Yao Xiuying, Zhang Lixiang, Huang Lei, Chen Xia, Geng Li, Xu Xu
Department of Intensive Care Unit, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230036, People's Republic of China.
Department of Nursing DepartmeThe First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230036, People's Republic of China.
Risk Manag Healthc Policy. 2021 Nov 2;14:4457-4468. doi: 10.2147/RMHP.S321399. eCollection 2021.
To analyze the risk factors of in-hospital death in patients with acute kidney injury (AKI) in the intensive care unit (ICU), and to develop a personalized risk prediction model.
The clinical data of 137 AKI patients hospitalized in the ICU of Anhui provincial hospital from January 2018 to December 2020 were retrospectively analyzed. Patients were divided into two groups: those that survived to discharge ("survival" group, 100 cases) and those that died while in hospital ("death" group, 37 cases), and risk factors for in-hospital death analyzed.
The in-hospital mortality of AKI patients in the ICU was 27.01% (37/137). A multivariate logistic regression analysis indicated age, mechanical ventilation and vasoactive drugs were significant risk factors for in-hospital death in AKI patients, and a nomogram risk prediction model was developed. The Harrell's C-index of the nomogram model was 0.891 (95% CI: 0.837-0.945), and the area under the receiver operating characteristic (ROC) curve was 0.886 (95% CI: 0.823-0.936) after internal validation, indicating that the nomogram model had good discrimination. The Hosmer-Lemeshow goodness of fit test and calibration curve indicated the predicted probability of the nomogram model was consistent with the actual frequency of death in ICU patients with AKI. The decision curve analysis (DCA) showed that the clinical net benefit level of the nomogram model is highest when the probability threshold of AKI is between 0.01 and 0.75.
Patients in the ICU with AKI had high in-hospital mortality and were affected by a variety of risk factors. The nomogram prediction model based on the risk factors of AKI showed good prediction efficiency and clinical applicability, which could help medical staff in the ICU to identify AKI patients with high-risk, allowing early prevention, detection and intervention, and reducing the risk of in-hospital deaths in ICU patients with AKI.
分析重症监护病房（ICU）中急性肾损伤（AKI）患者院内死亡的危险因素，并建立个性化风险预测模型。
回顾性分析2018年1月至2020年12月在安徽省立医院ICU住院的137例AKI患者的临床资料。将患者分为两组：存活至出院的患者（“存活”组，100例）和住院期间死亡的患者（“死亡”组，37例），分析院内死亡的危险因素。
ICU中AKI患者的院内死亡率为27.01%（37/137）。多因素logistic回归分析表明，年龄、机械通气和血管活性药物是AKI患者院内死亡的显著危险因素，并建立了列线图风险预测模型。列线图模型的Harrell's C指数为0.891（95%CI：0.837-0.945），内部验证后受试者操作特征（ROC）曲线下面积为0.886（95%CI：0.823-0.936），表明列线图模型具有良好的区分度。Hosmer-Lemeshow拟合优度检验和校准曲线表明，列线图模型的预测概率与ICU中AKI患者的实际死亡频率一致。决策曲线分析（DCA）显示，当AKI的概率阈值在0.01至0.75之间时，列线图模型的临床净效益水平最高。
ICU中患有AKI的患者院内死亡率高，且受多种危险因素影响。基于AKI危险因素的列线图预测模型显示出良好的预测效率和临床适用性，可帮助ICU医护人员识别高危AKI患者，实现早期预防、检测和干预，降低ICU中AKI患者的院内死亡风险。
