage of patients with chest pain before being sent to the assessment of coronary circulation with radionuclide MPS.

Accelerated progression of arterial stiffness in dialysis patients compared with the general population.

BACKGROUND/AIMS: The aim of this study was to compare the progression of aortic stiffness in chronic hemodialysis patients (CHP) with that of general population patients (GPP) over a 36-month period and to evaluate the determinants of this progression. METHODS: The study group included 80 patients undergoing hemodialysis (aged 59.3 ± 11.8 years; duration of dialysis 5.47 ± 5.16 years). The control group consisted of 60 patients (aged 57.5 ± 10.9 years) with a glomerular filtration rate of > 60 mL/min/1.73 m(2). Pulse wave velocity (PWV) was determined from time diversity propagation of the common carotid artery and femoral artery by Doppler ultrasound. Clinical and biochemical parameters were determined in serum using standard laboratory procedures. RESULTS: The mean PWV values at baseline and 36 months were 11.18 ± 2.29 and 11.82 ± 2.34 m/sec in the CHP group, and 9.02 ± 1.89 and 9.29 ± 1.93 m/sec in the GPP group, respectively. The average PWV progressions were 63.95 ± 18.373 cm/sec in CHP and 27.28 ± 28.519 cm/sec in GPP. By multiple regression analysis, hemoglobin (standardized coefficient ß [ßst] = -0.405, p = 0.004; ßst = -0.364, p = 0.011), albumin (ßst = -0.349, p = 0.042; ßst = -0.303, p = 0.034), CRP (ßst = 0.458, p = 0.002; ßst = 0.187, p = 0.008), and total cholesterol (ßst = 0.236, p = 0.038; ßst = 0.171, p = 0.078) were independently associated with PWV in the CHP and GPP groups, respectively. CONCLUSIONS: Accelerated arterial stiffness was more pronounced in the CHP group than in the GPP group. The independent determinants of this progression in both groups include traditional risk factors and blood levels of hemoglobin, albumin and CRP. Cholesterol and uremia-related factors are determinants only in CHP.