神经源性膀胱上尿路损害风险评估工具的研制  

Development of the risk evaluation tool for upper urinary tract damage of neurogenic bladder

作　　者：方蘅英[1] 梁骊敏[1] 蔡文智 王凯[3] 

机构地区：[1]中山大学附属第三医院护理部,广州市510630 [2]南方医科大学深圳医院护理部 [3]南方医科大学公共卫生学院

出　　处：《中华护理杂志》2018年第2期179-184,共6页Chinese Journal of Nursing

基　　金：广东省自然科学基金自由申请项目(2016A030313623);德国汉诺威医学院Iris Meyenburg-Altwarg教授专科护理人才教育团队项目(SZSM201612018);广州市天河区科技计划项目(201704KW023)

摘　　要：目的研制神经源性膀胱上尿路损害风险评估工具,以早期发现危险人群。方法调查112例神经源性膀胱患者的一般资料、病情资料、尿动力学和泌尿系影像学资料,分别建立Logistic回归和决策树模型,根据准确度和受试者工作特征曲线下面积较高的模型形成风险评估工具。结果决策树模型的准确度和受试者工作特征曲线下面积(84.8%,0.909)高于Logistic回归模型(73.2%,0.842),据此形成了包含尿道功能、性别、最大腹压、最大膀胱内压4个指标的风险评估表。结论本研究研制的神经源性膀胱上尿路损害风险评估表,为临床筛选危险人群提供了一种简便易行的工具。Objective To develop a risk evaluation tool for upper urinary tract damage （UUTD） of neurogenic bladder （NGB） to identify population at risk in the early stage. Methods The general,elinical,urodynamie,urinary imaging data of 112 NGB patients were retrospectively investigated. Logistic regression and decision tree were used to establish the risk early warning model respectively. The risk evaluation tool was formed according to the model with a higher accuracy and area under curve. Results The accuracy and area under curve of decision tree model （84.8%,0.909）was higher than that of logistic regression model （73.2%,0.842）. A risk evaluation scale including urinary tract funetion,gender,Pabd max,Pves max was formed. Conclusion We developed a risk evaluation scale to predict the risk of UUTD in patients with NGB. It might provide a convenient way to screen UUTD in NGB patients.

关 键 词：神经源性膀胱 膀胱输尿管反流 尿动力学 数据挖掘 

分 类 号：R473.6[医药卫生—护理学]