Supplementary Material for: Development of a Simple Risk Score Model to Predict Renal Artery Stenosis

Background/Aims: Renal artery stenosis (RAS) is a known cause of secondary hypertension and renal failure. Although renal artery angiography is the gold standard for diagnosing RAS, a simple method to estimate if patients will develop RAS is required. The aim of this retrospective study was to develop a simple risk score to predict significant RAS. Methods: Four thousand one hundred seventy-seven patients who underwent renal angiography between 2002 and 2016 at Tehran Heart Center were included. Significant RAS was defined as narrowing of the renal artery by at least 70%. Multiple predictors of the RAS were determined using multivariable logistic regression with a backward elimination method. The scoring system obtained from the final model was presented as nomogram. The possible nonlinear effect of continuous variables was evaluated using restricted cubic splines. Overfitting of the final model was assessed applying the tenfold cross-validation method. Model performance was checked using calibration plot as well as Hosmer-Lemeshow goodness of fit test, and area under the receiver operating characteristics (ROC) curve. Results: The prevalence of RAS was 14.1%. Female sex (OR [95% CI]: 1.53 [1.26–1.85]), hypertension (OR [95% CI]: 1.38 [1.08–1.77]), estimated glomerular filtration rate (OR [95% CI]: 0.98 [0.97–0.98]), body mass index (OR [95% CI]: 0.97 [0.95–0.99]), and age (OR [95% CI]: 1.01 [1.00–1.02]) were determined as the multiple predictors of RAS. The area under the ROC curve of the final predictive model was 0.702 (95% CI: 0.679–0.725). Conclusion: This model assesses the risk of RAS using available information. This model can be used for both clinical and research purposes.

【背景与目的】肾动脉狭窄（Renal Artery Stenosis, RAS）是继发性高血压与肾衰竭的明确病因。尽管肾动脉造影术是诊断肾动脉狭窄的金标准，但目前仍亟需一种简便方法以预估患者是否会发生肾动脉狭窄。本回顾性研究旨在构建一种简便的风险评分模型，用于预测重度肾动脉狭窄。
【方法】本研究纳入2002年至2016年间在德黑兰心脏中心接受肾动脉造影的4177例患者。重度肾动脉狭窄定义为肾动脉狭窄程度≥70%。采用向后消元法的多变量logistic回归分析确定肾动脉狭窄的多项预测因素，并将最终模型所得的评分系统以列线图形式呈现。通过限制性立方样条评估连续变量的潜在非线性效应；采用十折交叉验证法评估最终模型的过拟合风险；通过校准曲线、Hosmer-Lemeshow拟合优度检验以及受试者工作特征（Receiver Operating Characteristics, ROC）曲线下面积评估模型性能。
【结果】肾动脉狭窄的患病率为14.1%。最终确定的肾动脉狭窄多因素预测因素包括：女性（比值比[Odds Ratio, OR] 95%置信区间[Confidence Interval, CI]：1.53 [1.26–1.85]）、高血压（OR 95% CI：1.38 [1.08–1.77]）、估算肾小球滤过率（OR 95% CI：0.98 [0.97–0.98]）、体质量指数（OR 95% CI：0.97 [0.95–0.99]）以及年龄（OR 95% CI：1.01 [1.00–1.02]）。最终预测模型的ROC曲线下面积为0.702（95% CI：0.679–0.725）。
【结论】本模型可基于现有临床信息评估肾动脉狭窄的发病风险，可同时应用于临床实践与科学研究。