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Patients on hemodialysis (HD) and renal transplant recipients (RT) have a high prevalence of HCV infection. The aim of our study was to determine the prevalence of HCV-RNA in the anti-HCV positive patients and to compare the biochemical parameters of PCR(+) and PCR(−) subgroups. Methods: The 525 sera were screened for anti-HCV. HCV-RNA was detected by polymerase chain reaction (PCR) and liver enzymes [SGOT, SGPT, GGT, α-glutathione S-transferase (GST)] were measured. Results: Active viraemia was found only in 187 of 289 (65%) seropositive HD patients in contrast to 53 of 53 (100%) of seropositive RT patients. Significantly increased (p<0.05) GST values (9.9 μg/l) were found in the PCR(+) subgroups compared to GST levels (2.7 μg/l) of the PCR(−) subgroups. Elevated GST concentration was found in 80% (208/251) of PCR(+) patients. The measured enzymes were not elevated in HCV infected patients. Six percent of HD and 11% of RT patients were screened before seroconversion. Diagnostic sensitivity (80%) and specificity (79%) of GST were calculated as good for early liver damage caused by HCV. In contrast, the sensitivity of the measurement of other liver enzymes were very weak (SGOT: 8%; SGPT: 10%; GGT: 42%). Conclusion: The significantly higher viraemia of the RT subgroup could be related to the immunosuppressive therapy. Increased GST level may be a useful indicator of tissue damage during HCV infection. If HCV infection is suspected, PCR and GST measurement should be performed, even if anti-HCV result is negative.

The value of urinary cytology in the diagnosis of different pathological conditions in renal transplantation is particularly important. Manual microscopic urinalysis is a high-volume procedure that currently requires significant labour. Objective: To automate the sediment evaluation and to make this more accurate using the Iris Diagnostics Automated Urine Microscopy Analyzer (iQ200). Our goal was to compare the manual and automated microscopic data to apply iQ200 in renal function monitoring. Method: The iQ200 uses digital imaging and Auto Analyte Recognition software to classify urine constituents into 12 analyte categories and quantitatively report. Results: We determined cut-off values of urine particles in every category, which correlated well with manual microscopic results. The iQ200 was more sensitive for pathological casts than manual microscopic analysis. iQ200 helped the operator to differentiate between isomorphic and dismorphic erythrocytes and between lymphocytes and granulocytes, too. Every pathological constituent could be recognized, which is very important for early recognition of renal impairment, graft rejection and urinary tract infection. Conclusions: The iQ200 system automatically classifies 12 particles, significantly reducing the need for additional sample preparation, manual microscopic review achieving a high degree of standardization in urinalysis.

. július 1-jén megalakult a vesetranszplantációs várólista-bizottság. A szerzők a várólista-bizottság működésének a transzplantáció előtti kivizsgálásra gyakorolt hatását kívánták felmérni. A szerzők ismeretei szerint a veseriadó során a szelekciós listán megjelenő betegek alkalmatlanságát elemző tanulmányt még nem közöltek. , 2011, 152, 190-195. Kulcsszavak: vesetranszplantáció, recipiensalkalmasság, várólista Impact of the establishment of waiting list committee on recipient evaluation for kidney transplantation: experience of the Budapest CentreThe aim of this study was to assess the impact of the establishment of waiting list committee on recipient evaluation for kidney transplantation. Studies on this issue have not been previously reported. Methods: Data of 714 patients were collected between September 1, 2007 and April 20, 2010. Of the 714 patients 354 were transplanted. Data from the fi rst 16 months period were compared to those obtained during the second 16 months period. Results: During the fi rst period 171 patients (47.9%) were unfi t for transplantation [129 patients (36.1%) were refused after telephone information and 42 patients (11.8%) after clinical investigation]. During the second period 141 (39.5%) patients were found to be unsuitable [80 patients (22.4%) after telephone information and 61 patients (17.1)] after clinical examination. During the two periods of the study 44% of patients were unfi t for transplantation. A considerable number of patients were refused because of cardiologic reasons. The percent of fi t patients was 52.1% in the fi rst period and 60.5% in the second period. In addition, the percent of unfi t patients who were unsuitable for kidney transplantation after telephone information decreased from 36.1% to 22.4%, while the percent of unfi t patients after clinical evaluation increased from 11.% to 17.1%. Conclusions: Authors conclude that waiting list committee made an effective work. Orv. Hetil., 2011, 152, 190-195.