Department of Nephrology, The Affiliated Hospital of Qingdao University, Qingdao, China.
Ren Fail. 2021 Dec;43(1):1588-1600. doi: 10.1080/0886022X.2021.2009863.
We aim to develop and validate a nomogram model for predicting severe acute kidney injury (AKI) after orthotopic liver transplantation (OLT).
A total of 576 patients who received OLT in our center were enrolled. They were assigned to the development and validation cohort according to the time of inclusion. Univariable and multivariable logistic regression using the forward variable selection routine were applied to find risk factors for post-OLT severe AKI. Based on the results of multivariable analysis, a nomogram was developed and validated. Patients were followed up to assess the long-term mortality and development of chronic kidney disease (CKD).
Overall, 35.9% of patients were diagnosed with severe AKI. Multivariable logistic regression analysis revealed that recipients' BMI (OR 1.10, 95% CI 1.04-1.17, = 0.012), hypertension (OR 2.32, 95% CI 1.22-4.45, = 0.010), preoperative serum creatine (sCr) (OR 0.96, 95% CI 0.95-0.97, < 0.001), and intraoperative fresh frozen plasm (FFP) transfusion (OR for each 1000 ml increase 1.34, 95% CI 1.03-1.75, = 0.031) were independent risk factors for post-OLT severe AKI. They were all incorporated into the nomogram. The area under the ROC curve (AUC) was 0.73 ( < 0.05) and 0.81 ( < 0.05) in the development and validation cohort. The calibration curve demonstrated the predicted probabilities of severe AKI agreed with the observed probabilities ( > 0.05). Kaplan-Meier survival analysis showed that patients in the high-risk group stratified by the nomogram suffered significantly poorer long-term survival than the low-risk group (HR 1.92, < 0.01). The cumulative risk of CKD was higher in the severe AKI group than no severe AKI group after competitive risk analysis (HR 1.48, < 0.05).
With excellent predictive abilities, the nomogram may be a simple and reliable tool to identify patients at high risk for severe AKI and poor long-term prognosis after OLT.
我们旨在开发和验证一种列线图模型,用于预测原位肝移植(OLT)后严重急性肾损伤(AKI)。
共纳入 576 例在我院接受 OLT 的患者。根据纳入时间将其分配至开发和验证队列。采用向前变量选择常规的单变量和多变量逻辑回归分析来寻找 OLT 后严重 AKI 的风险因素。基于多变量分析的结果,开发并验证了一个列线图。对患者进行随访以评估长期死亡率和慢性肾脏病(CKD)的发生情况。
总体而言,35.9%的患者被诊断为严重 AKI。多变量逻辑回归分析显示,受者 BMI(比值比 1.10,95%可信区间 1.04-1.17, = 0.012)、高血压(比值比 2.32,95%可信区间 1.22-4.45, = 0.010)、术前血清肌酐(sCr)(比值比 0.96,95%可信区间 0.95-0.97, < 0.001)和术中新鲜冷冻血浆(FFP)输注(每输注 1000 ml 增加 1.34,95%可信区间 1.03-1.75, = 0.031)是 OLT 后严重 AKI 的独立风险因素。所有因素均纳入列线图。ROC 曲线下面积(AUC)在开发和验证队列中分别为 0.73( < 0.05)和 0.81( < 0.05)。校准曲线表明,严重 AKI 的预测概率与观察到的概率相符( > 0.05)。Kaplan-Meier 生存分析显示,根据列线图分层的高危组患者的长期生存明显差于低危组(风险比 1.92, < 0.01)。竞争风险分析后,严重 AKI 组的 CKD 累积风险高于无严重 AKI 组(风险比 1.48, < 0.05)。
该列线图具有良好的预测能力,可能是一种简单可靠的工具,可用于识别 OLT 后发生严重 AKI 和预后不良的高危患者。