Yuan Ding1,2,3,4,5, Tianchun Wu1,2,3,4,5, Wenyan Zhang6, Sitong Zhang1,2,3,4,5, Weilin Wang1,2,3,4,5. 1. Department of Hepatobiliary and Pancreatic Surgery, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310009, China. 2. Key Laboratory of Precision Diagnosis and Treatment for Hepatobiliary and Pancreatic Tumor of Zhejiang Province, Hangzhou 310009, China. 3. Research Center of Diagnosis and Treatment Technology for Hepatocellular Carcinoma of Zhejiang Province, Hangzhou 310009, China. 4. Clinical Medicine Innovation Center of Precision Diagnosis and Treatment for Hepatobiliary and Pancreatic Disease of Zhejiang University, Hangzhou 310009, China. 5. Clinical Research Center of Hepatobiliary and Pancreatic Diseases of Zhejiang Province, Hangzhou 310009, China. 6. Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310009, China.
Abstract
BACKGROUND: In the model for end-stage liver disease (MELD) score, renal function was well thought to be associated with the prognosis of liver recipients. Serum cystatin C (CystC)-based equations were considered more accurate for calculating estimated glomerular filtration rate (eGFR) than creatinine (Pcr) based equations. Thus, we aimed to assess the association between eGFR estimated by chronic kidney disease epidemiology collaboration (CKD-EPI)-CystC equation and post-transplantation mortality. METHODS: From January 2015 to January 2018, prior to liver transplantation (LT) and other clinical parameters, CystC was collected in all 307 consecutive patients who underwent LT at our center. Patients were divided into four groups according to the Kidney Disease Outcomes Quality Initiative (KDOQI) classification. RESULTS: Based on CKD-EPI-CystC and the KDOQI classification, 117 patients (38.1%) were stage I, 76 (24.8%) were stage II, 85 (27.7%) were stage III, and 29 (9.4%) were stage IV-V. After univariate and multivariate analysis, MELD score [hazard ratio (HR) =1.035; 95% confidence interval (CI), 1.006-1.066; P=0.018], associated HCC (HR =2.314; 95% CI, 1.253-4.273; P=0.007), and KDOQI stage III (HR =1.850; 95% CI, 1.001-3.419; P=0.049), and stage IV-V (HR =3.915; 95% CI, 1.843-8.316; P<0.001) according to CKD-EPI-CystC equation were confirmed to be independent prognostic factors for post-LT survival. CONCLUSIONS: The pretransplant renal function evaluated by serum CystC was associated with mortality after LT and could be used for predicting post-transplant survival.
BACKGROUND: In the model for end-stage liver disease (MELD) score, renal function was well thought to be associated with the prognosis of liver recipients. Serum cystatin C (CystC)-based equations were considered more accurate for calculating estimated glomerular filtration rate (eGFR) than creatinine (Pcr) based equations. Thus, we aimed to assess the association between eGFR estimated by chronic kidney disease epidemiology collaboration (CKD-EPI)-CystC equation and post-transplantation mortality. METHODS: From January 2015 to January 2018, prior to liver transplantation (LT) and other clinical parameters, CystC was collected in all 307 consecutive patients who underwent LT at our center. Patients were divided into four groups according to the Kidney Disease Outcomes Quality Initiative (KDOQI) classification. RESULTS: Based on CKD-EPI-CystC and the KDOQI classification, 117 patients (38.1%) were stage I, 76 (24.8%) were stage II, 85 (27.7%) were stage III, and 29 (9.4%) were stage IV-V. After univariate and multivariate analysis, MELD score [hazard ratio (HR) =1.035; 95% confidence interval (CI), 1.006-1.066; P=0.018], associated HCC (HR =2.314; 95% CI, 1.253-4.273; P=0.007), and KDOQI stage III (HR =1.850; 95% CI, 1.001-3.419; P=0.049), and stage IV-V (HR =3.915; 95% CI, 1.843-8.316; P<0.001) according to CKD-EPI-CystC equation were confirmed to be independent prognostic factors for post-LT survival. CONCLUSIONS: The pretransplant renal function evaluated by serum CystC was associated with mortality after LT and could be used for predicting post-transplant survival.
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