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A Novel Predictive Model of Detrusor Overactivity Based on Clinical Symptoms and Non-invasive Test Parameters in Female Patients with Lower Urinary Tract Symptoms
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A Novel Predictive Model of Detrusor Overactivity Based on Clinical Symptoms and Non-invasive Test Parameters in Female Patients with Lower Urinary Tract Symptoms
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A Novel Predictive Model of Detrusor Overactivity Based on Clinical Symptoms and Non-invasive Test Parameters in Female Patients with Lower Urinary Tract Symptoms
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Journal Article
A Novel Predictive Model of Detrusor Overactivity Based on Clinical Symptoms and Non-invasive Test Parameters in Female Patients with Lower Urinary Tract Symptoms
2024
Overview
Introduction and Hypothesis
This study was aimed at investigating non-invasive indicators correlated with detrusor overactivity (DO) and at developing a prediction model for DO by reviewing clinical and urodynamic data of female patients.
Methods
We retrospectively enrolled 1,084 female patients who underwent a urodynamic study (UDS) at Tongji Hospital between September 2011 and April 2021. Associated factors and the independent prediction factors of DO were demonstrated by univariate and multivariate analysis. A non-invasive prediction model of DO was developed and validated by applying these data.
Results
A total of 194 patients (17.9%) were classified as having DO. A logistic regression of a multivariate nature showed that DO risk factors were independent of age, nocturia, urgency, urgency urinary incontinence (UUI), and the lack of stress urinary incontinence (SUI). The DO prediction model had good performance, with an area under the curve of 0.880 (95% CI 0.826–0.933), which was verified by urodynamic data of patients in Tongji Hospital to be 0.818 (95% CI 0.783–0.853). An outstanding correspondence between the anticipated probability and the observed frequency was revealed by the calibration curve. Decision curve analysis demonstrated that clinical net benefit can be obtained by applying the DO prediction model when the DO risk probability was between 8 and 97%.
Conclusions
A non-invasive prediction model of DO was developed and validated using clinical and urodynamic data. Five independent factors associated with DO were identified: age, nocturia, urgency, UUI, and SUI. This prediction model can contribute to assessing the risk of female DO without the need for invasive urodynamic studies.
Publisher
Springer International Publishing,Springer Nature B.V
