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Parenchymal Volumetric Assessment as a Predictive Tool to Determine Renal Function Benefit of Nephron-Sparing Surgery Compared with Radical Nephrectomy

机译:实质体积评估作为确定肾功能保留肾手术与根治性肾切除术相比肾功能获益的预测工具

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摘要

>Purpose: To develop a preoperative prediction model using a computer-assisted volumetric assessment of potential spared parenchyma to estimate the probability of chronic kidney disease (CKD, estimated glomerular filtration rate [eGFR] <60 mL/min/1.73 m2) 6 months from extirpative renal surgery (nephron-sparing surgery [NSS] or radical nephrectomy [RN]).>Patients and Methods: Retrospective analysis of patients who underwent NSS or RN at our institution from January 2000 to June 2013 with a compatible CT scan 6-month renal function follow-up was performed. Primary outcome was defined as the accuracy of 6-month postoperative eGFR compared with actual postoperative eGFR based on root mean square error (RMSE). Models were constructed using renal volumes and externally validated. A clinical tool was developed on the best model after a given surgical procedure using area under the curve (AUC).>Results: We identified 130 (51 radical, 79 partial) patients with a median age of 58 years (interquartile range [IQR] 48–67) and preoperative eGFR of 82.1 (IQR 65.9–104.3); postoperative CKD (eGFR <60) developed in 42% (55/130). We performed various linear regression models to predict postoperative eGFR. The Quadratic model was the highest performing model, which relied only on preoperative GFR and the volumetric data for a RMSE of 15.3 on external validation corresponding to a clinical tool with an AUC of 0.89.>Conclusion: Volumetric-based assessment provides information to predict postoperative eGFR. A tool based on this equation may assist surgical counseling regarding renal functional outcomes before renal tumor surgical procedures.
机译:>目的:使用计算机辅助容量评估可能的剩余实质进行术前预测模型,以评估慢性肾脏疾病的可能性(CKD,估计肾小球滤过率[eGFR] <60 mL / min / 1.73 m 2 )是在肾脏切除术(保留肾的手术[NSS]或根治性肾切除术[RN])的6个月后进行的。>患者和方法: 2000年1月至2013年6月在我们机构进行了NSS或RN并进行了兼容的CT扫描,并进行了6个月的肾功能随访。主要结局定义为基于均方根误差(RMSE)的6个月术后eGFR与实际术后eGFR的准确性。使用肾脏体积构建模型并进行外部验证。在给定的手术程序后,使用曲线下面积(AUC)在最佳模型上开发了一种临床工具。>结果:我们确定了130名(51名根治性,79名部分性)患者,中位年龄为58岁(四分位间距[IQR] 48-67)和术前eGFR为82.1(IQR 65.9-104.3);术后CKD(eGFR <60)发生率为42%(55/130)。我们执行了各种线性回归模型来预测术后eGFR。 Quadratic模型是性能最高的模型,它仅依赖于术前GFR和外部验证的RMSE为15.3的体积数据(对应于AUC为0.89的临床工具)。>结论:评估可提供信息以预测术后eGFR。基于此等式的工具可以在肾脏肿瘤外科手术之前协助有关肾脏功能结果的手术咨询。

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