Objective The aim of this study was to apply high performance liquid chromatography (HPLC) with modern gel filtration media to determine high molecular weight (HMW) icodextrin fractions and low molecular weight (LMW) icodextrin metabolites in dialysate and plasma in peritoneal dialysis (PD) patients on treatment with icodextrin, and to explore the potential relationships between these compounds, α-amylase activity, and glomerular filtration rate. Design Retrospective study of dialysate and plasma samples from PD patients. Setting Samples were collected at one PD center. Patients Blood and dialysate samples were obtained from PD patients who were subdivided into three groups: patients using only glucose-based peritoneal dialysis fluid (GPDF; GLU group, n = 23), patients studied after the first long dwell with icodextrin-based peritoneal dialysis fluid (IPDF; 1st ICO group, n = 24), and patients who were regular users of IPDF for the long dwells (ICO group, n = 9). Methods LMW icodextrin metabolites [ i.e., maltose (G2), maltotriose (G3), maltotetraose (G4), maltopentaose (G5), maltohexaose (G6), and maltoheptaose (G7)] and HMW fractions were determined in plasma and dialysate using two different gel filtration HPLC methods. Enzymatic hydrolysis with amyloglucosidase to glucose yielded the total carbohydrate content and this was used to validate the HPLC results. α-Amylase activity was determined using a routine method. Results The results obtained by gel filtration HPLC yielded values of LMW metabolites and HMW fractions in plasma and dialysate in agreement with results obtained with enzymatic hydrolysis. HMW fractions were not detectable in plasma. Absorption of icodextrin from the peritoneal cavity during the long dwell (10 – 16 hours) was, on average, 39% of the amount instilled. During the long dwell, there was a relative decrease in the dialysate concentration of the largest HMW fractions (>21.4 kDa). Plasma concentration of the LMW icodextrin metabolites G2–G7 was highest in the ICO group (2.65 ± 0.54 mg/mL) but also higher in the 1st ICO group (1.97 ± 0.57 mg/mL) compared with the GLU group (0.52 ± 0.23 mg/mL). Plasma α-amylase activity was significantly lower in the 1st ICO group and in the ICO group compared with the GLU group. Conclusions Accurate analysis of HMW icodextrin fractions in dialysate and LMW icodextrin metabolites in plasma and dialysate in PD patients can be achieved by gel filtration HPLC with two different columns. This method can be used to study the complex pattern of changes in icodextrin and its metabolites in plasma and dialysate. The finding that HMW icodextrin fractions were not detected in plasma was unexpected, and differs from results of previous studies by other researchers.

In 32 noncirrhotic patients on peritoneal dialysis, mean serum β₂-microglobulin (sβ₂M) was 26.58 ± 12.32 mg/l (9.7-63.5). We found a significant correlation between sβ₂M and serum creatinine (sCr; r = 0.760), blood urea nitrogen (BUN; r = 0.573), total creatinine and BUN clearance (r = 0.623 and 0.599, respectively), 24-hour Kt/V (r = 0.638), glomerular filtration rate (r = 0.623), 24-hour urine output (r = 0.669), serum total protein (r = 0.584) (p < 0.01 for all the above r values); β₂M peritoneal clearance and mass transfer (r = 0.414 and 0.427, respectively; p < 0.05). Our data demonstrate and confirm the contribution of residual renal function in determining sβ₂M levels and it is seemingly more important than β₂M peritoneal clearance.

Solutes removed during PD tend to decrease following an increase in molecular weight of the substance. Since anuric patients are at higher risk of middle molecule and small protein accumulation, more attention should be paid to the removal of middle molecules. Further studies should be undertaken to evaluate whether removing them has a clinical impact and to determine their threshold levels.

Gadolinium-based contrast media (GBCM) toxicity in patients with kidney disease is a concern for the possible development of systemic nephrogenic fibrosis and possible renal complications. This review focuses on the pathological mechanisms underlying the potential kidney toxicity of gadolinium. Gadolinium, as a free compound (Gd3+), is highly toxic in humans because it competes with divalent calcium (Ca2+) and magnesium (Mg2+) ions, interfering in some relevant biologic processes. Its toxicity is blunted by the complexing of Gd3+ with a carrier, allowing its use in magnetic resonance imaging. The binding reaction between gadolinium and a carrier is thermodynamically reversible. Consequently, under some conditions, gadolinium can be released in the interstitial space as a free Gd3+ compound with the possibility of toxicity. Other metals such as iron, copper, and calcium can interfere with the binding between gadolinium and its carrier because they compete for the same binding site. This process is known as transmetallation. In patients with kidney impairment, conditions such as low clearance of the Gd-carrier complex, acid-base derangements, and high serum phosphorous can increase the presence of free Gd3+, leading to a higher risk for toxicity.

Poor compliance in peritoneal dialysis (PD) is a significant cause of dropout and morbidity. PD Adequest software, which, through a mathematical model, predicts the effect of the dialysis prescription on the basis of the peritoneal transport, may be used to identify the noncompliant patient. Fifty patients from two dialysis centers, aged 65.9±1.5 years and on PD for 28.6±4.7 months, were studied. A peritoneal equilibration test (PET) was carried out and 24hour urine and dialysate were collected. Total weekly creatinine clearance (CrCI, L/week/1.73 m2) was calculated, as well as the glomerular filtration rate [(GFR), mL/min, mean CrCI and urea nitrogen clearance (UNCI)]. The dialytic schedules used were then introduced into the program and the parameters were recalculated using the software model. Nine patients considered noncompliant from their case histories were used to assess the differences of reference between expected and measured values. The control group was significantly different from the noncompliant group in the percentage of the CrCI and the serum creatinine (sCR) differences. The noncompliance threshold value was calculated from the mean of the lower 95% confidence interval of the compliant group and the higher one of the noncompliant group (-5.3%) for CrCI and vice versa for sCR (+10%), which behaved to the contrary. Reassessing the patients, 11 (22%) were identified as probably noncompliant.