摘要
目的:对增加机器人辅助腹腔镜儿童肾盂成形术手术难度相关因素进行分析,并探讨相关因素对增加手术难度的预测价值。方法:回顾性分析2020年9月—2021年9月于我院住院行机器人辅助腹腔镜肾盂成形术治疗患儿的临床资料,依据手术时间及出血量分正常组及困难组并进行比较,对可能引起手术困难的相关因素进行多因素分析,并通过二元logistic回归构建预测手术难度的模型。结果:本研究共纳入124例初次行机器人辅助腹腔镜肾盂成形术治疗的单侧肾积水患儿,单因素分析显示患儿年龄、术前复发性尿路感染、小肾盂、肾轴旋转不良、腔静脉后输尿管、异位血管与手术难度相关(P<0.05)。Logistic回归分析发现,婴幼儿手术(OR=3.202,95%CI:1.148~8.935,P=0.026)、术前复发性尿路感染(OR=3.568,95%CI:1.187~10.723,P=0.023)、小肾盂(OR=3.836,95%CI:1.334~11.028,P=0.013)、肾轴旋转不良(OR=3.074,95%CI:1.074~8.798,P=0.036)、腔静脉后输尿管(OR=3.117,95%CI:1.013~9.591,P=0.047)是影响手术难度的相关因素。通过模型公式Logit(P)=-2.744+1.164×婴幼儿手术+1.272×术前复发性尿路感染+1.344×小肾盂+1.123×肾轴旋转不良+1.137×腔静脉后输尿管,可以术前预测手术难度,其AUC、灵敏度、特异度、约登指数、临界值分别为0.865、83.4%、84.7%、0.701、0.268。结论:婴幼儿手术、术前存在复发性尿路感染、小肾盂、肾轴旋转不良及腔静脉后输尿管,可以增加患儿机器人辅助腹腔镜肾盂成形术难度。本预测模型可以为准备或初步开展机器人手术的泌尿外科医生提供参考依据,并可以术前预判手术难度,便于该技术更安全地推广。
Objective: To analyze the factors related to increasing the difficulty of robot-assisted laparoscopic pyeloplasty in children, and to explore the predictive value of related factors for increasing the difficulty of the operation. Methods: The clinical data of children who underwent robot-assisted laparoscopic pyeloplasty in our hospital from September 2020 to September 2021 were retrospectively analyzed. According to the operation time and blood loss, they were divided into normal group and difficult group and compared. Binary logistic regression was used to construct a model to predict surgical difficulty. Results: A total of 124 children with unilateral hydronephrosis who underwent robot-assisted laparoscopic pyeloplasty for the first time were enrolled in this study. Univariate analysis showed that age, preoperative recurrent urinary tract infection, small renal pelvis, renal axis malrotation, retrocaval ureter, and ectopic vessels were associated with surgical difficulty(P<0.05). Logistic regression analysis showed that infant surgery(OR=3.202, 95%CI: 1.148-8.935, P=0.026) and preoperative recurrent urinary tract infection(OR=3.568, 95%CI: 1.187-10.723, P=0.023), small renal pelvis(OR=3.836, 95%CI: 1.334-11.028, P=0.013), renal axis malrotation(OR=3.074, 95%CI: 1.074-8.798, P=0.036) and retrocaval ureter(OR=3.117, 95%CI: 1.013-9.591, P=0.047) were related factors affecting the difficulty of operation. According to the model formula Logit(P)=-2.744+1.164×infant surgery+1.272× preoperative recurrent urinary tract infection +1.344×small renal pelvis+1.123×renal axis malrotation+1.137×retrocaval ureter, the difficulty of operation could be predicted before operation. The AUC, sensitivity, specificity, Youden index and critical value were 0.865, 83.4%, 84.7%, 0.701, 0.268, respectively. Conclusion: Infant surgery, preoperative recurrent urinary tract infection, small renal pelvis, renal axis malrotation and retrocaval ureter may increase the difficulty of robot-assisted laparoscopic pyeloplasty. This prediction model can provide reference for urological surgeons who are preparing or initially carrying out robotic surgery, and predict the difficulty of surgery so as to promote this technology safely.
作者
赵扬
周辉霞
马立飞
陶天
周晓光
陶元东
李品
ZHAO Yang;ZHOU Huixia;MA Lifei;TAO Tian;ZHOU Xiaoguang;TAO Yuandong;LI Pin(Department of Urology,Senior Department of Pediatrics,The Seventh Medical Center of Chinese PLAGeneral Hospital,Beijing,100700,China)
出处
《临床泌尿外科杂志》
CAS
2023年第3期188-191,195,共5页
Journal of Clinical Urology
基金
首都医学发展科研专项(No:2022-2-5083)
军队计生专项(No:18JS001)。
关键词
机器人辅助腹腔镜肾盂成形术
肾积水
儿童
难度预测
robot-assisted laparoscopic pyeloplasty
hydronephrosis
children
difficulty prediction