目的: 基于盆底超声测量的前腔室结构参数,构建产妇产后盆底功能障碍（pelvic floor dysfunction,PFD）预测模型。方法: 选取2021年4月—2024年4月间于笔者医院行超声盆底检查的女性患者320名作为研究对象,根据被调查者的盆底状况将其分为正常组（n=206）和障碍组（n=114）。统计比较两组患者的一般临床资料和前腔室结构参数;多因素Logistic分析产妇产后PFD的危险因素并构建预测模型;限制性立方样条（Restricted cubic splineRestricted cubic spline,RCS）模型分析前腔室结构参数与产妇产后PFD的剂量-反应关系;构建多因素Logistic回归模型并评价模型预测效能。结果: 正常组与障碍组患者年龄、孕周、产次、不良孕产率、盆底功能影响问卷简表（pelvic floor impact questionnaire-7,PFIQ-7）、PFD问卷（pelvic floor distress inventory-short form 20,PFDI-20）和盆底器官脱垂-尿失禁性功能问卷（pelvic organ prolapsed-urinary incontinence sexual questionnaire-12,PISQ-12）评分的比较,差异均有统计学意义。正常组与障碍组患者膀胱尿道后角（posterior vesicourethral angle,PUVA）、膀胱颈至趾骨联合下缘的距离（edge of bladder neck to toe bone joint distance,D）、逼尿肌厚度（detrusor thickness,BDT）、尿道旋转角（urethral rotation angle,URA）、膀胱颈移动度（bladder neck descent,BND）和尿道倾斜角（urethral angle,UTA）水平的比较,差异均有统计学意义。Logistic回归分析结果显示,PUVA水平高、D水平高、BDT水平高、URA水平高、BND水平高、UTA水平高、年龄水平高、孕周高、产次为经产、不良孕产史、PFIQ-7水平高、PFDI-20水平高和PISQ-12水平高是发生PFD的危险因素。基于上述一般临床资料和前腔室结构参数构建一般临床资料模型、前腔室结构参数模型和联合模型。模型评估显示,联合模型可以有效预测产妇产后盆底功能障碍的发生;与一般临床资料模型和前腔室结构参数模型相比,该模型显示出较好的预测效能。结论: 本研究基于一般临床资料和盆底超声测量的前腔室结构参数,构建了用于预测产妇产后PFD的联合模型,该模型具有较高的预测效能,对临床具有一定的指导意义。
Abstract
Objective To construct a prediction model of postpartum pelvic floor dysfunction (PFD) based on the anterior chamber structural parameters measured by pelvic floor ultrasound. Methods A total of 320 female patients who underwent ultrasound pelvic floor examination in our hospital from April 2021 to April 2024 were selected as the study objects, and were divided into normal group (n=206) and disabled group (n=114) according to their pelvic floor conditions. The general clinical data and anterior chamber structure parameters were statistically compared between the two groups. Multivariate logistic analysis was conducted to analyze the risk factors of postpartum PFD and to build a prediction model. Restricted cubic spline (RCS) model was used to analyze the dose-relationship between the structural parameters of the anterior chamber and postpartum PFD. Multivariate Logistic regression model was constructed and the predictive efficiency of the model was evaluated. Results The differences of age, gestational age, parity, adverse pregnancy rate, pelvic floor impact questionnaire-7 (PFIQ-7), pelvic floor distress inventory-short form 20 (PFDI-20) and pelvic organ prolapsed-urinary incontinence sexual questionnaire-12 (PISQ-12) scores between normal group and disorder group were statistically significant. There were significant differences in the levels of posterior vesicourethral angle (PUVA), edge of bladder neck to toe bone joint distance (D), detrusor thickness (BDT), urethral rotation angle (URA), bladder neck descent (BND), and urethral angle (UTA) between the normal group and the disorder group. Logistic regression analysis showed that high PUVA level, high D level, and high BDT level, URA, BND, UTA, higher age, higher gestational age, multiparity, history of adverse pregnancy and delivery, high level of PFIQ-7, high level of PFDI-20 and high level of PISQ-12 were risk factors for PFD. Based on the above general clinical data and anterior compartment structural parameters, the general clinical data model, anterior compartment structural parameter model and combined model were constructed. Model evaluation showed that the combined model could effectively predict the occurrence of postpartum pelvic floor dysfunction. Compared with the general clinical data model and the anterior compartment structural parameter model, the model showed better prediction performance. Conclusion In this study, based on the general clinical data and the anterior chamber structure parameters measured by pelvic floor ultrasound, a combined model for predicting postpartum PFD was constructed. This model has high predictive efficiency and has certain guiding significance for clinical practice.
关键词
盆底超声 /
前腔室结构参数 /
盆底功能 /
深度学习
Key words
basin ultrasound /
front chamber structural parameters /
pelvic floor function /
deep learning
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基金
2021年度河北省医学科学研究课题计划“四维超声评估高龄顺产及剖宫产女性盆底结构及功能变化的临床研究”（20211407）
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