切换至 "中华医学电子期刊资源库"

中华腔镜泌尿外科杂志(电子版) ›› 2023, Vol. 17 ›› Issue (05) : 506 -511. doi: 10.3877/cma.j.issn.1674-3253.2023.05.016

所属专题: 总编推荐

临床研究

体外冲击波治疗>1 cm输尿管上段结石失败的预测模型建立
徐慧新, 刘波, 唐立钧()   
  1. 210029 江苏,南京医科大学第一附属医院泌尿外科
    210029 江苏,南京医科大学第一附属医院放射科
    210029 江苏,南京医科大学第一附属医院核医学科
  • 收稿日期:2022-05-17 出版日期:2023-10-01
  • 通信作者: 唐立钧

Development of a prediction model for failed extracorporeal shock wave lithotripsy of proximal ureteral stones larger than 1 cm

Huixin Xu, Bo Liu, Lijun Tang()   

  1. Department of Urology, the First Affiliated Hospital of Nanjing Medical University, Jiangsu 210029, China
    Department of Radiology, the First Affiliated Hospital of Nanjing Medical University, Jiangsu 210029, China
    Department of Nuclear Medicine, the First Affiliated Hospital of Nanjing Medical University, Jiangsu 210029, China
  • Received:2022-05-17 Published:2023-10-01
  • Corresponding author: Lijun Tang
引用本文:

徐慧新, 刘波, 唐立钧. 体外冲击波治疗>1 cm输尿管上段结石失败的预测模型建立[J/OL]. 中华腔镜泌尿外科杂志(电子版), 2023, 17(05): 506-511.

Huixin Xu, Bo Liu, Lijun Tang. Development of a prediction model for failed extracorporeal shock wave lithotripsy of proximal ureteral stones larger than 1 cm[J/OL]. Chinese Journal of Endourology(Electronic Edition), 2023, 17(05): 506-511.

目的

建立并验证预测>1 cm的输尿管上段结石体外冲击波碎石(ESWL)治疗失败的模型。

方法

回顾性收集2019年1月至2021年6月南京医科大学第一附属医院泌尿外科收治经ESWL治疗的>1 cm输尿管上段单一结石的病例,分析其临床及影像学资料。临床资料包括性别、年龄、体质量指数(BMI)及结石患侧。影像学资料包括结石大小,结石密度,结石处输尿管壁最大厚度(UMT)、积水程度及结石上段输尿管内径(PUD)。其中结石大小包括结石最大上下径(MCD)、横径最大值(MATD)及横径最小值(MITD)及结石体积(SV);结石密度包括结石平均CT值(MESD)、最大CT值(MASD)、密度标准差(SDSD)及密度变异系数(VCSD)。采用单因素及多因素Logistic回归分析筛选预测>1 cm输尿管上段结石ESWL治疗失败的独立预测因子并建立模型。使用分辨度及符合度评价模型的预测效能。

结果

共纳入355例患者,失败组100例,成功组255例。单因素分析结果显示年龄,结石大小(包括MCD、MATD、MITD和SV)、结石密度(包括MESD、VCSD)、UMT、积水程度、PUD差异有统计学意义(P<0.05)。多因素分析结果显示年龄、MITD、MESD、UMT、PUD是ESWL治疗>1 cm的输尿管上段结石失败的独立影响因素,其OR值(95%置信区间)分别是:1.024(1.002~1.047),1.364(1.020~1.825),1.003(1.001~1.004),1.976(1.376~2.836)及1.731(1.387~2.160)。基于以上的5个独立预测因素建立列线图模型,该模型显示了良好的符合度及区分度,受试者工作特征(ROC)曲线下面积(AUC)为0.881(95%CI:0.844~0.917)。

结论

本研究基于年龄、MITD、MESD、UMT和PUD构建的列线图具有较好的预测效能,为>1 cm的输尿管上段结石拟行ESWL治疗病例的筛选提供参考。

Objective

To develop and validate a prediction model for predicting the failure after extracorporeal shock wave lithotripsy (ESWL) in patients with proximal ureteral stones larger than 1 cm.

Methods

The clinical and radiographic data of patients with solitary proximal ureteral stone larger than 1 cm who underwent ESWL from January 2019 to June 2021 were retrospectively analyzed. Clinical data included sex, age, body mass index (BMI) and stone laterality. Radiographic data included stone size, stone density, ureteral wall thickness (UMT), hydronephrosis grade and proximal ureter diameter (PUD). Stone size included maximal craniocaudal (MCD), maximal transverse diameter (MATD), minimal transverse diameter (MITD) and stone volume (SV). Stone density included mean stone density (MESD), maximum stone density (MASD), standard deviation of stone density (SDSD) and variation coefficient of stone density (VCSD). Univariate and multivariate analyses were used to identify the prognostic factors of ESWL failure for proximal ureteral stones larger than 1cm. Multivariable logistic regression model was adopted to built a nomogram. Nomogram performance was determined by its discrimination and calibration.

Results

355 patients in total were divided into two groups as failure (100 cases) and success (255 cases). Univariate analysis showed significant difference in age, stone size (including MCD, MATD, MITD and SV), stone density (including MESD and VCSD), UMT, hytronephrosis grade and PUD between success and failure group. Multivariate analysis showed that age (OR: 1.024 [95%CI: 1.002 to 1.047], P=0.030), MITD (OR: 1.364 [95%CI: 1.020 to 1.825], P=0.036), MESD (OR: 1.003 [95%CI: 1.001 to 1.004], P<0.001), UMT (OR: 1.976 [95%CI: 1.376 to 2.836], P<0.001) and PUD (OR: 1.731 [95%CI: 1.387 to 2.160], P<0.001) were independent predictors of ESWL failure. A nomogram to predict the failure of ESWL with these five predictors was developed. The nomogam showed good calibration and discrimination [area under the ROC curve was 0.881 (95%CI: 0.844 to 0.917)].

Conclusion

Based on age, MITD, MESD, UMT and PUD, the nomogram showed good prediction value, which provided reference to screening the suitable patients with proximal ureteral stone larger than 1 cm for ESWL treatment.

表1 ESWL治疗失败组及成功组的临床及影像学资料比较
表2 输尿管结石ESWL一次成功率影响因素多因素分析
图1 预测>1 cm上段输尿管结石ESWL治疗失败的列线图
图2 预测>1 cm上段输尿管结石ESWL治疗失败的列线图模型校准曲线
[1]
Türk C, Skolarikos A, Neisius A,et al. EAU Guidelines on Urolithiasis[EB/OL].[2019-03-01].

URL    
[2]
Onen A. Grading of Hydronephrosis: An ongoing challenge[J]. Front Pediatr, 2020, 8: 458.
[3]
郭万松, 杨波, 赵航. 体外冲击波碎石术治疗尿路结石研究进展[J/OL]. 中华腔镜泌尿外科杂志(电子版), 2020, 14(5): 393-396.
[4]
Wiesenthal JD, Ghiculete D, Ray AA, et al. A clinical nomogram to predict the successful shock wave lithotripsy of renal and ureteral calculi[J]. J Urol, 2011, 186(2): 556-562.
[5]
Yoshioka T, Ikenoue T, Hashimoto H, et al. Development and validation of a prediction model for failed shockwave lithotripsy of upper urinary tract calculi using computed tomography information: the S3HoCKwave score[J]. World J Urol, 2020, 38(12): 3267-3273.
[6]
Ng CF, Siu DY, Wong A, et al. Development of a scoring system from noncontrast computerized tomography measurements to improve the selection of upper ureteral stone for extracorporeal shock wave lithotripsy[J]. J Urol, 2009, 181, 1151-1157.
[7]
Sugino Y, Kato T, Furuya S, et al. The usefulness of the maximum Hounsfield units (HU) in predicting the shockwave lithotripsy outcome for ureteral stones and the proposal of novel indicators using the maximum HU[J]. Urolithiasis, 2020, 48(1): 85-91.
[8]
Guler Y, Erbin A, Kafkasli A, et al. Factors affecting success in the treatment of proximal ureteral stones larger than 1cm with extracorporeal shockwave lithotripsy in adult patients[J]. Urolithiasis, 2021, 49(1): 51-56.
[9]
Perks AE, Schuler TD, Lee J, et al. Stone attenuation and skin-to-stone distance on computed tomography predicts for stone fragmentation by shock wave lithotripsy[J]. Urology, 2008, 72(4):765-769.
[10]
Cui HW, Devlies W, Ravenscroft S, et al. CT texture analysis of ex vivo renal stones predicts ease of fragmentation with shockwave lithotripsy[J]. J Endourol, 2017, 31(7): 694-700.
[11]
Cui HW, Silva MD, Mills AW, et al. Predicting shockwave lithotripsy outcome for urolithiasis using clinical and stone computed tomography texture analysis variables[J]. Sci Rep, 2019, 9(1): 14674.
[12]
Lee JY, Kim JH, Kang DH, et al. Stone heterogeneity index as the standard deviation of Hounsfield units: A novel predictor for shock-wave lithotripsy outcomes in ureter calculi[J]. Sci Rep, 2016, 6:23988.
[13]
Yamashita S, Kohjimoto Y, IguchiT, et al. Variation coeffificient of stone density:a novel predictor of the outcome of extracorporeal shock wave lithotripsy[J]. J Endourol, 2017, 31(4): 384-390.
[14]
Mannil M, von Spiczak J, Hermanns T, et al. Prediction of successful shock wave lithotripsy with CT: a phantom study using texture analysis[J]. Abdom Radiol, 2018, 43(6): 1432-1438.
[15]
Amasyali AS, Groegler J, Hajiha M, et al. What Guidewire Is the Best for Bypassing an Impacted Ureteral Stone? [J] J Endourol, 2020, 34(5): 629-636.
[16]
Khalil M. Management of impacted proximal ureteral stone: extracorporeal shock wave lithotripsy versus ureteroscopy with holmium: YAG laser lithotripsy [J]. Urol Ann, 2013, 5: 88-92.
[17]
Sarica K, Kafkasli A, Yazici ö,et al. Ureteral wall thickness at the impacted ureteral stone site: a critical predictor for success rates after SWI[J]. Urolithiasis, 2015, 43: 83-88.
[18]
许清江, 叶烈夫, 朱庆国, 等. 输尿管壁厚度对嵌顿性输尿管结石的预测价值[J]. 中华泌尿外科杂志, 2019, 40(3): 210-214.
[19]
王成路, 金露, 薛波新. 术前预测输尿管嵌顿性结石的临床因素分析[J]. 中华泌尿外科杂志, 2019, 40(1): 42-46.
[20]
Drake T, Grivas N, Dabestani S, et al. What are the benefits and harms of ureteroscopy compared with shock-wave lithotripsy in the treatment of upper ureteral stones? a systematic review[J]. Eur Urol, 2017, 72(5): 772-786.
[21]
Lang J, Narendrula A, El-Zawahry A, et al. Global trends in incidence and burden of urolithiasis from 1990 to 2019: an analysis of global burden of disease study data[J]. Eur Urol Open Sci, 2022, 35: 37-46.
[22]
Yoshida T, Inoue T, Taguchi M, et al. Ureteral wall thickness as a significant factor in predicting spontaneous passage of ureteral stones of ≤ 10 mm: a preliminary report[J]. World J Urol, 2019, 37(5): 913-919.
[23]
Na L, Li J, Pan C, et al. Development and validation of a predictive model for major complications after extracorporeal shockwave lithotripsy in patients with ureteral stones: based on a large prospective cohort[J]. Urolithiasis, 2023, 51(1): 42.
[24]
Ozbir S, Can O, Atalay HA, et al. Formula for predicting the impaction of ureteral stones[J]. Urolithiasis, 2020, 48(4): 353-60.
[25]
Tran TY, Bamberger JN, Blum KA, et al. Predicting the Impacted Ureteral Stone with Computed Tomography[J]. Urology, 2019, 130: 43-47.
[1] 胡可, 鲁蓉. 基于多参数超声特征的中老年女性压力性尿失禁诊断模型研究[J/OL]. 中华医学超声杂志(电子版), 2024, 21(05): 477-483.
[2] 余晓青, 高欣, 罗文培, 杨露. BI-RADS 4类结节患者的乳腺癌风险预测模型[J/OL]. 中华乳腺病杂志(电子版), 2024, 18(04): 217-223.
[3] 蒲彦婷, 吴翠先, 兰玉梅. 类风湿关节炎患者骨质疏松症风险预测列线图模型构建[J/OL]. 中华关节外科杂志(电子版), 2024, 18(05): 596-603.
[4] 庄燕, 戴林峰, 张海东, 陈秋华, 聂清芳. 脓毒症患者早期生存影响因素及Cox 风险预测模型构建[J/OL]. 中华危重症医学杂志(电子版), 2024, 17(05): 372-378.
[5] 杜佳丽, 鲍睿, 乔春红, 韩伟. 中孕期宫颈功能不全孕妇经阴道紧急宫颈环扎术后不良妊娠结局预测模型构建[J/OL]. 中华妇幼临床医学杂志(电子版), 2024, 20(04): 403-409.
[6] 蔡大明, 陆晓峰, 王行舟, 王萌, 刘颂, 夏雪峰, 沈晓菲, 杜峻峰, 管文贤. 三级淋巴结构在胃神经内分泌瘤中的预后价值及预后预测模型构建[J/OL]. 中华普外科手术学杂志(电子版), 2024, 18(04): 401-405.
[7] 屈勤芳, 束方莲. 盆腔器官脱垂患者盆底重建手术后压力性尿失禁发生的影响因素及列线图预测模型构建[J/OL]. 中华腔镜泌尿外科杂志(电子版), 2024, 18(06): 606-612.
[8] 杜贵伟, 陆勇, 成博, 贺薏, 梁爽. 钬激光碎石术术后联合坦索罗辛治疗对输尿管结石患者的影响分析[J/OL]. 中华腔镜泌尿外科杂志(电子版), 2024, 18(05): 491-496.
[9] 张瑜, 姜梦妮. 基于DWI信号值构建局部进展期胰腺癌放化疗生存获益预测模型[J/OL]. 中华肝脏外科手术学电子杂志, 2024, 13(05): 657-664.
[10] 杨秀君, 崔梦莹, 刘水, 盛基尧, 张丹. 基于SEER数据库胰头部胰腺神经内分泌癌患者预后列线图构建与验证[J/OL]. 中华肝脏外科手术学电子杂志, 2024, 13(04): 520-525.
[11] 单良, 刘怡, 于涛, 徐丽. 老年股骨颈骨折术后患者心理弹性现状及影响因素分析[J/OL]. 中华老年骨科与康复电子杂志, 2024, 10(05): 294-300.
[12] 刘燚隆, 党荣广, 艾蓉, 张凯. 肝硬化合并静脉曲张出血患者内镜治疗后再出血风险的模型建立与验证[J/OL]. 中华消化病与影像杂志(电子版), 2024, 14(04): 336-342.
[13] 倪颖, 张铁龙, 王岗, 高玉龙, 陈韶鹏, 倪家璇. 未预置支架逆行输尿管镜治疗近端输尿管结石手术中的困难与应对[J/OL]. 中华临床医师杂志(电子版), 2024, 18(09): 795-801.
[14] 韦巧玲, 黄妍, 赵昌, 宋庆峰, 陈祖毅, 黄莹, 蒙嫦, 黄靖. 肝癌微波消融术后中重度疼痛风险预测列线图模型构建及验证[J/OL]. 中华临床医师杂志(电子版), 2024, 18(08): 715-721.
[15] 颜世锐, 熊辉. 感染性心内膜炎合并急性肾损伤患者的危险因素探索及死亡风险预测[J/OL]. 中华临床医师杂志(电子版), 2024, 18(07): 618-624.
阅读次数
全文


摘要