Chung Hyun Sik, Lee Yu Jung, Jo Yun Sung
Department of Anesthesiology and Pain Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea.
Department of Obstetrics and Gynecology, College of Medicine, St. Vincent's Hospital, The Catholic University of Korea, Seoul, South Korea.
Ann Transplant. 2017 Feb 21;22:101-107. doi: 10.12659/aot.901771.
BACKGROUND Acute liver failure (ALF) is known to be a rapidly progressive and fatal disease. Various models which could help to estimate the post-transplant outcome for ALF have been developed; however, none of them have been proved to be the definitive predictive model of accuracy. We suggest a new predictive model, and investigated which model has the highest predictive accuracy for the short-term outcome in patients who underwent living donor liver transplantation (LDLT) due to ALF. MATERIAL AND METHODS Data from a total 88 patients were collected retrospectively. King's College Hospital criteria (KCH), Child-Turcotte-Pugh (CTP) classification, and model for end-stage liver disease (MELD) score were calculated. Univariate analysis was performed, and then multivariate statistical adjustment for preoperative variables of ALF prognosis was performed. A new predictive model was developed, called the MELD conjugated serum phosphorus model (MELD-p). The individual diagnostic accuracy and cut-off value of models in predicting 3-month post-transplant mortality were evaluated using the area under the receiver operating characteristic curve (AUC). The difference in AUC between MELD-p and the other models was analyzed. The diagnostic improvement in MELD-p was assessed using the net reclassification improvement (NRI) and integrated discrimination improvement (IDI). RESULTS The MELD-p and MELD scores had high predictive accuracy (AUC >0.9). KCH and serum phosphorus had an acceptable predictive ability (AUC >0.7). The CTP classification failed to show discriminative accuracy in predicting 3-month post-transplant mortality. The difference in AUC between MELD-p and the other models had statistically significant associations with CTP and KCH. The cut-off value of MELD-p was 3.98 for predicting 3-month post-transplant mortality. The NRI was 9.9% and the IDI was 2.9%. CONCLUSIONS MELD-p score can predict 3-month post-transplant mortality better than other scoring systems after LDLT due to ALF. The recommended cut-off value of MELD-p is 3.98.
背景 急性肝衰竭（ALF）是一种进展迅速的致命性疾病。目前已开发出多种有助于评估ALF患者移植后预后的模型；然而，尚无一种模型被证明是具有准确性的确定性预测模型。我们提出了一种新的预测模型，并研究了哪种模型对因ALF接受活体肝移植（LDLT）患者的短期预后具有最高的预测准确性。
材料与方法 回顾性收集了总共88例患者的数据。计算了国王学院医院标准（KCH）、Child-Turcotte-Pugh（CTP）分级和终末期肝病模型（MELD）评分。进行单因素分析，然后对ALF预后的术前变量进行多因素统计调整。开发了一种新的预测模型，称为MELD结合血清磷模型（MELD-p）。使用受试者操作特征曲线下面积（AUC）评估各模型预测移植后3个月死亡率的个体诊断准确性和临界值。分析了MELD-p与其他模型之间AUC的差异。使用净重新分类改善（NRI）和综合辨别改善（IDI）评估MELD-p的诊断改善情况。
结果 MELD-p和MELD评分具有较高的预测准确性（AUC>0.9）。KCH和血清磷具有可接受的预测能力（AUC>0.7）。CTP分级在预测移植后3个月死亡率方面未能显示出鉴别准确性。MELD-p与其他模型之间AUC的差异与CTP和KCH具有统计学显著相关性。预测移植后3个月死亡率的MELD-p临界值为3.98。NRI为9.9%，IDI为2.9%。
结论 MELD-p评分在预测因ALF接受LDLT患者移植后3个月死亡率方面优于其他评分系统。MELD-p的推荐临界值为3.98。
