Xin Qi, Xie Tonghui, Chen Rui, Zhang Xing, Tong Yingmu, Wang Hai, Wang Shufeng, Liu Chang, Zhang Jingyao
Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, People's Republic of China.
Department of General Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, People's Republic of China.
J Inflamm Res. 2022 Aug 11;15:4561-4571. doi: 10.2147/JIR.S372246. eCollection 2022.
Sepsis-induced acute kidney injury (S-AKI) is associated with systemic inflammatory responses and coagulation system dysfunction, and it is associated with an increased risk of mortality. However, there was no study to explore the predictive value of inflammatory and coagulation indicators for S-AKI.
In this retrospective study, 1051 sepsis patients were identified and divided into a training cohort (75%, n = 787) and a validation cohort (25%, n = 264) in chronological order according to the date they were admitted. Univariate analyses and multivariate logistic regression analyses were performed to identify the independent predictors of S-AKI. The logistic regression analyses (enter methods) were used to conducted the prediction models. The ROC curves were used to determine the predictive value of the constructed models on S-AKI. To test whether the increase in the AUC is significant, we used a two-sided test for ROC curves available online (http://vassarstats.net/roc_comp.html). The secondary outcome was different AKI stages and major adverse kidney events within 30 days (MAKE30). Stage 3B of S-AKI was defined as both meeting the stage 3 criteria [increase of Cr level by > 300% (≥ 4.0 mg/dL with an acute increase of ≥ 0.5 mg/dL) and/or UO < 0.3 mL/kg/h for > 24 h or anuria for > 12 h and/or acute kidney replacement therapy] and having cystatin C positive. MAKE30 were a composite of death, new renal replacement therapy (RRT), or persistent renal dysfunction (PRD).
We discovered that cardiovascular disease, white blood cell (WBC), mean arterial pressure (MAP), platelet (PLT), serum procalcitonin (PCT), prothrombin time activity (PTA), and thrombin time (TT) were independent predictors for S-AKI. The predictive value (AUC = 0.855) of the simplest model 3 (constructed with PLT, PCT, and PTA), with a sensitivity of 77.6% and a specificity of 82.4%, had a similar predictive value comparing with the model 1 (AUC = 0.872) and the model 2 (AUC = 0.864) in the training cohort (P > 0.05). Compared with the model 1 (AUC = 0.888) and the model 2 (AUC = 0.887), the model 3 (AUC = 0.887) had a similar predictive value in the validation cohort. Moreover, model 3 had the best predictive power for predicting S-AKI in the stage 3 (AUC = 0.777), especially in stage 3B (AUC = 0.771). Finally, the model 3 (AUC = 0.843) had perfect predictive power for predicting MAKE30 in sepsis patients.
Within 24 hours after admission, the simplest model 3 (constructed with PLT, PCT, and PTA) might be a robust predictor of the S-AKI in sepsis patients, providing information for timely and efficient intervention.
脓毒症诱导的急性肾损伤（S-AKI）与全身炎症反应和凝血系统功能障碍相关，且与死亡风险增加有关。然而，尚无研究探讨炎症和凝血指标对S-AKI的预测价值。
在这项回顾性研究中，共纳入1051例脓毒症患者，并根据入院日期按时间顺序分为训练队列（75%，n = 787）和验证队列（25%，n = 264）。进行单因素分析和多因素逻辑回归分析以确定S-AKI的独立预测因素。采用逻辑回归分析（逐步法）构建预测模型。使用ROC曲线确定所构建模型对S-AKI的预测价值。为检验AUC的增加是否显著，我们使用在线提供的ROC曲线双侧检验（http://vassarstats.net/roc_comp.html）。次要结局为不同的急性肾损伤阶段以及30天内的主要不良肾脏事件（MAKE30）。S-AKI的3B期定义为同时符合3期标准[肌酐水平升高>300%（≥4.0mg/dL且急性升高≥0.5mg/dL）和/或尿量<0.3mL/kg/h持续>24小时或无尿>超过12小时和/或接受急性肾脏替代治疗]且胱抑素C阳性。MAKE30是死亡、新的肾脏替代治疗（RRT）或持续性肾功能不全（PRD）的综合指标。
我们发现心血管疾病、白细胞（WBC）、平均动脉压（MAP）、血小板（PLT）、血清降钙素原（PCT）、凝血酶原时间活动度（PTA）和凝血酶时间（TT）是S-AKI的独立预测因素。最简单的模型3（由PLT、PCT和PTA构建）的预测价值（AUC = 0.855），灵敏度为77.6%，特异度为82.4%，在训练队列中与模型1（AUC = 0.872）和模型2（AUC = 0.864）的预测价值相似（P>0.05）。与模型1（AUC = 0.888）和模型2（AUC = 0.887）相比，模型3（AUC = 0.887）在验证队列中的预测价值相似。此外，模型3对3期S-AKI（AUC = 0.777），尤其是3B期（AUC = 0.771）具有最佳预测能力。最后，模型3（AUC = 0.843）对预测脓毒症患者的MAKE30具有理想的预测能力。
入院后24小时内，最简单的模型3（由PLT、PCT和PTA构建）可能是脓毒症患者S-AKI的可靠预测指标，可为及时有效的干预提供信息。
