Non-Invasive Clinical Parameters for the Prediction of Urodynamic Bladder Outlet Obstruction: Analysis Using Causal Bayesian Networks |
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Authors: | Myong Kim Abhilash Cheeti Changwon Yoo Minsoo Choo Jae-Seung Paick Seung-June Oh |
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Affiliation: | 1. Department of Urology, Seoul National University Hospital, Seoul, Korea.; 2. Department of Computer Science, School of Computing and Information Sciences, Florida International University, Miami, FL, United States of America.; 3. Department of Biostatistics, Robert Stempel College of Public health & Social Work, Florida International University, Miami, FL, United States of America.; Politecnico di Torino, Italy, |
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Abstract: | PurposeTo identify non-invasive clinical parameters to predict urodynamic bladder outlet obstruction (BOO) in patients with benign prostatic hyperplasia (BPH) using causal Bayesian networks (CBN).Subjects and MethodsFrom October 2004 to August 2013, 1,381 eligible BPH patients with complete data were selected for analysis. The following clinical variables were considered: age, total prostate volume (TPV), transition zone volume (TZV), prostate specific antigen (PSA), maximum flow rate (Qmax), and post-void residual volume (PVR) on uroflowmetry, and International Prostate Symptom Score (IPSS). Among these variables, the independent predictors of BOO were selected using the CBN model. The predictive performance of the CBN model using the selected variables was verified through a logistic regression (LR) model with the same dataset.ResultsMean age, TPV, and IPSS were 6.2 (±7.3, SD) years, 48.5 (±25.9) ml, and 17.9 (±7.9), respectively. The mean BOO index was 35.1 (±25.2) and 477 patients (34.5%) had urodynamic BOO (BOO index ≥40). By using the CBN model, we identified TPV, Qmax, and PVR as independent predictors of BOO. With these three variables, the BOO prediction accuracy was 73.5%. The LR model showed a similar accuracy (77.0%). However, the area under the receiver operating characteristic curve of the CBN model was statistically smaller than that of the LR model (0.772 vs. 0.798, p = 0.020).ConclusionsOur study demonstrated that TPV, Qmax, and PVR are independent predictors of urodynamic BOO. |
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