Department of Cardiothoracic Surgery, Monash Medical Centre, and Department of Surgery, Monash University Faculty of Medicine, Nursing and Health Sciences, Melbourne, Australia.
Department of Epidemiology and Preventive Medicine, Monash University Faculty of Medicine, Nursing and Health Sciences, Melbourne, Australia.
J Thorac Cardiovasc Surg. 2014 Jun;147(6):1875-83, 1883.e1. doi: 10.1016/j.jtcvs.2013.06.049. Epub 2013 Aug 28.
To predict acute kidney injury after cardiac surgery.
The study included 28,422 cardiac surgery patients who had had no preoperative renal dialysis from June 2001 to June 2009 in 18 hospitals. Logistic regression analyses were undertaken to identify the best combination of risk factors for predicting acute kidney injury. Two models were developed, one including the preoperative risk factors and another including the pre-, peri-, and early postoperative risk factors. The area under the receiver operating characteristic curve was calculated, using split-sample internal validation, to assess model discrimination.
The incidence of acute kidney injury was 5.8% (1642 patients). The mortality for patients who experienced acute kidney injury was 17.4% versus 1.6% for patients who did not. On validation, the area under the curve for the preoperative model was 0.77, and the Hosmer-Lemeshow goodness-of-fit P value was .06. For the postoperative model area under the curve was 0.81 and the Hosmer-Lemeshow P value was .6. Both models had good discrimination and acceptable calibration.
Acute kidney injury after cardiac surgery can be predicted using preoperative risk factors alone or, with greater accuracy, using pre-, peri-, and early postoperative risk factors. The ability to identify high-risk individuals can be useful in preoperative patient management and for recruitment of appropriate patients to clinical trials. Prediction in the early stages of postoperative care can guide subsequent intensive care of patients and could also be the basis of a retrospective performance audit tool.
预测心脏手术后急性肾损伤。
本研究纳入了 2001 年 6 月至 2009 年 6 月间 18 家医院的 28422 例无术前肾脏透析的心脏手术患者。采用逻辑回归分析确定预测急性肾损伤的最佳风险因素组合。建立了两种模型，一种包括术前风险因素，另一种包括术前、术中和术后早期的风险因素。采用分割样本内部验证计算受试者工作特征曲线下面积，以评估模型的区分度。
急性肾损伤的发生率为 5.8%（1642 例）。发生急性肾损伤的患者死亡率为 17.4%，而未发生急性肾损伤的患者死亡率为 1.6%。在验证中，术前模型的曲线下面积为 0.77，Hosmer-Lemeshow 拟合优度 P 值为 0.06。术后模型的曲线下面积为 0.81，Hosmer-Lemeshow P 值为 0.6。两个模型均具有良好的区分度和可接受的校准度。
心脏手术后急性肾损伤可单独使用术前风险因素进行预测，或使用更准确的术前、术中和术后早期风险因素进行预测。识别高危个体的能力可用于术前患者管理，并为招募合适的患者参加临床试验提供依据。术后早期护理的预测可指导患者的后续重症监护，也可作为回顾性绩效审计工具的基础。
