Schlegel A, Linecker M, Kron P, Györi G, De Oliveira M L, Müllhaupt B, Clavien P-A, Dutkowski P
Department of Surgery and Transplantation, Swiss HPB and Transplant Center, University Hospital Zürich, Zürich, Switzerland.
Department of Gastroenterology and Hepatology, University Hospital Zürich, Zürich, Switzerland.
Am J Transplant. 2017 Apr;17(4):1050-1063. doi: 10.1111/ajt.14065. Epub 2016 Nov 14.
Allocation of liver grafts triggers emotional debates, as those patients, not receiving an organ, are prone to death. We analyzed a high-Model of End-stage Liver Disease (MELD) cohort (laboratory MELD score ≥30, n = 100, median laboratory MELD score of 35; interquartile range 31-37) of liver transplant recipients at our center during the past 10 years and compared results with a low-MELD group, matched by propensity scoring for donor age, recipient age, and cold ischemia time. End points of our study were cumulative posttransplantation morbidity, cost, and survival. Six different prediction models, including donor age x recipient MELD (D-MELD), Difference between listing MELD and MELD at transplant (Delta MELD), donor-risk index (DRI), Survival Outcomes Following Liver Transplant (SOFT), balance-of-risk (BAR), and University of California Los Angeles-Futility Risk Score (UCLA-FRS), were applied in both cohorts to identify risk for poor outcome and high cost. All score models were compared with a clinical-oriented decision, based on the combination of hemofiltration plus ventilation. Median intensive care unit and hospital stays were 8 and 26 days, respectively, after liver transplantation of high-MELD patients, with a significantly increased morbidity compared with low-MELD patients (median comprehensive complication index 56 vs. 36 points [maximum points 100] and double cost [median US$179 631 vs. US$80 229]). Five-year survival, however, was only 8% less than that of low-MELD patients (70% vs. 78%). Most prediction scores showed disappointing low positive predictive values for posttransplantation mortality, such as mortality above thresholds, despite good specificity. The clinical observation of hemofiltration plus ventilation in high-MELD patients was even superior in this respect compared with D-MELD, DRI, Delta MELD, and UCLA-FRS but inferior to SOFT and BAR models. Of all models tested, only the BAR score was linearly associated with complications. In conclusion, the BAR score was most useful for risk classification in liver transplantation, based on expected posttransplantation mortality and morbidity. Difficult decisions to accept liver grafts in high-risk recipients may thus be guided by additional BAR score calculation, to increase the safe use of scarce organs.
肝移植供体的分配引发了激烈的情感辩论，因为那些没有获得器官的患者极易死亡。我们分析了本中心过去10年中终末期肝病模型（MELD）评分较高的肝移植受者队列（实验室MELD评分≥30，n = 100，实验室MELD评分中位数为35；四分位间距为31 - 37），并将结果与通过对供体年龄、受者年龄和冷缺血时间进行倾向评分匹配的低MELD组进行比较。我们研究的终点是移植后的累积发病率、成本和生存率。六种不同的预测模型，包括供体年龄×受者MELD（D - MELD）、登记MELD与移植时MELD的差值（Delta MELD）、供体风险指数（DRI）、肝移植后生存结果（SOFT）、风险平衡（BAR）和加利福尼亚大学洛杉矶分校 - 无效风险评分（UCLA - FRS），应用于两个队列，以确定不良结局和高成本的风险。所有评分模型都与基于血液滤过加通气联合的临床导向决策进行了比较。高MELD患者肝移植后，重症监护病房和住院时间的中位数分别为8天和26天，与低MELD患者相比，发病率显著增加（综合并发症指数中位数为56分对36分[满分100分]，成本翻倍[中位数分别为179,631美元对80,229美元]）。然而，五年生存率仅比低MELD患者低8%（70%对78%）。大多数预测评分对移植后死亡率的阳性预测值较低，令人失望，例如高于阈值的死亡率，尽管特异性良好。在这方面，高MELD患者血液滤过加通气的临床观察甚至优于D - MELD、DRI、Delta MELD和UCLA - FRS，但不如SOFT和BAR模型。在所有测试模型中，只有BAR评分与并发症呈线性相关。总之，基于预期的移植后死亡率和发病率，BAR评分在肝移植风险分类中最有用。因此，在高风险受者中接受肝移植的艰难决策可能通过额外计算BAR评分来指导，以增加稀缺器官的安全使用。
