背景:与排卵功能障碍(AUB-O)相关的异常子宫出血是一种典型的妇科疾病,可影响各个年龄段的女性。能够识别有AUB-O风险的女性可以让医生及时采取行动。本研究旨在探讨中国女性AUB-O的影响因素,然后开发并验证预测模型。
方法:在这项多中心病例对照研究中,在2019年4月至2022年1月期间,来自浙江省9家医院的391名AUB-O女性和838名对照者被招募。所有参与者完成了一份结构化问卷,包括一般特征,生活方式和习惯,月经和生殖史,以前的疾病。预测模型是在一组822名女性上开发的,并在一组407名女性上进行了验证。采用Logistic回归对影响因素进行调查并建立模型,然后进行验证。
结果:AUB-O的独立预测因素是年龄(OR1.073,95%CI1.046-1.102,P<0.001),体重指数(OR1.081,95%CI1.016-1.151,P=0.015),收缩压(OR1.016,95%CI1.002-1.029,P=0.023),居住地(OR2.451,95%CI1.727-3.478,P<0.001),植物性饮食(OR2.306,95%CI1.415-3.759,P<0.001),吃水果(OR1.887,95%CI1.282-2.776,P=0.001),每日睡眠持续时间(OR0.819;95%CI0.708-0.946,P=0.007),多产(奇偶校验=1,OR0.424,95%CI0.239-0.752,P=0.003;奇偶校验>1,OR0.450,95%CI0.247-0.822,P=0.009),和卵巢囊肿病史(OR1.880,95%CI1.305-2.710,P<0.001)。发展组的预测能力(曲线下面积)为0.77(95%CI0.74-0.81),而在验证组中为0.73(95%CI0.67-0.79)。开发组校准曲线与标准曲线高度吻合,类似于验证组。创建了用于AUB-O风险计算的工具。
结论:本研究提出了9个影响因素和预测模型,这可以识别出患有AUB-O的高风险女性。这一发现强调了女性早期筛查和终身治疗排卵障碍的重要性。
Abnormal uterine bleeding associated with ovulatory dysfunction (AUB-O) is a typical gynecological disease that can affect women of various ages. Being able to identify women at risk of AUB-O could allow physicians to take timely action. This study aimed to identify the influencing factors of AUB-O in Chinese women, and then develop and validate a predictive model.
In this multicenter
case-control study, 391 women with AUB-O and 838 controls who came from nine hospitals in Zhejiang province were recruited between April 2019 and January 2022. All the participants completed a structured questionnaire including general characteristics, lifestyle and habits, menstrual and reproductive history, and previous diseases. The predictive model was developed on a group of 822 women and validated on a group of 407 women. Logistic regression was adopted to investigate the influencing factors and develop the model, and validation was then performed.
The independent predictive factors of AUB-O were age (OR 1.073, 95% CI 1.046-1.102, P < 0.001), body mass index (OR 1.081, 95% CI 1.016-1.151, P = 0.015), systolic blood pressure (OR 1.016, 95% CI 1.002-1.029, P = 0.023), residence (OR 2.451, 95% CI 1.727-3.478, P < 0.001), plant-based diet (OR 2.306, 95% CI 1.415-3.759, P < 0.001), fruits eating (OR 1.887, 95% CI 1.282-2.776, P = 0.001), daily sleep duration (OR 0.819; 95% CI 0.708-0.946, P = 0.007), multiparous (parity = 1, OR 0.424, 95% CI 0.239-0.752, P = 0.003; parity > 1, OR 0.450, 95% CI 0.247-0.822, P = 0.009), and history of ovarian cyst (OR 1.880, 95% CI 1.305-2.710, P < 0.001). The predictive ability (area under the curve) in the development group was 0.77 (95% CI 0.74-0.81), while in the validation group it was 0.73 (95% CI 0.67-0.79). The calibration curve was in high coincidence with the standard curve in the development group, and similar to the validation group. A tool for AUB-O risk calculation was created.
Nine influencing factors and a predictive model were proposed in this study, which could identify women who are at high risk of developing AUB-O. This finding highlights the importance of early screening and the lifelong management of ovulatory disorders for women.