Farag Fawzy, Elbadry Mohamed, Saber Mohammed, Badawy Abdelbasset A, Heesakkers John
Department of Urology, Sohag University Hospital, Sohag, Egypt.
Department of Urology, Minia University Hospital, Minia, Egypt.
Arab J Urol. 2017 Mar 6;15(2):153-158. doi: 10.1016/j.aju.2017.01.002. eCollection 2017 Jun.
To determine the ability of bladder wall thickness (BWT) in combination with non-invasive variables to distinguish patients with bladder outlet obstruction (BOO).
Patients completed the International Prostate Symptom Score (IPSS) questionnaire and prostate size was measured by transrectal ultrasonography (US). Pressure-flow studies were performed to determine the urodynamic diagnosis. BWT was measured at 250-mL bladder filling using transabdominal US. Recursive partition analysis (RPA) recursively partitions data for relating independent variable(s) to a dependent variable creating a tree of partitions. It finds a set of cuts of the dependent variable(s) that best predict the independent variable, by searching all possible cuts until the desired fit is reached. RPA was used to test the ability of the combined data of BWT, maximum urinary flow rate (), post-void residual urine volume (PVR), IPSS, and prostate size to predict BOO.
In all, 72 patients were included in the final analysis. The median BWT, voided volumes, PVR, mean , and IPSS were significantly higher in patients who had an Abrams/Griffiths (A/G) number of >40 (55 patients) compared to those with an A/G number of ≤40 (17 patients). RPA revealed that the combination of BWT and gave a correct classification in 61 of the 72 patients (85%), with 92% sensitivity and 65% specificity, 87% positive predictive value, and 76% negative predictive value (NPV) for BOO (area under the curve 0.85). The positive diagnostic likelihood ratio of this reclassification fit was 2.6.
It was possible to combine BWT with to create a new algorithm that could be used as a screening tool for BOO in men with lower urinary tract symptoms.
确定膀胱壁厚度（BWT）联合非侵入性变量区分膀胱出口梗阻（BOO）患者的能力。
患者完成国际前列腺症状评分（IPSS）问卷，经直肠超声（US）测量前列腺大小。进行压力流研究以确定尿动力学诊断。使用经腹超声在膀胱充盈至250 mL时测量BWT。递归划分分析（RPA）将数据递归划分为与因变量相关的自变量，从而创建一个划分树。它通过搜索所有可能的划分，直到达到所需的拟合度，找到一组能最佳预测自变量的因变量划分。RPA用于测试BWT、最大尿流率（）、排尿后残余尿量（PVR）、IPSS和前列腺大小的联合数据预测BOO的能力。
最终分析共纳入72例患者。Abrams/Griffiths（A/G）值>40的患者（55例）与A/G值≤40的患者（17例）相比，BWT中位数、排尿量、PVR、平均和IPSS显著更高。RPA显示，BWT和的联合在72例患者中的61例（85%）中分类正确，对BOO的敏感性为92%，特异性为65%，阳性预测值为87%，阴性预测值（NPV）为76%（曲线下面积为0.85）。这种重新分类拟合的阳性诊断似然比为2.6。
将BWT与相结合创建一种新算法是可行的，该算法可作为下尿路症状男性BOO的筛查工具。
