Wang Jinming, Li Dan, Guo Zhenglong, Ren Yanxin, Wang Li, Liu Yuehua, Kang Kai, Shi Weili, Huang Jianmei, Liao Shixiu, Hao Yibin
Medical Genetics Institute of Henan Province, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Zhengzhou, China.
National Health Commission Key Laboratory of Birth Defects Prevention, Henan Key Laboratory of Population Defects Prevention, Zhengzhou, China.
Front Med (Lausanne). 2024 Aug 7;11:1443056. doi: 10.3389/fmed.2024.1443056. eCollection 2024.
Early prediction and intervention are crucial for the prognosis of unexplained recurrent spontaneous abortion (uRSA). The main purpose of this study is to establish a risk prediction model for uRSA based on routine pre-pregnancy tests, in order to provide clinical physicians with indications of whether the patients are at high risk.
This was a retrospective study conducted at the Prenatal Diagnosis Center of Henan Provincial People's Hospital between January 2019 and December 2022. Twelve routine pre-pregnancy tests and four basic personal information characteristics were collected. Pre-pregnancy tests include thyroid-stimulating hormone (TSH), free triiodothyronine (FT3), free thyroxine thyroid (FT4), thyroxine (TT4), total triiodothyronine (TT3), peroxidase antibody (TPO-Ab), thyroid globulin antibody (TG-Ab), 25-hydroxyvitamin D [25-(OH) D], ferritin (Ferr), Homocysteine (Hcy), vitamin B12 (VitB12), folic acid (FA). Basic personal information characteristics include age, body mass index (BMI), smoking history and drinking history. Logistic regression analysis was used to establish a risk prediction model, and receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were employed to evaluate the performance of prediction model.
A total of 140 patients in uRSA group and 152 women in the control group were randomly split into a training set ( = 186) and a testing set ( = 106). Chi-square test results for each single characteristic indicated that, FT3 ( = 0.018), FT4 ( = 0.048), 25-(OH) D ( = 0.013) and FA ( = 0.044) were closely related to RSA. TG-Ab and TPO-Ab were also important characteristics according to clinical experience, so we established a risk prediction model for RSA based on the above six characteristics using logistic regression analysis. The prediction accuracy of the model on the testing set was 74.53%, and the area under ROC curve was 0.710. DCA curve indicated that the model had good clinical value.
Pre-pregnancy tests such as FT3, FT4, TG-Ab, 25-(OH)D and FA were closely related to uRSA. This study successfully established a risk prediction model for RSA based on routine pre-pregnancy tests.
早期预测和干预对于不明原因复发性自然流产（uRSA）的预后至关重要。本研究的主要目的是基于孕前常规检查建立uRSA风险预测模型，以便为临床医生提供患者是否处于高风险的指征。
这是一项在2019年1月至2022年12月期间于河南省人民医院产前诊断中心进行的回顾性研究。收集了12项孕前常规检查和4项基本个人信息特征。孕前检查包括促甲状腺激素（TSH）、游离三碘甲状腺原氨酸（FT3）、游离甲状腺素（FT4）、甲状腺素（TT4）、总三碘甲状腺原氨酸（TT3）、过氧化物酶抗体（TPO-Ab）、甲状腺球蛋白抗体（TG-Ab）、25-羟维生素D [25-(OH)D]、铁蛋白（Ferr）、同型半胱氨酸（Hcy）、维生素B12（VitB12）、叶酸（FA）。基本个人信息特征包括年龄、体重指数（BMI）、吸烟史和饮酒史。采用逻辑回归分析建立风险预测模型，并采用受试者工作特征（ROC）曲线和决策曲线分析（DCA）评估预测模型的性能。
uRSA组共140例患者，对照组152例女性，随机分为训练集（n = 186）和测试集（n = 106）。各单一特征的卡方检验结果表明，FT3（P = 0.018）、FT4（P = 0.048）、25-(OH)D（P = 0.013）和FA（P = 0.044）与RSA密切相关。根据临床经验，TG-Ab和TPO-Ab也是重要特征，因此我们采用逻辑回归分析基于上述六个特征建立了RSA风险预测模型。该模型在测试集上的预测准确率为74.53%，ROC曲线下面积为0.710。DCA曲线表明该模型具有良好的临床价值。
FT3、FT4、TG-Ab、25-(OH)D和FA等孕前检查与uRSA密切相关。本研究成功基于孕前常规检查建立了RSA风险预测模型。
