Metabolic syndrome and abdominal fat are associated with inflammation, but not with clinical outcomes, in peritoneal dialysis patients

In February 2009, patients aged >20 years who had undergone maintenance PD for more than 3 months were enrolled. Pregnant women and patients who had undergone CT scanning during the previous 6 months were excluded. After providing informed consent, each patient underwent a non-contrast abdominal CT, and a blood sample was obtained to measure biomarkers. Patients fasted for 6 hours prior to phlebotomy. The blood samples were immediately centrifuged at 3,000 rpm and 4°C, and the resulting plasma samples were frozen at −80°C until analysis.

The imaging of each subject was performed on a 64-MDCT scanner (LightSpeed VCT; GE Healthcare, Milwaukee, WI), and the umbilicus cut was analyzed for VFA [23]. Image analysis software (ImageJ, version 1.45; National Institutes of Health, Bethesda, MD) was used at an attenuation range of −50 to −250 Hounsfield units to quantify abdominal adipose tissue areas in cm². The subcutaneous fat area (SFA) was clearly visible and defined as the extraperitoneal fat between skin and muscle. Intra-abdominal tissue at the same density as SFA was defined as VFA. The total fat area (TFA) was the sum of SFA and VFA. The images were reviewed by radiologists who were blinded to the clinical characteristics of the PD patients. The 3 indicators of fat area were corrected for BMI (cm²/[kg/m²]) because fat area relates to body mass [8].

Clinical and dialysis data of PD patients were recorded and included medication (RAS blockers, beta blockers, or statin), results of PD-associated peritoneal equilibration test (PET), dialysis Kt/V, residual renal function, and normalized protein catabolic rate (nPCR). Routine biochemical studies were also recorded and included urea nitrogen, creatinine, albumin, hemoglobin, CRP, lipid profile, total cholesterol (CHO), triglyceride (TG), high-density lipoprotein (HDL), and low-density lipoprotein (LDL).

Two atherogenic indices (AIs) were derived from the lipid profile, according to the following equations: AI1 = log (TG/HDL) [24] and AI2 = non-HDL cholesterol/HDL = (T-CHO-HDL)/HDL [8].

The dialysate prescribed to each PD patient during 2009 was also recorded and used to calculate the glucose load in these patients, as previously described [12‐14]. Glucose load 1 represents the average glucose concentration in the total PD fluid, including extraneal and nutrineal. Glucose load 2 represents the average glucose concentration of the glucose-containing dialysate only.

After they had undergone an abdominal CT, patients were monitored for the following events: hospitalization, peritonitis, technique failure, cardiovascular disease (CVD), and mortality. Cardiac disease, cerebrovascular disease, and severe ischemic events were categorized as CVD. Patients who received transplants were censored in technique survival and mortality. Transplant admissions were not considered episodes of hospitalization. Follow-up was continued until February 2012.

MetS was diagnosed according to the definition in the National Cholesterol Education Program Adult Treatment Panel III [25], which requires fulfillment of at least 3 of the following criteria: abnormal waist circumference, TG >150 mg/dL, HDL < 40 mg/dL in men or < 50 mg/dL in women, blood pressure >130/85 mmHg or active treatment with antihypertensive agents, and fasting blood glucose >100 mg/dL. Because waist measurements are inaccurate in PD patients, we substituted BMI >25 kg/m² for this value, as has been done in other studies [17].

All continuous variables are reported as mean ± SD (with 95% confidence intervals as appropriate), and all categorical variables are reported as frequencies or percentages. Comparison between groups was done using the student t-test, non-parametric test, or one-way analysis of variance (ANOVA). The differences in frequency were tested by χ² analysis. The relationships between variables were tested by Pearson’s correlation. The independent determinants of a variable were determined by multiple linear regression analysis. The adjusted variables were stated for each analysis. Peritonitis incidence in PD patients was compared by Poisson analysis. Kaplan-Meier survival analysis was used to compare survival between groups. P values < 0.05 were considered significant. Statistical analyses were conducted using SPSS 13.0 for Windows (SPSS Inc., IL USA).

A total of 183 PD patients were enrolled in this study. There were 146 patients without DM who were further classified as non-MetS (n = 73, group 1) or MetS (n = 65, group 2). The remaining patients were classified as DM (n = 45, group 3), including 5 patients met the criteria for DM after they had begun PD. Besides differing in the criteria met for MetS, patients in group 2 also had higher levels of albumin and CRP, higher AI1 and AI2, more abdominal fat indicators, and lower levels of D/P creatinine and nPCR than patients in group 1 (Table 1). DM patients (group 3) had more significant histories of coronary artery disease (CAD), older ages, higher BMIs, higher glucose loads, increased AI1 and AI2, and more abdominal fat than patients in group 1. The PD duration in the DM patients was the shortest and the nPCR was the lowest of the 3 groups. These results indicate that MetS patients are similar to DM patients in that they have higher AIs and CRP levels, and more abdominal fat, but MetS patients have less significant CAD histories.

Because DM significantly influences lipid and carbohydrate metabolism and fat distribution, we analyzed the correlation between VFA and other variables in the groups. Because CRP was not evenly distributed, we log-transformed the CRP data for analysis. We applied the Pearson’s correlation to define the relationship between CRP levels and fat components. In non-DM patients, CRP levels had a significant positive correlation with VFA (r = 0.396, P < 0.001; Figure 1A), SFA (r = 0.431, P < 0.001; Figure 1B), and TFA (r = 0.476, P < 0.001; Figure 1C). Otherwise, fat area correlated proportionally with age, body weight (BW), CHO, TG, AIs, and fasting glucose (Table 2). These abdominal fat parameters were inversely correlated with peritoneal KT/V, creatinine, and nPCR. The cardiothoracic ratio, which is inversely related to heart function, also had a positive correlation with abdominal fat. The use of RAS blockers had a negative correlation with abdominal fat, whereas the use of beta blockers had a positive one (Table 2). In general, the correlations were similar in DM patients, except that CRP level and type of antihypertensive medication had no correlations with abdominal fat.

In addition, we used multiple linear regression analysis to determine independent predictors, after adjusting for age, sex, and BW. In non-DM patients, creatinine associated negatively with all fat area indicators (Table 3A). CRP levels were associated positively with VFA and TFA. The use of RAS blockers negatively predicted VFA, whereas the use of beta blockers associated positively with SFA. Both types of medications correlated with TFA. In DM patients, the fat area was associated only with age, sex, and lipid parameters (Table 3B).

Since fat area correlated with lipid and glucose metabolism, both of which reflect metabolic dysfunction, we analyzed the fat area in all PD patients without DM and categorized the patients into 6 groups based on the number of criteria they met for MetS. Four patients did not meet any criteria of MetS, 35 fulfilled 1 criterion, 39 fulfilled 2 criteria, 45 fulfilled 3 criteria, 44 fulfilled 4 criteria, and 16 fulfilled all 5 MetS criteria. VFA, SFA, and TFA increased as the number of criteria met increased (Figure 2; P < 0.001 by ANOVA).

PD patients without DM were analyzed further for each criterion of MetS fulfilled by comparing VFA, CRP, PD dialysate glucose load, annual glucose exposure, CAD history, and CVD comorbidity. CRP levels were higher in patients who fulfilled any single criterion except for hypertension (Table 4). PD glucose load and exposure were similar for each criterion. Finally, none of the criteria for MetS resulted in significant differences in heart size, CAD history, or follow-up CVD events.

The Kaplan-Meier survival analysis was used to compare survival among non-MetS, MetS, and DM patients. Patients with DM had the shortest survival, but MetS did not have an effect on survival outcome (Figure 2).