Effects of fibrates on C-reactive protein concentrations: a meta-analysis of randomized controlled trials

Author(s):  
Yongchen Hao ◽  
Huan Zhang ◽  
Xueli Yang ◽  
Lu Wang ◽  
Dongfeng Gu

AbstractThe effects of fibrates on C-reactive protein (CRP) are controversial. This meta-analysis was conducted to synthesize the available clinical trial evidence and summarize the effects of fibrates on CRP concentrations. In addition, this study assessed the relationship between changes in CRP and lipid measures.A systematic search was conducted of randomized controlled trials on the effects of fibrates on CRP concentrations in the PubMed, Embase and Cochrane Library Database up to January 2011. A meta-analysis was performed using a random effect model. Meta-regression analysis was employed to assess the relationships between average change in CRP and lipid profiles.Sixteen randomized controlled trials were included in the meta-analysis. Compared with placebo, treatment with fibrates significantly decreased CRP concentrations (weighted mean difference –0.47 mg/L, 95% confidence interval –0.93 to –0.01 mg/L, p=0.046). Fibrates significantly reduced CRP concentrations in trials with a higher baseline CRP concentrations (≥3 mg/L). There was a significant correlation between change in CRP and change in high-density lipoprotein cholesterol (regression coefficient or slope=–2.03, 95% CI –3.20 to –0.87, p=0.001).Fibrates can reduce CRP concentrations and change in CRP was correlated with change in high-density lipoprotein cholesterol but not with triglyceride. These findings suggest that patients with dyslipidemia could benefit from fibrates treatment by CRP lowering and this benefit is associated with lipid profile improving.

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
George A Kelley ◽  
Kristi S Kelley

BACKGROUND AND PURPOSE: Non-high-density lipoprotein cholesterol (non-HDL-C) is associated with an increased risk for cerebrovascular disease. However, the effects of three community-deliverable lifestyle interventions [diet (D), aerobic exercise (E), or both (DE)] on non-HDL-C in adults are not known. The purpose of this study was to use the aggregate data meta-analytic approach to address this gap. METHODS: A priori study eligibility included randomized controlled trials >4 weeks that included a D, E, DE and control (C) group in adults >18 years of age in which data for total cholesterol (TC) and high-density lipoprotein cholesterol (HDL-C) were available for calculating non-HDL-C. Studies were retrieved by searching nine electronic databases, cross-referencing and expert review. Dual data selection and extraction were conducted. A mixed effects model was employed whereby a random-effects approach was used to combine effect size (ES) results within each subgroup while a fixed-effect approach was used to compare subgroups (Q b ). Heterogeneity was examined using the Q and I 2 statistics and 95% confidence intervals (CI) were also calculated. Statistical significance was set at p < 0.05 while a trend for statistical significance was set between p >0.05 to < 0.10. RESULTS: Overall, a statistically significant exercise minus control group decrease in non-HDL-C was found for DE (7 ESs, 389 participants, mean, -11.1 mg/dl, 95% CI, -21.7 to -0.6, p =0.04, Q=2.4, p =0.88, I 2 =0%), a trend for the D group (7 ESs, 402 participants, mean, -8.5 mg/dl, 95% CI, -18.6 to 1.6, p =0.10, Q=0.76, p =0.99, I 2 =0%) and no change for the E group (7 ESs, 387 participants, mean, 3.0 mg/dl, 95% CI, -7.1 to 13.1, p =0.56, Q=0.78, p =0.99, I 2 =0%). Relative changes were -6.5%, -5.6%, and 0.8% respectively, for DE, D and E groups. Overall, no statistically significant between-group differences were found (Q b = 4.1, p = 0.12). There was a trend for decreases in non-HDL-C to be greater in the DE versus E group (Q b = 3.6, p = 0.06) with no statistically significant differences between D and E (Q b = 2.5, p = 0.12) or DE and D (Q b = 0.1, p = 0.72) groups. CONCLUSIONS: Combined DE reduces non-HDL-C in adults.


2018 ◽  
Vol 21 ◽  
pp. 222-235 ◽  
Author(s):  
Boyu Li ◽  
Ying Wang ◽  
Zhikang Ye ◽  
Hui Yang ◽  
Xiangli Cui ◽  
...  

PURPOSE: Non-alcoholic fatty liver disease (NAFLD) affects about 75% of patients with type 2 diabetes mellitus (T2DM). We conducted a meta-analysis to determine the effect of canagliflozin on fatty liver indexes in T2DM patients. METHODS: A literature search of PubMed, Embase and Cochrane was conducted up to March 30, 2017. The liver function test and lipid profile were extracted from randomized controlled trials (RCTs) to evaluate the effect of canagliflozin on fatty liver. Weighted mean differences (WMDs) or relative risks and 95% confidence intervals (CIs) were computed by using either fixed or random-effects models. Sensitivity analysis and publication bias were evaluated. RESULTS: Our results showed that canagliflozin decreased serum concentrations of  alanine amino transferase (WMD: -11.68 [95% CI: -18.95, -10.95]; P<0.001), aspartate amino transferase (WMD: -7.50 [95% CI: -10.61, -4.38]; P<0.001), gamma-glutamyl transferase (WMD: -15.17 [95% CI: -17.73, -12.61]; P<0.001), triglycerides (WMD: -0.10 [95% CI: -0.15, -0.05]; P<0.001) but increased low-density lipoprotein cholesterol (WMD: 0.1 [95% CI: 0.06, 0.13]; P<0.001), high-density lipoprotein cholesterol (WMD: 0.06 [95% CI: 0.05, 0.07]; P<0.001) at week 26 or 52. CONCLUSIONS: Our results indicated that canagliflozin may have a protective effect on fatty liver in T2DM patients. The limitation was that the liver biopsy was hard to obtain in published studies. More RCTs specified on NAFLD are needed to get further information. This article is open to POST-PUBLICATION REVIEW. Registered readers (see “For Readers”) may comment by clicking on ABSTRACT on the issue’s contents page.


2005 ◽  
Vol 62 (11) ◽  
pp. 811-819
Author(s):  
Aleksandra Jovelic ◽  
Goran Radjen ◽  
Stojan Jovelic ◽  
Marica Markovic

Background/Aim. C-reactive protein is an independent predictor of the risk of cardiovascular events and diabetes mellitus in apparently healthy men. The relationship between C-reactive protein and the features of metabolic syndrome has not been fully elucidated. To assess the cross-sectional relationship between C-reactive protein and the features of metabolic syndrome in healthy people. Methods. We studied 161 military pilots (agee, 40?6 years) free of cardiovascular disease, diabetes mellitus and active inflammation on their regular annual medical control. Age, total cholesterol, low density lipoprotein cholesterol, high density lipoprotein cholesterol, triglycerides, fasting glucose, glycosylated hemoglobin, blood pressure, smoking habit, waist circumference and body mass index were evaluated. Plasma C-reactive protein was measured by the immunonephelometry (Dade Behring) method. Metabolic syndrome was defined according to the National Cholesterol Education Program Expert Panel. Results. The mean C-reactive protein concentrations in the subjects grouped according to the presence of 0, 1, 2 and 3 or more features of the metabolic syndrome were 1.11, 1.89, 1.72 and 2.22 mg/L, respectively (p = 0.023) with a statistically, significant difference between those with 3, and without metabolic syndrome (p = 0.01). In the simple regression analyses C-reactive protein did not correlate with the total cholesterol, low density lipoprotein cholesterol, high density lipoprotein cholesterol, body mass index and blood pressure (p > 0.05). In the multiple regression analysis, waist circumference (? = 0.411, p = 0.000), triglycerides to high density lipoprotein cholesterol ratio (? = 0.774, p = 0.000), smoking habit (? = 0.236, p = 0.003) and triglycerides (? = 0.471, p = 0.027) were independent predictors of C-reactive protein. Conclusions. Our results suggested a cross-sectional independent correlation between the examined cardiovascular risk factors as the predominant features of metabolic syndrome and C-reactive protein in the group of apparently healthy subjects. The lack of correlation of C-reactive protein with the total cholesterol and low density lipoprotein cholesterol in our study may suggest their different role in the process of atherosclerosis and the possibility to determine C-reactive protein in order to identify high-risk subjects not identified with cholesterol screening.


Nutrients ◽  
2015 ◽  
Vol 7 (2) ◽  
pp. 1131-1143 ◽  
Author(s):  
Ling-Mei Zhou ◽  
Jia-Ying Xu ◽  
Chun-Ping Rao ◽  
Shufen Han ◽  
Zhongxiao Wan ◽  
...  

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