A single-center analysis to evaluate kidney function parameters after liver transplantation in adult patients.

Severe renal dysfunction may occur after orthotopic liver transplantation (OLT). In this study, we retrospectively analyzed a single-center series of adult liver recipients (n = 62) seeking to identify patients prone to develop renal dysfunction during follow-up. Liver recipients (age range, 53.54 ± 8.19 years; female/male: 21/41) who underwent a first OLT from a brain dead donor were enrolled according to strict criteria. We enrolled only liver recipients with 5 serum creatinine (SCr) measurements after hospital discharge and at least 1 measurement/year with a follow-up period of not less than 2 years. We estimated glomerular filtration rate (eGFR) using the formula developed by the Mayo Clinic. The average rate of SCr change after OLT was 0.0065 ± 0.013 mg/dL/mo. By calculating the per-patient slope, the average rate of SCr change was 0.000165 ± 0.000383 mg/dL (0.000007 ± 0.000017 mg/dL/mo). In regression models evaluated with SCr as the dependent variable versus post-OLT time, no significance was observed (P = .130). The average rate of eGFR change after OLT was −0.462 ± 0.883 mL/min/mo. By calculating the per-patient slope, the average rate of eGFR change was −0.009 ± 0.0026 mL/min (−0.0004 ± 0.0012 mL/min/mo). In the regression models evaluated with eGFR as dependent variable versus post-OLT time, no significance occurred (P = .168). By applying the regression prediction to SCr at 3 to 5 versus the 1 to 2 post-OLT measurements, we noted 3 male liver recipients (MLR) whose SCr values were significantly higher than the predicted values: MLR1: P = .048 at measurement 4; MLR2: P = .019 at measurement 4; and MLR3: P = .017 at measurement 5. Conversely, we did not observed a significant difference between observed versus predicted eGFR values. Clinical decisions on immunosuppressive treatments for liver recipients should be determined also on the basis of the series of post-OLT kidney function, which should be studied with rigorous evaluation of fitted regression models.