ArticleBrazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica2017
Application of data mining techniques to explore predictors of upper urinary tract damage in patients with neurogenic bladder.
Article in Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 5 citations in OpenAlex.
- Prognostic value of plasma microRNAs for non-small cell lung cancer based on data mining models.BMC cancer · 2024Article
- ABT-263 exerts a protective effect on upper urinary tract damage by alleviating neurogenic bladder fibrosis.Renal failure · 2023Article
- Diagnostic Value of Plasma MicroRNAs for Lung Cancer Using Support Vector Machine Model.Journal of Cancer · 2019Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study proposed a decision tree model to screen upper urinary tract damage (UUTD) for patients with neurogenic bladder (NGB). Thirty-four NGB patients with UUTD were recruited in the case group, while 78 without UUTD were included in the control group. A decision tree method, classification and regression tree (CART), was then applied to develop the model in which UUTD was used as a dependent variable and history of urinary tract infections, bladder management, conservative treatment, and urodynamic findings were used as independent variables. The urethra function factor was found to be the primary screening information of patients and treated as the root node of the tree; Pabd max (maximum abdominal pressure, >14 cmH2O), Pves max (maximum intravesical pressure, ≤89 cmH2O), and gender (female) were also variables associated with UUTD. The accuracy of the proposed model was 84.8%, and the area under curve was 0.901 (95%CI=0.844-0.958), suggesting that the decision tree model might provide a new and convenient way to screen UUTD for NGB patients in both undeveloped and developing areas.
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Registered trials
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