Yang L, Xin E Y, Liao B, Lai L J, Han M, Wang X P, Ju W Q, Wang D P, Guo Z Y, He X S
Organ Transplant Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China; Guangdong Provincial Key Laboratory of Organ Donation and Transplant Immunology, Guangzhou, China; Guangdong Provincial International Cooperation Base of Science and Technology, Guangzhou, China.
Guangdong Provincial Key Laboratory of Organ Donation and Transplant Immunology, Guangzhou, China; Guangdong Provincial International Cooperation Base of Science and Technology, Guangzhou, China; Pathology Department, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Transplant Proc. 2017 Jul-Aug;49(6):1357-1363. doi: 10.1016/j.transproceed.2017.03.083.
Early allograft dysfunction (EAD) is frequent complication post-liver transplantation and is closely related to recipient's mortality and morbidity. We sought to develop a nomogram for predicting incidence of EAD.
Based on multivariate analysis of donor, recipient, and operation data of 199 liver transplants from deceased donors between 2013 and 2015, we identified 5 significant risk factors for EAD to build a nomogram. The model was subjected to prospective validation with a cohort of 42 patients who was recruited between January and June 2016. The predictive accuracy and discriminative ability were measured by area under the receiver operating characteristic curve (AUC). The agreement between nomogram prediction and actual observation was showed by the calibration curve.
Incidence rate of EAD in the training set and validation cohort were 55.91% (104/199) and 54.76% (23/42), respectively. In the training set, according to the results of univariable and multivariable analysis, 5 independent risk factors including donor gender, donor serum gamma-glutamyl transpeptidase level, donor serum urea level, donor comorbidities (respiratory, cardiac, and renal dysfunction), and recipient Model for End-stage Liver Disease score were identified and assembled into the nomogram. The AUC of internal validation using bootstrap resampling and prospective validation using the external cohort of 42 patients was 0.74 and 0.60, respectively. The calibration curves for probability of EAD showed acceptable agreement between nomogram prediction and actual observation. According to the score table, the probability of EAD was under 30% when the total point tally was under 72. But when the total was up to 139, the risk of EAD increased to 60%.
We've established and validated a nomogram that can provide individual prediction of EAD for liver transplant recipients. The practical prognostic model may help clinicians to qualify the liver graft accurately, making a more reasonable allocation of organs.
早期移植肝功能障碍（EAD）是肝移植术后常见的并发症，与受者的死亡率和发病率密切相关。我们试图建立一个预测EAD发生率的列线图。
基于对2013年至2015年间199例脑死亡供者肝移植的供者、受者及手术数据进行多变量分析，我们确定了5个EAD的显著危险因素以构建列线图。该模型在2016年1月至6月招募的42例患者队列中进行前瞻性验证。预测准确性和判别能力通过受试者操作特征曲线下面积（AUC）来衡量。校准曲线显示了列线图预测与实际观察之间的一致性。
训练集和验证队列中EAD的发生率分别为55.91%（104/199）和54.76%（23/42）。在训练集中，根据单变量和多变量分析结果，确定了5个独立危险因素，包括供者性别、供者血清γ-谷氨酰转肽酶水平、供者血清尿素水平、供者合并症（呼吸、心脏和肾功能不全）以及受者终末期肝病模型评分，并将其纳入列线图。使用自举重采样进行内部验证以及使用42例患者的外部队列进行前瞻性验证的AUC分别为0.74和0.60。EAD概率的校准曲线显示列线图预测与实际观察之间具有可接受的一致性。根据评分表，当总分低于72分时，EAD的概率低于30%。但当总分高达139分时，EAD的风险增加到60%。
我们建立并验证了一个可为肝移植受者提供EAD个体预测的列线图。这个实用的预后模型可能有助于临床医生准确评估肝移植供肝，更合理地分配器官。
