Division of Perioperative Informatics, Department of Anesthesiology, University of California San Diego, 200 West Arbor Drive, San Diego, CA, 80203, USA.
Division of Surgical Oncology, Department of Surgery, University of California San Diego, San Diego, CA, USA.
Sci Rep. 2024 Mar 19;14(1):6630. doi: 10.1038/s41598-024-54979-w.
Acute kidney injury (AKI) following hyperthermic intraperitoneal chemotherapy (HIPEC) is common. Identifying patients at risk could have implications for surgical and anesthetic management. We aimed to develop a predictive model that could predict AKI based on patients' preoperative characteristics and intraperitoneal chemotherapy regimen. We retrospectively gathered data of adult patients undergoing HIPEC at our health system between November 2013 and April 2022. Next, we developed a model predicting postoperative AKI using multivariable logistic regression and calculated the performance of the model (area under the receiver operating characteristics curve [AUC]) via tenfold cross-validation. A total of 412 patients were included, of which 36 (8.7%) developed postoperative AKI. Based on our multivariable logistic regression model, multiple preoperative and intraoperative characteristics were associated with AKI. We included the total intraoperative cisplatin dose, body mass index, male sex, and preoperative hemoglobin level in the final model. The mean area under the receiver operating characteristics curve value was 0.82 (95% confidence interval 0.71-0.93). Our risk model predicted AKI with high accuracy in patients undergoing HIPEC in our institution. The external validity of our model should now be tested in independent and prospective patient cohorts.
高热腹腔内化疗（HIPEC）后急性肾损伤（AKI）很常见。识别有风险的患者可能对手术和麻醉管理有影响。我们旨在开发一种预测模型，该模型可以根据患者的术前特征和腹腔内化疗方案预测 AKI。我们回顾性地收集了 2013 年 11 月至 2022 年 4 月在我们医疗系统接受 HIPEC 的成年患者的数据。接下来，我们使用多变量逻辑回归开发了一种预测术后 AKI 的模型，并通过十折交叉验证计算了模型的性能（接受者操作特征曲线下的面积 [AUC]）。共纳入 412 例患者，其中 36 例（8.7%）发生术后 AKI。基于我们的多变量逻辑回归模型，多个术前和术中特征与 AKI 相关。我们最终模型中纳入了总术中顺铂剂量、体重指数、男性和术前血红蛋白水平。接受者操作特征曲线下面积的平均值为 0.82（95%置信区间 0.71-0.93）。我们的风险模型在我们机构接受 HIPEC 的患者中预测 AKI 的准确性很高。我们的模型的外部有效性现在应在独立和前瞻性患者队列中进行测试。
