国际生殖健康/计划生育杂志

国际生殖健康/计划生育杂志 ›› 2024, Vol. 43 ›› Issue (6): 453-457.doi: 10.12280/gjszjk.20240147

• 论著 • 上一篇    下一篇

未分化结缔组织病患者发生不良妊娠结局的影响因素及列线图预测模型的构建

王钥, 唐岑, 李亚锦, 胡万芹()   

  1. 650101 昆明医科大学第二附属医院产科
  • 收稿日期:2024-04-01 出版日期:2024-11-15 发布日期:2024-11-12
  • 通讯作者: 胡万芹，E-mail：hwq2017@126.com
  • 基金资助:
    国家自然科学基金(82060294)

Risk Factors of Adverse Pregnancy Outcomes in Patients with Undifferentiated Connective Tissue Disease and Construction of A Nomogram Model for Predicting

WANG Yue, TANG Cen, LI Ya-jin, HU Wan-qin()   

  1. Department of Obstetrics, The Second Affiliated Hospital of Kunming Medical University, Kunming 650101, China
  • Received:2024-04-01 Published:2024-11-15 Online:2024-11-12
  • Contact: HU Wan-qin, E-mail: hwq2017@126.com

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摘要：

目的：分析未分化结缔组织病（undifferentiated connective tissue disease，UCTD）患者发生不良妊娠结局的影响因素，并构建列线图预测模型。方法：选取2020年5月—2023年5月在昆明医科大学第二附属医院产科就诊的108例UCTD孕妇，根据妊娠结局分为结局不良组（n=44）与结局良好组（n=64），采用多因素Logistic回归分析筛选影响因素，并构建列线图模型。结果：UCTD患者妊娠结局不良组的体质量指数（body mass index，BMI）、凝血酶时间（thrombin time，TT）、IgA水平和体外受精、尿蛋白升高、子痫前期比例均高于结局良好组，而使用泼尼松的比例和白蛋白水平低于结局良好组，差异有统计学意义（均P<0.05）。经Logistic回归分析显示，子痫前期（OR=8.361，95%CI：1.331~52.527，P=0.024）、BMI升高（OR=1.236，95%CI：1.011~1.510，P=0.039）、TT升高（OR=1.889，95%CI：1.043~3.423，P=0.036）、IgA升高（OR=3.027，95%CI：1.099~8.340，P=0.032）是UCTD患者发生不良妊娠结局的危险因素，白蛋白升高（OR=0.842，95%CI：0.700~0.971，P=0.021）是UCTD患者发生不良妊娠结局的保护因素。基于此构建的列线图预测模型达到了较高的区分度，曲线下面积（AUC）为0.853（95%CI：0.722~0.934）。结论：构建了预测准确度较好的UCTD患者不良妊娠结局风险预测的列线图模型，为给予及时干预改善母婴结局提供了依据。

关键词: 妊娠, 未分化结缔组织病, 妊娠结局, 影响因素, 列线图模型

Abstract:

Objective: To investigate the risk factors of adverse pregnancy outcomes in patients with undifferentiated connective tissue disease (UCTD), and to construct a nomogram prediction model. Methods: 108 pregnant women with UCTD who were treated in the obstetrics department of the Second Affiliated Hospital of Kunming Medical University from May 2020 to May 2023 were selected. All patients were divided into the poor outcome group (n=44) and the good outcome group (n=64), and multivariate Logistic regression was used to analysis risk factors. A nomogram prediction model was then developed. Results: The body mass index (BMI), thrombin time (TT), IgA levels, and the proportions of in vitro fertilization, elevated urinary protein, and preeclampsia in the poor outcome group of UCTD patients were all higher than those in the good outcome group, while the proportion of patients using prednisone and the level of albumin were lower than those in the good outcome group, with statistical significance (all P<0.05). Logistic regression analysis showed that preeclampsia (OR=8.361, 95%CI: 1.331-52.527, P=0.024), increased BMI (OR=1.236, 95%CI: 1.011-1.510, P=0.039), increased TT (OR=1.889, 95%CI: 1.043-3.423, P=0.036), and increased IgA (OR=3.027, 95%CI: 1.099-8.340, P=0.032) are independent risk factors for poor pregnancy outcomes in UCTD patients, while increased albumin (OR=0.842, 95%CI: 0.700-0.971, P=0.021) is a protective factor. According to the predictive model, a high degree of discrimination was obtained with an area under the curve (AUC) of 0.853 (95%CI: 0.722-0.934). Conclusions: The nomogram model constructed in this study has good predictive accuracy and provides a clinically available prediction tool for the prevention of adverse pregnancy outcomes in patients with UCTD.

Key words: Pregnancy, Undifferentiated connective tissue disease, Pregnancy outcome, Influencing factors, Nomogram model