Although the prevalence of obesity and metabolic syndrome (MetS) among dialysis patients has been exceeding than general population, little is known regarding obesity and MetS in non-dialysis chronic kidney disease (CKD). We aimed to find the magnitude of obesity and MetS and their associations with impaired renal function among type 2 diabetes mellitus (T2DM) patients. A national survey of T2DM patients was collected in the Thai National Health Security Office database during 2014–5. The sampling frame was designated as distinct geographic regions throughout the country. A stratified two-stage cluster sampling was used to select the study population. Anthropometry and 12-hour fasting blood samples were obtained by trained personnel. BMI of ≥25 kg/m² was classified as obesity. MetS was defined as having elevated waist circumference (>90 and >80 cm in men and women, respectively) plus any two of the followings: triglyceride ≥150 mg/dL, HDL-C <40 in men or <50 mg/dL in women, blood pressure ≥130/85 mmHg, and fasting blood sugar ≥100 mg/dL. CKD was defined as an impaired renal function (eGFR <60 mL/min/1.73m² according to the CKD-EPI equation). Logistic regression analysis was performed to examine the relationship between obesity and MetS with the presence of CKD. A total of 32,616 diabetic patients were finally recruited from 997 hospitals. The mean age was 61.5±10.9 years with 67.5% women. Of the participants, 35.4% were CKD patients. The prevalence of obesity was 46.5% in CKD and 54.1% in non-CKD patients with T2DM (p<0.001). In contrast, the prevalence of MetS in CKD patients was higher than their non-CKD counterparts (71.3 vs 68.8%, p<0.001). Moreover, there was an association between the prevalence of MetS with CKD stage from 3a to 5 (70.1, 72.3, 73.4, and 72.7%, respectively, p trend = 0.02). MetS, but not obesity, had a significant association with CKD in T2DM patients after adjusting for age, sex, and comorbidities [OR 1.14; 95% CI 1.06–1.22, p<0.001]. When stratified by each component of MetS, only high serum triglyceride and low HDL-C levels were increased in patients with CKD stage 4 and 5 compared with CKD stage 3 (p<0.001) and had a significant relationship with impaired renal function. There were relatively high prevalences of both obesity and MetS in T2DM patients. A higher prevalence of MetS, but lower prevalence of obesity, was observed among diabetic CKD group compared with their non-CKD counterparts. MetS, as a surrogate of insulin resistance, appeared to be more important than obesity in the development of impaired renal function in diabetic population.

In hemodialysis (HD) patients, protein-energy wasting (PEW) is highly prevalent and firstly treated with oral nutritional supplements (ONS). The extent to which intradialytic parenteral nutrition (IDPN) contributes to improve PEW status in HD patients intolerable to ONS remains unclear. Maintenance PEW HD patients being unable to tolerate ONS adverse effects, and having spontaneous energy and protein intake of ≥ 20 kcal/kg/day and ≥ 0.8 g/kg/day, respectively were randomly assigned 1:1 into IDPN and control groups. In IDPN group, most concentrated 3-in-1, fish-oil based parenteral nutrition was infused during HD for 3 months. The control group received intensive dietary counselling once weekly for 3 months. Both groups were then followed for additional 3 months after intervention. A total of 38 patients were randomized (mean age 67.6 years). After 3 months, serum albumin was significantly higher in the IDPN (n = 18) compared with control group (from 3.5 ± 0.3 to 3.8 ± 0.2 vs from 3.6 ± 0.3 to 3.5 ± 0.3 g/dL, respectively, p = 0.01). Spontaneous dietary intake (p = 0.04), body weight (p = 0.01), and malnutrition inflammation score (MIS, p = 0.01) were improved in the IDPN, but not in the control group. Muscle mass, strength, serum prealbumin, interleukin-6, high sensitivity-c reactive protein, and acylated ghrelin were not significantly different but leptin levels increased in the control group after 3 months (p = 0.03). At 6 months, serum albumin in the IDPN group was persistently higher than baseline (p = 0.04). Neither volume overload nor uncontrolled hyperglycemia was found throughout the study. In conclusion, a 3-month IDPN supplementation demonstrated a significant increase in serum albumin, body weight, spontaneous oral intake, and MIS; and appeared to be superior to continuing intensive dietary counselling among HD patients intolerable to ONS. The impacts of IDPN therapy on clinical outcomes may require larger scale with longer period of study.

In slowing kidney progression, numerous pre-dialysis chronic kidney disease (CKD) patients could not adhere to the well-established dietary pattern, including a very low protein diet, 0.3–0.4 g/kg/day, plus a full dose ketoanalogues (KAs) of amino acids. We evaluated the role of a low protein diet (LPD), 0.6–0.8 g/kg/day, combined with KAs (LPD–KAs) on CKD progression. We extracted data in the retrospective cohort using electronic medical records (n = 38,005). Participants with LPD–KAs for longer than six months were identified. An unmatched control group, LPD alone, was retrieved from the same database. Cox proportional hazard models were performed to examine the associations between LPD–KAs and outcomes. The primary outcome was either a rapid estimated glomerular filtration rate (eGFR) decline > 5 mL/min/1.73m²/year or commencing dialysis. Other secondary outcomes include changes in proteinuria, serum albumin, and other metabolic profiles were also assessed. A total of 1042 patients were finally recruited (LPD–KAs = 543). Although patients with LPD–KAs had significantly lower eGFR and a prevalence of diabetes, age, and dietary protein intake were comparable between LPD–KAs (0.7 ± 0.2 g/kg/day) and LPD alone groups (0.7 ± 0.3 g/kg/day, p = 0.49). During a median follow-up of 32.9 months, patients treated with LPD–KAs had a significantly lower risk of kidney function decline (HR 0.13; 95% CI 0.09–0.19, p < 0.001) and dialysis initiation (HR 0.24; 95% CI 0.12–0.49, p < 0.001) than LPD alone after adjusting for confounders. The annual rate of eGFR decline in patients receiving LPD–KAs was 4.5 [3.4–5.5] mL/min/1.73m² compared with 7.7 [6.0–9.4] mL/min/1.73m² in LPD alone (p = 0.001). According to KAs dose–response analysis, the daily dose of ≤ 5 tablets was conversely associated with a higher risk of the primary endpoint, whereas the association disappeared among patients receiving a dose of > 6 tablets. The spot urine protein creatinine ratio and serum phosphate levels were not significantly different between groups. LPD–KAs could retard kidney progression compared with LPD alone. This favorable effect was significant among CKD patients receiving a daily KAs dose of more than six tablets. Future randomized controlled trials should be performed to verify these findings.

Emerging evidence indicates gut microbiota is essential to chronic kidney disease (CKD) progression. This study investigated the association between gut microbiota profiles, plasma trimethylamine-N-oxide (TMAO), and circulating inflammatory markers in CKD patients according to dietary patterns, particularly low-protein, high-fiber (LP-HF) versus high-protein, low-fiber (HP-LF) diet. In this cross-sectional study, patients with non-dialysis CKD and healthy subjects were enrolled. Dietary patterns among participants were assessed using three-day diet records with detailed nutrient analysis. The 16 S ribosomal RNA sequencing was conducted to examine fecal gut microbiota composition. Plasma samples were analyzed for TMAO concentration and cytokine levels. A total of 135 CKD patients were recruited. A distinct shift in gut microbiota composition in CKD patients was observed compared to 19 healthy controls, particularly a significant reduction of short-chain fatty acid (SCFA)-producing bacteria. TMAO and several cytokine levels were significantly elevated in CKD patients compared to healthy subjects. Within CKD, patients with LP-HF diet displayed a greater abundance of SCFA-producing bacteria, such as the Lachnospiraceae NK4A136 group and Eubacterium ruminantium group, than those with the HP-LF diet. The HP-LF subgroup showed enriched proteolytic bacterial genera such as Klebsiella. The HP-LF subgroup also exhibited significantly higher plasma levels of TMAO, interleukin (IL)-18, and monocyte chemoattractant protein-1 (MCP-1). CKD patients displayed marked alterations in gut bacterial composition compared to healthy controls. Our results also highlighted the potential advantages of adopting a high fiber-rich and low-protein diet intake in reducing gut dysbiosis in CKD patients.

Background: Obesity is a major public health with increasing numbers of obese individuals are at risk for kidney disease. However, the validity of serum creatinine-based glomerular filtration rate (GFR) estimating equations in obese population is yet to be determined. Methods: We evaluated the performance of the reexpressed Modification of Diet in Renal Disease (MDRD), reexpressed MDRD with Thai racial factor, Thai estimated GFR (eGFR) as well as Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations among obese patients, defined as body mass index (BMI) ≥25 kg/m² with the reference measured GFR (mGFR) determined by ^99mTc-diethylene triamine penta-acetic acid (^99mTc-DTPA) plasma clearance method. Serum creatinine levels were measured using standardized enzymatic method simultaneously with GFR measurement. The statistical methods in assessing agreement for continuous data including total deviation index (TDI), concordance correlation coefficient (CCC), and coverage probability (CP) for each estimating equation were compared with the reference mGFR. Accuracy within 10% representing the percentage of estimations falling within the range of ±10% of mGFR values for all equations were also tested. Results: A total of 240 Thai obese patients were finally recruited with mean BMI of 31.5 ± 5.8 kg/m². In the total population, all eGFR equations underestimated the reference mGFR. The average TDI values were 55% indicating that 90% of the estimates falling within the range of -55 to +55% of the reference mGFR. The CP values averaged 0.23 and CCC scores ranged from 0.75 to 0.81, reflecting the low to moderate levels of agreement between each eGFR equation and the reference mGFR. The proportions of patients achieving accuracy 10% ranged from 23% for the reexpressed MDRD equation to 33% for the Thai eGFR formula. Among participants with BMI more than 35 kg/m² (n = 48), the mean error of all equations was extremely wide and significantly higher for all equations compared with the lower BMI category. Also, the strength of agreement evaluated by TDI, CCC, and CP were low in the subset of patients with BMI ≥35 kg/m². Conclusion: Estimating equations generally underestimated the reference mGFR in subjects with obesity. The overall performance of GFR estimating equations demonstrated poor concordance with the reference mGFR among individuals with high BMI levels. In certain clinical settings such as decision for dialysis initiation, the direct measurements of GFR are required to establish real renal function among obese population.