Prediction of Unexplained Recurrent Miscarriages Using Thromboelastography

Abstract

Jinjin Xu,1– 3,* Yan Yang,1– 3,* Guixue Guan,1– 3,* Yuan Gao,1– 3 Qian Sun,1– 3 Guangwei Yuan,4 Xiaozuo Zhang,1– 3 Jingyun Yang,5,6 Wen Yang,1– 3 Zuobin Zhu,7 Conghui Han8,9 1Department of Gynecology, The First People’s Hospital of Lianyungang, Lianyungang, Jiangsu, People’s Republic of China; 2Department of Gynecology, The First Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang, Jiangsu, 22206, People’s Republic of China; 3Medical University, Lianyungang, Jiangsu, China & Department of Gynecology, Xuzhou Medical University Affiliated Hospital of Lianyungang, Lianyungang, Jiangsu, People’s Republic of China; 4College of Professional Studies, Northeastern University, Boston, MA, USA; 5Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, USA; 6Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA; 7Department of Genetics, Xuzhou Engineering Research Center of Medical Genetics and Transformation, Key Laboratory of Genetic Foundation and Clinical Application, Xuzhou Medical University, Xuzhou, Jiangsu, People’s Republic of China; 8Department of Urology, Xuzhou Clinical School of Xuzhou Medical University, Xuzhou, Jiangsu, People’s Republic of China; 9Department of Urology, Xuzhou Central Hospital, Xuzhou, Jiangsu, People’s Republic of China*These authors contributed equally to this workCorrespondence: Wen Yang, Department of Gynecology, The First Affiliated Hospital of Kangda College of Nanjing Medical University, Zhenhua Road, Lianyungang, Jiangsu, 222061, People’s Republic of China, Tel [phone], Email [email protected] Conghui Han, Department of Urology, Xuzhou Clinical School of Xuzhou Medical University, 199 Jiefang South Road, Xuzhou, Jiangsu, 221000, People’s Republic of China, Tel [phone], Email [email protected]: This study investigates the thromboelastography (TEG) changes in patients with unexplained recurrent spontaneous abortion (URSA) to identify effective diagnostic markers for URSA.Methods: We retrospectively analyzed 160 URSA patients from the Gynecology Department of the First People’s Hospital of Lianyungang (June 2017 - June 2020) and compared them with 190 healthy, fertile women without adverse pregnancy histories (control group). TEG parameters were assessed using logistic regression, applying stepwise selection for model optimization. Model performance was evaluated using Receiver Operating Characteristic (ROC) curves, determining sensitivity and specificity. The Youden index identified optimal cut points for predictive probabilities.Results: Significant differences were observed between the URSA and control groups in coagulation reaction time (R), clot formation time (K), clot formation rate (Angle-α), and maximum clot strength (MA) (P< 0.05). Multivariable logistic regression identified R, Angle-α, and MA as independent URSA risk factors. The model demonstrated excellent discrimination (AUC: 0.940; 95% CI: 0.918– 0.962). The optimal cut point of predictive probability (Youden index) was P=0.355, yielding a sensitivity of 0.925 and specificity of 0.795.Conclusion: URSA patients exhibit a hypercoagulable state even when not pregnant. More research is needed to validate our findings and explore the potential clinical implications of anticoagulants in treating URSA.Keywords: unexplained recurrent spontaneous abortion, thromboelastography, prothrombotic state, coagulation function

Keywords

• unexplained recurrent spontaneous abortion
• thromboelastography
• prothrombotic state
• coagulation function