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Glycated hemoglobin (HbA1c) levels are commonly used to indicate long-term glycemic control. An HbA1c level of 6.5–5.7% is defined as pre-diabetes and is proposed as a criterion for diagnosing metabolic syndrome (MetS). However, HbA1c levels can be affected by chronic kidney disease (CKD). Whether HbA1c is associated with clinical outcomes in nondiabetic CKD patients with or without MetS is still unknown. This study included 1270 nondiabetic CKD stage 1–4 Asian patients, divided by HbA1c and MetS. Through linear regression, HbA1c was positively associated with age, waist circumference, hemoglobin levels, and C-reactive protein and was negatively associated with malnutrition–inflammation. HbA1c levels were 5.5% (0.6%) and 5.7% (0.6%) in non-MetS and MetS, respectively (p < 0.001). In Cox regression, higher-level HbA1c was associated with worse composite renal outcome in MetS patients, but with better renal outcome in non-MetS patients: Hazard ratio (HR) (95% confidence interval [CI]) of HbA1c ≥5.7%, compared with HbA1c <5%, was 2.00 (1.06–3.78) in MetS and 0.25 (0.14–0.45) in non-MetS. An association between HbA1c and all-cause mortality was not found. In conclusion, higher HbA1c levels are associated with worse renal outcomes in nondiabetic CKD stage 1–4 patients modified by the presence of MetS. [ABSTRACT FROM AUTHOR]

Obesity-related nephropathy is associated with renal function progression. However, some studies have associated a high body mass index (BMI) with improved renal outcomes—this is referred to as the obesity paradox for renal outcomes, especially in relation to advanced chronic kidney disease (CKD). Central obesity can explain the obesity paradox in all-cause mortality. However, whether obesity or central obesity is associated with renal outcomes (renal replacement therapy or a 50% decline in the estimated glomerular filtration rate) in patients with advanced CKD remains unclear. Our study included 3605 Asian patients with CKD stages 1–5 divided into six groups according to their BMI (between 15 and 35 kg/m2). Through linear regression, BMI was positively associated with hemoglobin and albumin at CKD stages 4 and 5. In the competing risk Cox regression model, a high BMI (27.5–35 kg/m2) was associated with renal outcomes at CKD stages 1–3, but not stages 4 and 5. A high BMI was associated with renal outcomes in patients with hemoglobin ≥11 g/dL, but not <11 g/dL. A high waist-to-hip ratio was not associated with renal outcomes. We conclude that the CKD stage and anemia may explain the obesity paradox in renal outcomes in patients with CKD. [ABSTRACT FROM AUTHOR]

A common complication of chronic kidney disease (CKD), anemia can influence glycated hemoglobin (HbA1c) levels. In diabetic patients, anemia occurs earlier and with higher severity over the course of CKD stages. To elucidate the effect of hemoglobin (Hb) on the predictive value of HbA1c, we enrolled 1558 diabetic patients with stages 3–4 CKD, categorized according to baseline Hb and HbA1c quartiles. Linear regression revealed that higher HbA1c correlated significantly with higher Hb in the Hb < 10 g/dL group (β = 0.146, P = 0.004). A fully-adjusted Cox regression model revealed worse clinical outcomes in patients with higher HbA1c quartiles in the Hb ≥ 10 g/dL group. Hazard ratios for end-stage renal disease (ESRD), all-cause mortality, and composite endpoint (cardiovascular events and all-cause mortality) in patients with Hb ≥ 10 g/dL and the highest HbA1c quartile were 1.92 (95% confidence interval [CI], 1.17–3.15), 1.76 (95% CI, 1.02–3.03), and 1.54 (95% CI, 1.03–2.31), respectively. By contrast, HbA1c was not associated with clinical outcomes in the Hb < 10 g/dL group. In conclusion, in stages 3–4 diabetic CKD, higher HbA1c is associated with a higher risk of poor clinical outcomes in patients with Hb ≥ 10 g/dL. [ABSTRACT FROM AUTHOR]

Background: Fluid overload is not only the characteristic but also an important complication in chronic kidney disease (CKD) patients. Angiopoietin-2 (Angpt2) disturbs endothelium and vessel permeability, which may induce fluid overload. The aim of this study is to examine the interaction between fluid status and Angpt2 in adverse renal outcomes of CKD. Methods: This cohort study enrolled 290 patients with CKD stages 3–5 from January 2011 to December 2011 and followed up until December 2015. Fluid status was presented as overhydration (OH) value measured by body composition monitor, while OH>1.1L was defined as fluid overload. Renal outcomes were defined as commencing dialysis and rapid renal function decline (the slope of estimated glomerular filtration rate < -5 ml/min/1.73 m2/y). Results: During a mean follow-up of 38.6±18.3 months, 125 (43.1%) patients progressed to commencing dialysis and 99(34.7%) patients presented rapid renal function decline. All patients were stratified by OH of 1.1L and the median of circulating Angpt2. These patients with both OH>1.1L and high circulating Angpt2 were more likely to reach commencing dialysis compared to other groups. The risks for commencing dialysis and rapid renal function decline were significantly higher in patients with OH>1.1L and high circulating Angpt2 level compared to those with OH≦1.1L and low circulating Angpt2 (2.14, 1.21–3.78, P = 0.009; 4.96, 1.45–16.97, P = 0.01). There was a significant interaction between OH level and circulating Angpt2 in entering dialysis (P-interaction = 0.02). Conclusions: Fluid overload and Angpt2 might have a synergistic effect on adverse renal outcomes in CKD patients. [ABSTRACT FROM AUTHOR]

BACKGROUND Systolic blood pressure (SBP) goal for chronic kidney disease (CKD) patients is ≤140mm Hg. However, the SBP target provides no suggested lower limit, and some studies indicate that a lower SBP target may be harmful. We aimed to investigate the J-shaped relationship between SBP and clinical outcomes in CKD patients and the factors that modify this relationship. METHODS This prospective observational study enrolled 2,144 CKD stage 3–4 patients between November 2002 and May 2009 and followed them until July 2010 or death. Patients included were also enrolled within the Integrated CKD Care Program for Delaying Dialysis in a medical center and its branch hospital. Demographic, clinical, laboratory, and disease variables at baseline and end of observation were measured. RESULTS In diabetic CKD patients, the hazard ratio (HR) at SBP 96–110mm Hg vs. 111–120mm Hg was 2.52 (95% confidence interval (CI) = 1.13–5.58) for cardiovascular outcomes and was 3.14 (95% CI = 1.16–8.49) for renal outcomes. In nondiabetic CKD patients, this J-shaped relationship was not seen. Heavy proteinuria was further found to modify the J-shaped relationship in diabetic CKD patients. The HR for renal outcomes at SBP 96–110mm Hg vs. 111–120mm Hg was 4.07 (95% CI = 1.18–13.99) in diabetic CKD patients with heavy proteinuria vs. 1.72 (95% CI = 0.13–22.5) in those without heavy proteinuria. CONCLUSIONS Diabetic CKD patients have a J-shaped relationship between SBP and cardiovascular or renal outcomes, but nondiabetic CKD patients do not. The optimal SBP range might be narrower in the diabetic CKD patients. [ABSTRACT FROM AUTHOR]

Background: Chronic kidney disease (CKD) and hepatitis C virus (HCV) infection are closely linked and both increase patient mortality. The association of HCV and risk of developing end-stage renal disease (ESRD) has not been analyzed with competing risk model. Method: We enrolled a prospective cohort of 4,185 patients (mean age, 62 years; 41% female) registered in the CKD integrated care program at two affiliated hospitals of Kaohsiung Medical University in Taiwan between November 11, 2002 and May 31, 2009. With competing risk model, we analyzed the association of HCV infection, defined by seropositive of anti-HCV antibody, and hepatitis B virus (HBV) infection, defined by seropositive of HBV surface antigen, with the risk of entering ESRD. Results: The prevalence of HCV infection was 7.6% and it increased with the CKD stages (trend test, P<0.001), while the prevalence of HBV infection was 7.4% and no specific trend among CKD stages (tend test, P = 0.1). During the 9,101 person-year follow-up period, there were 446 death and 1,205 patients entering ESRD. After adjusting death as the competing risk, the estimated 5-year cumulative incidence rate of ESRD among patients with and without HCV infection were 52.6% and 38.4%, respectively (modified log-rank, P<0.001). Multivariable analysis showed that HCV infection, but not HBV infection, had higher risk of developing ESRD compared with cases without infection (HCV, HR: 1.32, 95% CI: 1.07–1.62; HBV, HR: 1.10, 95% CI: 0.89–1.35). Subgroup analyses showed consistent results. Conclusions: With death-adjusted competing risk analysis, HCV infection is associated with an increased risk of developing ESRD in CKD cohort. [ABSTRACT FROM AUTHOR]

Dyslipidemia is highly prevalent in patients with chronic kidney disease (CKD) and the relationship between dyslipidemia with renal outcomes in patients with moderate to advanced CKD remains controversial. Hence, our objective is to determine whether dyslipidemia is independently associated with rapid renal progression and progression to renal replacement therapy (RRT) in CKD patients. The study analyzed the association between lipid profile, RRT, and rapid renal progression (estimated glomerular filtration rate [eGFR] slope <−6 ml/min/1.73 m2/yr) in 3303 patients with stages 3 to 5 CKD. During a median 2.8-year follow-up, 1080 (32.3%) participants commenced RRT and 841 (25.5%) had rapid renal progression. In the adjusted models, the lowest quintile (hazard ratios [HR], 1.23; 95% confidence interval [CI], 1.01 to 1.49) and the highest two quintiles of total cholesterol (HR, 1.25; 95% CI, 1.02 to 1.52 and HR, 1.35; 95% CI, 1.11 to 1.65 respectively) increased risks for RRT (vs. quintile 2). Besides, the highest quintile of total cholesterol was independently associated with rapid renal progression (odds ratio, 1.36; 95% CI, 1.01 to 1.83). Our study demonstrated that certain levels of dyslipidemia were independently associated with RRT and rapid renal progression in CKD stage 3–5. Assessment of lipid profile may help identify high risk groups with adverse renal outcomes. [ABSTRACT FROM AUTHOR]