Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
Department of Urology, The Second Affiliated Hospital of Nanchang University, No. 1, Minde Road, Nanchang, 330006, Jiangxi, China.
Int Urogynecol J. 2024 Oct;35(10):2065-2073. doi: 10.1007/s00192-024-05896-z. Epub 2024 Sep 19.
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.
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.
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%.
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.
本研究旨在探讨与逼尿肌过度活动（DO）相关的非侵入性指标，并通过回顾女性患者的临床和尿动力学数据，建立 DO 的预测模型。
我们回顾性纳入了 2011 年 9 月至 2021 年 4 月期间在同济医院接受尿动力学检查的 1084 例女性患者。通过单因素和多因素分析，显示与 DO 相关的因素和独立预测因素。应用这些数据建立和验证 DO 的非侵入性预测模型。
共有 194 例（17.9%）患者被归类为 DO。多因素逻辑回归显示，DO 的危险因素与年龄、夜尿症、尿急、急迫性尿失禁（UUI）和压力性尿失禁（SUI）缺失无关。DO 预测模型具有良好的性能，曲线下面积为 0.880（95%CI 0.826-0.933），在同济医院患者的尿动力学数据中得到验证为 0.818（95%CI 0.783-0.853）。校准曲线显示，预期概率与观察到的频率之间存在极好的一致性。决策曲线分析表明，当 DO 风险概率在 8%至 97%之间时，应用 DO 预测模型可以获得临床净收益。
使用临床和尿动力学数据建立和验证了 DO 的非侵入性预测模型。确定了与 DO 相关的五个独立因素：年龄、夜尿症、尿急、UUI 和 SUI。该预测模型有助于评估女性 DO 的风险，而无需进行侵入性尿动力学研究。
