World J Surg. 2013 Nov;37(11):2618-28. doi: 10.1007/s00268-013-2159-6.
A recently published score predicts the occurrence of acute kidney injury (AKI) after liver resection based on preoperative parameters (chronic renal failure, cardiovascular disease, diabetes, and alanine-aminotransferase levels). By inclusion of additional intraoperative parameters we aimed to develop a new prediction model.
A series of 549 consecutive patients were enrolled. The preoperative score and intraoperative parameters (blood transfusion, hepaticojejunostomy, oliguria, cirrhosis, diuretics, colloids, and catecholamine) were included in a multivariate logistic regression model. We added the strongest predictors that improved prediction of AKI compared to the existing score. An internal validation by fivefold cross validation was performed, followed by a decision curve analysis to evaluate unnecessary special care unit admissions.
Blood transfusions, hepaticojejunostomy, and oliguria were the strongest intraoperative predictors of AKI after liver resection. The new score ranges from 0 to 64 points predicting postoperative AKI with a probability of 3.5–95 %. Calibration was good in both models (15 % predicted risk vs. 15 % observed risk). The fivefold cross-validation indicated good accuracy of the new model (AUC 0.79 (95 % CI 0.73–0.84)). Discrimination was substantially higher in the new model (AUCnew 0.81 (95 % CI 0.76–0.86) versus AUCpreoperative 0.60 (95 % CI 0.52–0.69), p < 0.001). The new score could reduce up to 84 unnecessary special care unit admissions per 100 patients depending on the decision threshold.
By combining three intraoperative parameters with the existing preoperative risk score, a new prediction model was developed that more accurately predicts postoperative AKI. It may reduce unnecessary admissions to the special care unit and support management of patients at higher risk.
最近发表的一项评分标准可以根据术前参数（慢性肾衰竭、心血管疾病、糖尿病和丙氨酸氨基转移酶水平）预测肝切除术后急性肾损伤（AKI）的发生。通过纳入更多的术中参数，我们旨在开发一种新的预测模型。
纳入了 549 例连续患者。将术前评分和术中参数（输血、胆肠吻合术、少尿、肝硬化、利尿剂、胶体和儿茶酚胺）纳入多变量逻辑回归模型。我们添加了最强的预测因子，这些预测因子与现有评分相比可以提高 AKI 的预测能力。通过五分交叉验证进行内部验证，然后进行决策曲线分析以评估不必要的特殊护理病房入院。
输血、胆肠吻合术和少尿是肝切除术后 AKI 的最强术中预测因子。新评分范围为 0 至 64 分，预测术后 AKI 的概率为 3.5%至 95%。两种模型的校准均良好（预测风险为 15%与观察风险为 15%）。五分交叉验证表明新模型具有良好的准确性（AUC 为 0.79（95%CI 为 0.73-0.84））。新模型的判别能力明显更高（AUCnew 为 0.81（95%CI 为 0.76-0.86），AUCpreoperative 为 0.60（95%CI 为 0.52-0.69），p<0.001）。根据决策阈值，新评分可减少每 100 例患者中多达 84 例不必要的特殊护理病房入院。
通过将三个术中参数与现有的术前风险评分相结合，开发了一种新的预测模型，该模型可以更准确地预测术后 AKI。它可以减少不必要的特殊护理病房入院，并支持对高危患者的管理。
