R. Garcia-Naveiro

Peritonitis is a well-known cause of mortality in peritoneal dialysis (PD) patients. We carried out a retrospective study to disclose the clinical spectrum and risk profile of peritonitis-related mortality. We analyzed 693 episodes of infectious peritonitis suffered by 565 patients (follow-up 1149 patient-years). Death was the final outcome in 41 cases (5.9% of episodes), peritonitis being directly implicated in 15.2% of the global mortality and 68.5% of the infectious mortality observed. In 41.5% of patients with peritonitis-related mortality, the immediate cause of death was a cardiovascular event. Highest mortality rates corresponded to fungal (27.5%), enteric (19.3%), and Staphylococcus aureus (15.2%) peritonitis. Multivariate analysis disclosed thatthe baseline risk of peritonitis-related mortality was significantly higher in female [relative risk (RR) 2.13, 95% confidence interval (CI) 1.24-4.09, p = 0.02], older (RR 1.10/year, CI 1.06-1.14, p < 0.0005), and malnourished patients (RR 2.51, CI 1.21-5.23, p = 0.01) with high serum C-reactive protein (s-CRP) levels (RR 4.04, CI 1.45-11.32, p = 0.008) and a low glomerular filtration rate (RR 0.75 per mL/minute, CI 0.64 -0.87, p < 0.0005). Analysis of risk after a single episode of peritonitis and/or subanalysis restricted to peritonitis caused by more aggressive micro-organisms disclosed that overall comorbidity [odds ratio (OR) 1.21, CI 1.05-1.71, p = 0.005], depression (OR 2.35, CI 1.14-4.84, p = 0.02), and time on PD at the time of the event (OR 1.02/month, CI 1.00-1.03, p = 0.02) were other predictors of mortality. In summary, the etiologic agent is a definite marker of peritonitis-related mortality but gender, age, residual renal function, inflammation (s-CRP), malnutrition, and depression are other significant correlates of this outcome. Most of these risk factors are common to cardiovascular and peritonitis-related mortality, which may explain the high incidence of cardiovascular event as the immediate cause of death in patients with peritonitis-related mortality.

BACKGROUND: Ghrelin has been characterized as a relevant physiologic regulator of appetite and body weight in humans. However, the potential relationships between ghrelin levels, inflammation and malnutrition in dialysis patients have not been adequately studied. METHODS: We used a cross-sectional design to study 20 haemodialysis (HD) and 21 peritoneal dialysis (PD) patients, and compared their plasma ghrelin (PGhr) levels with that of an age-matched control group. We also explored correlations between ghrelin and selected hormonal, renal adequacy, nutritional and inflammation markers in both groups. RESULTS: PGhr levels were higher in HD (median 119.8 pg/ml, range 71.1-333.7, P = 0.001) and PD (99.3, range 45.8-578.5, P = 0.045) patients than in healthy controls (78, range 29-158) (HD vs PD, not significant). Ghrelin levels were strongly and inversely correlated with age (r = -0.46, P = 0.02 for patients; r = -0.61, P = 0.001 for controls). Except for a positive correlation between ghrelin and growth hormone (r = 0.48, P = 0.002), univariate analysis failed to detect associations between PGhr and the measured hormonal values, renal adequacy, nutritional indicators and markers of inflammation. However, multivariate analysis revealed significant inverse correlations between PGhr levels and nutritional markers, including subjective global assessment (P = 0.013), albumin (P = 0.001), transferrin (P = 0.01) and protein nitrogen appearance (as an estimate of protein intake) (P = 0.035), after controlling for the confounding effect of age. CONCLUSIONS: PGhr levels were moderately and similarly increased in patients undergoing HD and PD. Age was a strong determinant of PGhr levels, both in uraemic patients and in healthy controls. Dialysis adequacy, residual renal function and inflammation did not appear to influence ghrelin levels in these patients. The negative correlation between PGhr and nutritional markers suggests that low dietary intake causes increases in ghrelin secretion in dialysis patients.

BACKGROUND: Estimations of glomerular filtration rate (GFR) obtained either by the modification of diet in renal disease study equation (MDRD-GFR) or by classic 24-hour urine collection-based methods (mean of creatinine and urea clearance (Ccr-ur)) are considered to be equivalent in patients with chronic renal failure (CRF). However, the agreement between both methods has been insufficiently studied in patients during the most advanced stages of CRF. METHODS: We compared 615 estimations of GFR performed by both methods simultaneously in adult (> 18 years) patients with advanced (aCRF) (15 - 30 ml/min/1.73m2) and preterminal (tCRF) (< 15 ml/min/1.73m2) chronic renal failure. We also analyzed the influence of some relevant covariables (demographic characteristics, inflammatory and nutritional markers) with respect to the concordance between both methods. RESULTS: In aCRF, mean GFR were 19.7 +/- 5.5 (MDRD-GFR) and 19.3 +/- 3.7 ml/min/1.73m2 (Ccr-ur) (mean difference 0.4 ml/min/1.73m2, 95% confidence interval CI -0.3/1.1, p = 0.26), with an intraclass correlation coefficient of 0.46. In tCRF, mean GFR was 12.5 +/- 4.2 and 10.4 +/- 2.7 ml/min/1.73m2, respectively (mean difference 2.1 ml/min/1.73m2, 95% CI 1.7/2.4, p < 0.0005), with an intraclass correlation co-efficient of 0.43. Multivariate analysis identified lean body mass, body mass index, protein nitrogen appearance, proteinuria, gender, age, albumin (aCRF) and prealbumin (tCRF) as variables independently correlated with the difference MDRD-GFR minus Ccr-ur. Lean body mass was by far the strongest predictor of deviations between both methods, both in aCRF (R2 = 0.66, p < 0.0005) and tCRF (R2 = 0.49, p < 0.0005). CONCLUSIONS: MDRD-GFR and Ccr-ur show an acceptable agreement in advanced stages of chronic renal failure. However, MDRD-GFR produces estimations of GFR systematically higher than those given by the Ccr-ur method, in patients with tCRF. Moreover, this overestimation is particularly marked in some high risk subsets, including elderly patients and those presenting markers of a poor nutritional condition. Until this issue is further clarified, GFR should be estimated using Ccr-ur rather than MDRD-GFR in patients with tCRF, as also in older and malnourished patients with aCRF, as this may represent a more conservative and safer approach at the time of planning initiation of renal replacement therapy.