Desai Niraj M, Mange Kevin C, Crawford Michael D, Abt Peter L, Frank Adam M, Markmann Joseph W, Velidedeoglu Ergun, Chapman William C, Markmann James F
Department of Surgery, Washington University School of Medicine, St. Louis, Missouri, USA.
Transplantation. 2004 Jan 15;77(1):99-106. doi: 10.1097/01.TP.0000101009.91516.FC.
The Model for End-Stage Liver Disease (MELD) has been found to accurately predict pretransplant mortality and is a valuable system for ranking patients in greatest need of liver transplantation. It is unknown whether a higher MELD score also predicts decreased posttransplant survival.
We examined a cohort of patients from the United Network for Organ Sharing (UNOS) database for whom the critical pretransplant recipient values needed to calculate the MELD score were available (international normalized ratio of prothrombin time, total bilirubin, and creatinine). In these 2,565 patients, we analyzed whether the MELD score predicted graft and patient survival and length of posttransplant hospitalization.
In contrast with its ability to predict survival in patients with chronic liver disease awaiting liver transplant, the MELD score was found to be poor at predicting posttransplant outcome except for patients with the highest 20% of MELD scores. We developed a model with four variables not included in MELD that had greater ability to predict 3-month posttransplant patient survival, with a c-statistic of 0.65, compared with 0.54 for the pretransplant MELD score. These pretransplant variables were recipient age, mechanical ventilation, dialysis, and retransplantation. Recipients with any two of the three latter variables showed a markedly diminished posttransplant survival rate.
The MELD score is a relatively poor predictor of posttransplant outcome. In contrast, a model based on four pretransplant variables (recipient age, mechanical ventilation, dialysis, and retransplantation) had a better ability to predict outcome. Our results support the use of MELD for liver allocation and indicate that statistical modeling, such as reported in this article, can be used to identify futile cases in which expected outcome is too poor to justify transplantation.
终末期肝病模型（MELD）已被证实能准确预测肝移植前死亡率，是对最急需肝移植患者进行排序的重要系统。目前尚不清楚较高的MELD评分是否也预示着肝移植后生存率降低。
我们研究了器官共享联合网络（UNOS）数据库中的一组患者，这些患者可获取计算MELD评分所需的关键肝移植前受者数值（凝血酶原时间国际标准化比值、总胆红素和肌酐）。在这2565例患者中，我们分析了MELD评分是否能预测移植物和患者生存率以及肝移植后住院时间。
与MELD评分预测等待肝移植的慢性肝病患者生存率的能力不同，研究发现，除了MELD评分最高的20%患者外，MELD评分在预测肝移植后结局方面表现不佳。我们建立了一个包含四个MELD未纳入变量的模型，该模型预测肝移植后3个月患者生存率的能力更强，c统计量为0.65，而移植前MELD评分为0.54。这些移植前变量为受者年龄、机械通气、透析和再次移植。后三个变量中出现任意两个的受者，其移植后生存率显著降低。
MELD评分对肝移植后结局的预测能力相对较差。相比之下，基于四个移植前变量（受者年龄、机械通气、透析和再次移植）的模型预测结局的能力更强。我们的研究结果支持使用MELD进行肝脏分配，并表明本文报道的统计建模可用于识别预期结局太差而不值得进行移植的无效病例。
