Thyago Proença de Moraes

Predictive Value of Malnutrition Markers for Mortality in Peritoneal Dialysis Patients

INTRODUCTION Alterations in nutritional status have been described as important predictors of mortality in patients with chronic kidney disease (CKD). However, the association between multiple markers for nutritional status and the mortality rates of patients with CKD on peritoneal dialysis (PD) has not yet been illustrated in previously published data, particularly by using the new definition of protein energy wasting (PEW). OBJECTIVE To evaluate the predictive value of malnutrition markers for mortality rates, on the basis of the PEW definition, of PD patients. MATERIALS AND METHODS At the start of PD treatment, the nutritional status of 199 patients (mean age, 56 ± 13.3 years; 53% females) was evaluated. Body mass index (BMI), arm circumference, mid-arm muscle circumference, protein and caloric intake (by using a 3-day food record), and serum albumin were all recorded, as well as a subjective global assessment (SGA) and presence of PEW. Cut-off points were defined on the basis of the consensus of the International Society for Renal Nutrition and Metabolism (albumin, <3.8 g/dL; BMI, <23 kg/m(2); mid-arm muscle circumference, >10% in comparison with the 50th percentile for the reference population; protein intake, <0.8 g/kg/daily; caloric intake, <25 kcal/kg/daily). The data were obtained retrospectively between the years 2001 and 2008 on the basis of routine nutritional evaluation. Patients were monitored for fatal events from all possible causes. RESULT The mean BMI for the population was 26.6 ± 5.0 kg/m(2). A median protein intake of 0.94 (0.18 to 4.57) g/kg/daily was reported and 60.3% of the patients reported a protein intake of <0.8 g/kg/daily. With respect to caloric intake, 38.7% of the patients consumed <25 kcal/kg/daily. A median of 3.5 (1.4 to 5.3) g/dL for serum albumin was observed and 29.3% of the patients presented values of <3.8 g/dL. PEW was diagnosed in 17.5% of patients. In the univariate model, being of age >65 years (P = .002), cardiovascular disease (P < .001), diabetes mellitus (P = .02), SGA (P = .02), and albumin (P = .002), were all significant markers for mortality. The presence of patients aged >65 years (P = .02), with diabetes mellitus (P = .057), cardiovascular disease (P = .005), and albumin were considered as independent factors for mortality in this study. CONCLUSION SGA, albumin, and PEW were the only nutritional markers found to be associated with mortality in this cohort of PD patients. In the multivariate analysis, after adjusting for classic mortality risk factors, only patients with hypoalbuminemia were found to be at a high risk for mortality at follow-up. These results may be limited by the number of observations and a necessity for confirmation in larger prospective studies.

Inflammation and the Peritoneal Membrane: Causes and Impact on Structure and Function during Peritoneal Dialysis

Peritoneal dialysis therapy has increased in popularity since the end of the 1970s. This method provides a patient survival rate equivalent to hemodialysis and better preservation of residual renal function. However, technique failure by peritonitis, and ultrafiltration failure, which is a multifactorial complication that can affect up to 40% of patients after 3 years of therapy. Encapsulant peritoneal sclerosis is an extreme and potentially fatal manifestation. Causes of inflammation in peritoneal dialysis range from traditional factors to those related to chronic kidney disease per se, as well as from the peritoneal dialysis treatment, including the peritoneal dialysis catheter, dialysis solution, and infectious peritonitis. Peritoneal inflammation generated causes significant structural alterations including: thickening and cubic transformation of mesothelial cells, fibrin deposition, fibrous capsule formation, perivascular bleeding, and interstitial fibrosis. Structural alterations of the peritoneal membrane described above result in clinical and functional changes. One of these clinical manifestations is ultrafiltration failure and can occur in up to 30% of patients on PD after five years of treatment. An understanding of the mechanisms involved in peritoneal inflammation is fundamental to improve patient survival and provide a better quality of life.

ISPD Catheter-Related Infection Recommendations: 2017 Update

Department of Medicine and Therapeutics,1 Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong; Department of Nephrology,2 University of Queensland at Princess Alexandra Hospital, Brisbane, Australia; Renal Electrolyte Division,3 University of Pittsburgh School of Medicine Pittsburgh, PA, USA; Renal Division,4 Department of Medicine, Peking University First Hospital, Beijing, China; Pontifícia Universidade Católica do Rio Grande do Sul,5 FAENFI, Porto Alegre, Brazil; Division of Nephrology,6 Nagoya University Graduate School of Medicine, Nagoya, Japan; Division of Nephrology,7 Bezmialem Vakif University, Medical Faculty, Istanbul, Turkey; Pontifícia Universidade Católica do Paraná,8 Curitiba, Brazil; Elisabeth Tweesteden Hospital,9 Nephrology Department and Internal Medicine, Tilburg, Netherlands; and Imperial College Renal and Transplant Centre,10 Hammersmith Hospital, London, UK ISPD GUIDELINES/RECOMMENDATIONS

Icodextrin reduces insulin resistance in non-diabetic patients undergoing automated peritoneal dialysis: results of a randomized controlled trial (STARCH)

BACKGROUND Insulin resistance is a common risk factor in chronic kidney disease patients contributing to the high cardiovascular burden, even in the absence of diabetes. Glucose-based peritoneal dialysis (PD) solutions are thought to intensify insulin resistance due to the continuous glucose absorption from the peritoneal cavity. The aim of our study was to analyse the effect of the substitution of glucose for icodextrin on insulin resistance in non-diabetic PD patients in a multicentric randomized clinical trial. METHODS This was a multicenter, open-label study with balanced randomization (1:1) and two parallel-groups. Inclusion criteria were non-diabetic adult patients on automated peritoneal dialysis (APD) for at least 3 months on therapy prior to randomization. Patients assigned to the intervention group were treated with 2L of icodextrin 7.5%, and the control group with glucose 2.5% during the long dwell and, at night in the cycler, with a prescription of standard glucose-based PD solution only in both groups. The primary end-point was the change in insulin resistance measured by homeostatic model assessment (HOMA) index at 90 days. RESULTS Sixty patients were included in the intervention (n = 33) or the control (n = 27) groups. There was no difference between groups at baseline. After adjustment for pre-intervention HOMA index levels, the group treated with icodextrin had the lower post-intervention levels at 90 days in both intention to treat [1.49 (95% CI: 1.23-1.74) versus 1.89 (95% CI: 1.62-2.17)], (F = 4.643, P = 0.03, partial η(2) = 0.078); and the treated analysis [1.47 (95% CI: 1.01-1.84) versus 2.18 (95% CI: 1.81-2.55)], (F = 7.488, P = 0.01, partial η(2) = 0.195). CONCLUSIONS The substitution of glucose for icodextrin for the long dwell improved insulin resistance measured by HOMA index in non-diabetic APD patients.

Low Serum Potassium Levels Increase the Infectious-Caused Mortality in Peritoneal Dialysis Patients: A Propensity-Matched Score Study

Background and Objectives Hypokalemia has been consistently associated with high mortality rate in peritoneal dialysis. However, studies investigating if hypokalemia is acting as a surrogate marker of comorbidities or has a direct effect in the risk for mortality have not been studied. Thus, the aim of this study was to analyze the effect of hypokalemia on overall and cause-specific mortality. Design, Setting, Participants and Measurements This is an analysis of BRAZPD II, a nationwide prospective cohort study. All patients on PD for longer than 90 days with measured serum potassium levels were used to verify the association of hypokalemia with overall and cause-specific mortality using a propensity match score to reduce selection bias. In addition, competing risks were also taken into account for the analysis of cause-specific mortality. Results There was a U-shaped relationship between time-averaged serum potassium and all-cause mortality of PD patients. Cardiovascular disease was the main cause of death in the normokalemic group with 133 events (41.8%) followed by PD-non related infections, n=105 (33.0%). Hypokalemia was associated with a 49% increased risk for CV mortality after adjustments for covariates and the presence of competing risks (SHR 1.49; CI95% 1.01-2.21). In contrast, in the group of patients with K <3.5mEq/L, PD-non related infections were the main cause of death with 43 events (44.3%) followed by cardiovascular disease (n=36; 37.1%). For PD-non related infections the SHR was 2.19 (CI95% 1.52-3.14) while for peritonitis was SHR 1.09 (CI95% 0.47-2.49). Conclusions Hypokalemia had a significant impact on overall, cardiovascular and infectious mortality even after adjustments for competing risks. The causative nature of this association suggested by our study raises the need for intervention studies looking at the effect of potassium supplementation on clinical outcomes of PD patients.

Impact of patient training patterns on peritonitis rates in a large national cohort study

BACKGROUND Ideal training methods that could ensure best peritoneal dialysis (PD) outcome have not been defined in previous reports. The aim of the present study was to evaluate the impact of training characteristics on peritonitis rates in a large Brazilian cohort. METHODS Incident patients with valid data on training recruited in the Brazilian Peritoneal Dialysis Multicenter Study (BRAZPD II) from January 2008 to January 2011 were included. Peritonitis was diagnosed according to International Society for Peritoneal Dialysis guidelines; incidence rate of peritonitis (episodes/patient-months) and time to the first peritonitis were used as end points. RESULTS Two thousand two hundred and forty-three adult patients were included in the analysis: 59 ± 16 years old, 51.8% female, 64.7% with ≤4 years of education. The median training time was 15 h (IQI 10-20 h). Patients were followed for a median of 11.2 months (range 3-36.5). The overall peritonitis rate was 0.29 per year at risk (1 episode/41 patient-months). The mean number of hours of training per day was 1.8 ± 2.4. Less than 1 h of training/day was associated with higher incidence rate when compared with the intervals of 1-2 h/day (P = 0.03) and >2 h/day (P = 0.02). Patients who received a cumulative training of >15 h had significantly lower incidence of peritonitis compared with <15 h (0.26 per year at risk versus 0.32 per year at risk, P = 0.01). The presence of a caregiver and the number of people trained were not significantly associated with peritonitis incidence rate. Training in the immediate 10 days after implantation of the catheter was associated with the highest peritonitis rate (0.32 per year), compared with training prior to catheter implantation (0.28 per year) or >10 days after implantation (0.23 per year). More experienced centers had a lower risk for the first peritonitis (P = 0.003). CONCLUSIONS This is the first study to analyze the association between training characteristics and outcomes in a large cohort of PD patients. Low training time (particularly <15 h), smaller center size and the timing of training in relation to catheter implantation were associated with a higher incidence of peritonitis. These results support the recommendation of a minimum amount of training hours to reduce peritonitis incidence regardless of the number of hours trained per day.

Characterization of the BRAZPD II cohort and description of trends in peritoneal dialysis outcome across time periods.

Observational studies from different regions of the world provide valuable information in patient selection, clinical practice, and their relationship to patient and technique outcome. The present study is the first large cohort providing patient characteristics, clinical practice, patterns and their relationship to outcomes in Latin America. The objective of the present study was to characterize the cohort and to describe the main determinants of patient and technique survival, including trends over time of peritoneal dialysis (PD) initiation and treatment. This was a nationwide cohort study in which all incident adult patients on PD from 122 centers were studied. Patient demographics, socioeconomic and laboratory values were followed from December 2004 to January 2011 and, for comparison purposes, divided into 3 groups according to the year of starting PD: 2005/06, 2007/08 and 2009/10. Patient survival and technique failure (TF) were analyzed using the competing risk model of Fine and Gray. All patients active at the end of follow-up were treated as censored. In contrast, all patients who dropped the study for any reason different from the primary event of interest were treated as competing risk. Significance was set to a p level of 0.05. A total of 9,905 patients comprised the adult database, 7,007 were incident and 5,707 remained at least 90 days in PD. The main cause of dropout was death (54%) and of TF was peritonitis (63%). Technique survival at 1, 2, 3, 4, and 5 years was 91%, 84%, 77%, 68%, and 58%, respectively. There was no change in TF during the study period but 3 independent risk factors were identified: lower center experience, lower age, and automated PD (APD) as initial therapy. Cardiovascular disease (36%) was the main cause of death and the overall patient survival was 85%, 74%, 64%, 54%, and 48% at 1, 2, 3, 4, and 5 years, respectively. Patient survival improved along all study periods: compared to 2005/2006, patients starting at 2007/2008 had a relative risk reduction (SHR) of 0.83 (95% confidence interval [CI] 0.72 - 0.95); and starting in 2009/2010 of 0.69 (95% CI 0.57 - 0.83). The independent risk factors for mortality were diabetes, age > 65 years, previous hemodialysis, starting PD modality, white race, low body mass index (BMI), low educational level, center experience, length of pre-dialysis care, and the year of starting PD. We observed an improvement in patient survival along the years. This finding was sustained even after correction for several confounders and using a competing risk approach. On the other hand, no changes in technique survival were found.

Comparative analysis of lipid and glucose metabolism biomarkers in non-diabetic hemodialysis and peritoneal dialysis patients

OBJECTIVE To investigate and compare glucose and lipid metabolism biomarkers in non-diabetic peritoneal dialysis and hemodialysis patients. METHODS The study followed a prospective and cross-sectional design. PARTICIPANTS Participants included all prevalent end-stage renal disease patients under renal replacement therapy treated in a university-based clinic. INTERVENTIONS There were no interventions. MAIN OUTCOMES MEASURES Blood samples were taken after 8 hours of fasting. Insulin serum levels were determined by chemiluminescence. Insulin resistance were assessed by the insulin sensitivity check index (QUICKI) determined as follow: 1/[log(Io) + log(Go)], where Io is the fasting insulin, and Go is the fasting glucose. HOMA index was also measured: (FPG × FPI)/22.5; FPG = fasting plasma glucose (mmol/L); FPI = fasting plasma insulin (mU/mL). The others biochemical exams were measured utilizing the routine tests. RESULTS We screened 154 patients (80 on hemodialysis and 74 on peritoneal dialysis). Seventy-four diabetic patients were excluded. Of the remaining 80 patients (55% males, mean age 52 ± 15 years), 35 were on peritoneal dialysis and 45 on hemodialysis. Fasting glucose of peritoneal dialysis patients compared to hemodialysis patients were 5.0 ± 0.14 versus 4,58 ± 0.14 mmol/L, p<0.05; glycated hemoglobin 5.9 ± 0.1 versus 5.5 ± 0.1%, p < 0.05; total cholesterol 5.06 ± 0.19 versus 3.39 ± 0.20 mmol/L, p < 0.01; LDL-c 2.93 ± 0.17 versus 1.60 ± 0.17 mmol/L, p < 0.01; and index HOMA 3.27 versus 1,68, p < 0,05. Importantly, all variables were adjusted for age, gender, dialysis vintage, calcium-phosphorus product, albumin and C-reactive protein levels. CONCLUSION We observed a worst profile of lipid and glucose metabolism biomarkers in peritoneal dialysis patients (lower insulin sensitivity and higher fasting glucose, HbA1c, total cholesterol and LDL-c) when compared to hemodialysis, potentially due to the glucose-based dialysis solutions utilized in the peritoneal dialysis population.

Metabolic impact of peritoneal dialysis.

Peritoneal dialysis (PD) patients are at high risk of developing cardiovascular disease, resulting from both traditional and nontraditional cardiovascular risk factors, including factors related to uremia and dialysis. Glucose metabolism is altered in chronic kidney disease patients even in the earlier stages and the most common manifestations are insulin resistance and dyslipidemia, known factors in the pathogenesis of hypertension and atherosclerosis. Exposure to high glucose concentration solutions during PD intensifies these metabolic abnormalities, which are extremely common in PD patients and potentially have an impact on cardiovascular outcome. Life style and dietary modification and pharmacological interventions may be particularly important to revert these risk factors and glucose sparing solutions may represent an additional strategy to change the PD-induced metabolic profile. Together, these approaches may have a positive impact in reducing the risk of mortality in PD patients.

Length of time on peritoneal dialysis and encapsulating peritoneal sclerosis : position paper for ISPD : 2017 update

Imperial College Renal and Transplant Centre,1 Hammersmith Hospital, London, UK; University Health Network and the University of Toronto,2 Toronto, ON, Canada; Renal Division,3 Ghent University Hospital, Ghent, Belgium; Kidney Research Center,4 Department of Nephrology, Chang Gung Memorial Hospital, Taoyuan, Taiwan; Yale School of Medicine,5 New Haven, CT, USA; Central Manchester and Manchester Children’s NHS Foundation Trust,6 Manchester, UK; Department of Nephrology,7 University of Queensland at Princess Alexandra Hospital, Brisbane, Australia; Tsuchiya General Hospital,8 Faculty of Medicine, Hiroshima University, Japan; Institute for Applied Clinical Sciences,9 Keele University, Stoke-on-Trent, UK; Pontificia Universidade Catolica do Parana,10 Curitiba, Parana, Brazil; Division of Nephrology,11 Cliniques universitaires Saint-Luc, Brussels, Belgium, et Institut de Recherche Expérimentale et Clinique, Université catholique de Louvain, Brussels, Belgium; and St James’s University Hospital,12 Leeds, UK ISPD GUIDELINES/RECOMMENDATIONS