Jinming Wang ^1* Dan Li ^2* Zhenglong Guo ¹ Yanxin Ren ^1* Li Wang ^1* Yuehua Liu ^3* Kai Kang ⁴ WEILI SHI ¹ Jianmei Huang ¹ Shixiu Liao ^1* Yibin Hao ^1*

• ¹ Henan Provincial People's Hospital, Zhengzhou, China
• ² PLA Strategic Support Force Information Engineering University, Zhengzhou, China
• ³ Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, China
• ⁴ Henan Provincial Center for Disease Control and Prevention, zhengzhou, China

Introduction: 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. Methods: 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. Results: A total of 140 patients in uRSA group and 152 women in the control group were randomly split into a training set (n=186) and a testing set (n=106). Chi-square test results for each single characteristic indicated that, FT3 (P=0.018), FT4 (P=0.048), 25-(OH) D (P=0.013) and FA (P=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. Conclusions: Pre-pregnancy tests such as FT3, FT4, TG-Ab, 25-(OH)D and FA are were closely related to uRSA. This study successfully established a risk prediction model for RSA based on routine pre-pregnancy tests.