Chen Ling, Luo Dan, Yu Xiajuan, Jin Mei, Cai Wenzhi
Department of Nursing, Shenzhen Hospital, Southern Medical University, Shenzhen, Guangdong, China.
Department of Neonatology, Shenzhen Maternity & Child Health Care Hospital, Shenzhen, Guangdong, China.
Acta Obstet Gynecol Scand. 2018 Aug;97(8):966-975. doi: 10.1111/aogs.13368. Epub 2018 Jul 13.
The aim of this study was to develop and validate a predictive tool that combines pelvic floor ultrasound parameters and clinical factors for stress urinary incontinence during pregnancy.
A total of 535 women in the first or second trimester of pregnancy were included for an interview and transperineal ultrasound assessment from two hospitals. Imaging data sets were analyzed offline to assess for bladder neck vertical position, urethra angles (α, β and γ angles), hiatal area and bladder neck funneling. All significant continuous variables at univariable analysis were analyzed by receiver operating characteristics. Three multivariable logistic models were built on clinical factors, and combined with ultrasound parameters. The final predictive model with best performance and fewest variables was selected to establish a nomogram. Internal and external validation of the nomogram was performed by both discrimination represented by C-index and calibration measured by Hosmer-Lemeshow test. A decision curve analysis was conducted to determine the clinical utility of the nomogram.
After excluding 14 women with invalid data, 521 women were analyzed. β angle, γ angle and hiatal area had limited predictive value for stress urinary incontinence during pregnancy, with area under curves of 0.558-0.648. The final predictive model included body mass index gain since pregnancy, constipation, previous delivery mode, β angle at rest, and bladder neck funneling. The nomogram based on the final model showed good discrimination with a C-index of 0.789 and satisfactory calibration (p = 0.828), both of which were supported by external validation. Decision curve analysis showed that the nomogram was clinically useful.
The nomogram incorporating both the pelvic floor ultrasound parameters and clinical factors has been validated to show good discrimination and calibration, and could be an important tool for stress urinary incontinence risk prediction at an early stage of pregnancy.
本研究的目的是开发并验证一种结合盆底超声参数和临床因素的预测工具，用于预测孕期压力性尿失禁。
从两家医院纳入了共535名处于妊娠早期或中期的女性进行访谈和经会阴超声评估。对成像数据集进行离线分析，以评估膀胱颈垂直位置、尿道角度（α、β和γ角）、裂孔面积和膀胱颈漏斗形成情况。对单变量分析中所有具有显著意义的连续变量进行受试者工作特征分析。基于临床因素构建了三个多变量逻辑模型，并与超声参数相结合。选择性能最佳且变量最少的最终预测模型来建立列线图。通过以C指数表示的区分度和以Hosmer-Lemeshow检验测量的校准度对列线图进行内部和外部验证。进行决策曲线分析以确定列线图的临床实用性。
在排除14名数据无效的女性后，对521名女性进行了分析。β角、γ角和裂孔面积对孕期压力性尿失禁的预测价值有限，曲线下面积为0.558 - 0.648。最终的预测模型包括孕期体重指数增加、便秘、既往分娩方式、静息时的β角和膀胱颈漏斗形成情况。基于最终模型的列线图显示出良好的区分度，C指数为0.789，校准度令人满意（p = 0.828），两者均得到外部验证的支持。决策曲线分析表明该列线图具有临床实用性。
结合盆底超声参数和临床因素的列线图已得到验证，显示出良好的区分度和校准度，可成为孕期早期压力性尿失禁风险预测的重要工具。
