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作 者:古江林 罗生军[1] 蒋立[1] 胡代星 赵国智 唐伟[1] Gu Jianglin;Luo Shengjun;Jiang Li;Hu Daixing;Zhao Guozhi;Tang Wei(Department of Urology,The First Affiliated Hospital of Chongqing Medical University,Chongqing 400016,China)
机构地区:[1]重庆医科大学附属第一医院泌尿外科,重庆400016
出 处:《中华泌尿外科杂志》2022年第5期384-386,共3页Chinese Journal of Urology
基 金:重庆市科委社会技术创新与应用发展重点项目(cstc2019jscx-gksb0157)。
摘 要:回顾性分析我院收治的120例行输尿管软镜(FURS)治疗肾结石患者的临床资料,采用虚拟现实技术测量影像学相关数据。单因素分析结果显示肾盂肾盏高度(H)、肾盏漏斗部长度(L)、肾盂容积(P)、结石密度(E)和结石表面积(S)与结石清除率密切相关。根据上述因素构建H.L.P.E.S.评分系统,预测FURS术后结石清除率。H.L.P.E.S.、S.O.L.V.E.评分系统的受试者工作特征曲线下面积分别为0.921、0.754,H.L.P.E.S.评分系统具有更高的预测价值。The clinical data of 120 patients admitted to our hospital with renal stones treated by flexible ureteroscopy(FURS)and the imaging-related data measured by virtual reality technology were retrospectively analysed.The results of the univariate analysis showed that stone surface area(S),renal pelvis volume(P),length of calyces funnel(L),pelvic calyceal height(H)and essence of stone(E)were closely related to stone-free rate.The H.L.P.E.S.score was constructed to predict stone-free rate after FURS based on the above factors,and the area under the receiver aperating characteristic curve for the H.L.P.E.S.and S.O.L.V.E.scoring systems was 0.921 and 0.754 respectively.The H.L.P.E.S.scoring system has higher predictive value.
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