Arlen Angela M, Alexander Siobhan E, Wald Moshe, Cooper Christopher S
Department of Urology, University of Iowa Hospitals and Clinics, Iowa City, IA, USA; Department of Pediatrics, University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
Department of Urology, University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
J Pediatr Urol. 2016 Oct;12(5):288.e1-288.e5. doi: 10.1016/j.jpurol.2016.03.005. Epub 2016 Mar 31.
Factors influencing the decision to surgically correct vesicoureteral reflux (VUR) include risk of breakthrough febrile urinary tract infection (fUTI) or renal scarring, and decreased likelihood of spontaneous resolution. Improved identification of children at risk for recurrent fUTI may impact management decisions, and allow for more individualized VUR management. We have developed and investigated the accuracy of a multivariable computational model to predict probability of breakthrough fUTI in children with primary VUR.
Children with primary VUR and detailed clinical and voiding cystourethrogram (VCUG) data were identified. Patient demographics, VCUG findings including grade, laterality, and bladder volume at onset of VUR, UTI history, presence of bladder-bowel dysfunction (BBD), and breakthrough fUTI were assessed. The VCUG dataset was randomized into a training set of 288 with a separate representational cross-validation set of 96. Various model types and architectures were investigated using neUROn++, a set of C++ programs.
Two hundred fifty-five children (208 girls, 47 boys) diagnosed with primary VUR at a mean age of 3.1 years (±2.6) met all inclusion criteria. A total 384 VCUGs were analyzed. Median follow-up was 24 months (interquartile range 12-52 months). Sixty-eight children (26.7%) experienced 90 breakthrough fUTI events. Dilating VUR, reflux occurring at low bladder volumes, BBD, and history of multiple infections/fUTI were associated with breakthrough fUTI (Table). A 2-hidden node neural network model had the best fit with a receiver operating characteristic curve area of 0.755 for predicting breakthrough fUTI.
The risk of recurrent febrile infections, renal parenchymal scarring, and likelihood of spontaneous resolution, as well as parental preference all influence management of primary VUR. The genesis of UTI is multifactorial, making precise prediction of an individual child's risk of breakthrough fUTI challenging. Demonstrated risk factors for UTI include age, gender, VUR grade, reflux at low bladder volume, BBD, and UTI history. We developed a prognostic calculator using a multivariable model with 76% accuracy that can be deployed for availability on the Internet, allowing input variables to be entered to calculate the odds of an individual child developing a breakthrough fUTI.
A computational model using multiple variables including bladder volume at onset of VUR provides individualized prediction of children at risk for breakthrough fUTI. A web-based prognostic calculator based on this model will provide a useful tool for assessing personalized risk of breakthrough fUTI in children with primary VUR.
影响手术纠正膀胱输尿管反流（VUR）决策的因素包括突破性发热性尿路感染（fUTI）或肾瘢痕形成的风险，以及自然缓解的可能性降低。更好地识别复发性fUTI风险儿童可能会影响管理决策，并实现更个体化的VUR管理。我们开发并研究了一种多变量计算模型的准确性，以预测原发性VUR儿童发生突破性fUTI的概率。
确定患有原发性VUR且有详细临床和排尿性膀胱尿道造影（VCUG）数据的儿童。评估患者人口统计学特征、VCUG检查结果，包括VUR发作时的分级、侧别和膀胱容量、UTI病史、膀胱肠道功能障碍（BBD）的存在情况以及突破性fUTI。VCUG数据集被随机分为一个包含288例的训练集和一个单独的包含96例的代表性交叉验证集。使用一组C++程序neUROn++研究了各种模型类型和架构。
255名儿童（208名女孩，47名男孩）被诊断为原发性VUR，平均年龄为3.1岁（±2.6岁），符合所有纳入标准。共分析了384次VCUG检查。中位随访时间为24个月（四分位间距为12 - 52个月）。68名儿童（26.7%）经历了90次突破性fUTI事件。扩张性VUR、低膀胱容量时出现的反流、BBD以及多次感染/fUTI病史与突破性fUTI相关（表）。一个具有2个隐藏节点的神经网络模型拟合效果最佳，预测突破性fUTI的受试者操作特征曲线面积为0.755。
复发性发热感染的风险、肾实质瘢痕形成以及自然缓解的可能性，以及家长的偏好都会影响原发性VUR的管理。UTI的发生是多因素的，精确预测个体儿童发生突破性fUTI的风险具有挑战性。已证实的UTI风险因素包括年龄、性别、VUR分级、低膀胱容量时的反流、BBD和UTI病史。我们使用一个多变量模型开发了一个预后计算器，其准确率为76%，可在互联网上使用，允许输入变量来计算个体儿童发生突破性fUTI的几率。
一个使用包括VUR发作时膀胱容量在内的多个变量的计算模型可对有突破性fUTI风险的儿童进行个体化预测。基于此模型的网络预后计算器将为评估原发性VUR儿童突破性fUTI的个性化风险提供一个有用的工具。
