A decision tree model was generated to analyze several indicators for risk of UUTD. Urethra function, Pabd max, Pves max, and gender were selected as the screening indicators, and cut-off values for Pabd max and Pves max were 14 and 89, respectively (Figure 1).
The evaluation indices for the risk of UUTD using the decision tree are illustrated in Table 3.
The Kappa value was 0.661 (P< 0.001), showing a good fitness between the prediction results and the actual morbidity of UUTD.
UUTD in NGB includes a series of complications such as pyeloureterectasis, hydronephrosis, VUR and renal insufficiency (13).
The present study established a decision tree model to excavate the major risk factors for UUTD in NGB patients.
There were 45.9% of patients with UUTD showing normal urethra function, while none of the patients showing incompetent urethra function was with UUTD.
In our study, Pabd max and Pves max were valuable predictive variables for risk of UUTD in NGB patients.
The present study showed that gender is also a predictive variable for risk of UUTD in NGB patients.
The decision tree model for risk of neurogenic UUTD established in this study summarized two classification rules.
Our study developed a decision tree model to predict the risk of UUTD in patients with NGB.
Decision tree model for risk of upper urinary tract damage (UUTD) in patients with neurogenic bladder.