Establishment and validation of predictive model of pregnancy loss in patients with systemic lupus erythematosus
10.3969/j.issn.1674-8115.2020.07.008
- VernacularTitle: 系统性红斑狼疮妊娠丢失预测模型的建立与验证
- Author:
Jia-Yue WU
1
Author Information
1. Shanghai Key Laboratory of Gynecologic Oncology， Department of Obstetrics and Gynecology, Renji Hospital, Shanghai Jiao Tong University School of Medicine
- Publication Type:Journal Article
- Keywords:
Predictive model;
Pregnancy;
Pregnancy loss;
Systemic lupus erythematosus (SLE)
- From:
Journal of Shanghai Jiaotong University(Medical Science)
2020;40(7):909-914
- CountryChina
- Language:Chinese
-
Abstract:
Objective: To establish and verity predictive model of pregnancy loss in systemic lupus erythematosus (SLE). Methods: A total of 338 SLE pregnant patients admitted to Renji Hospital, Shanghai Jiao Tong University School of Medicine from Sept. 2011 to May 2017 (model development group) and 131 SLE pregnant patients admitted from Jun. 2017 to Jun. 2018 (model validation group) were selected. Multivariable Logistic regression model was used to determine the predictive variables and their coefficients of pregnancy loss in model development group. The predictive model was established, the risk score classification was performed, and model validation group was used for external validation. Results: Multivariate Logistic regression analysis showed that unplanned pregnancy (P=0.032), low complement C3 (P=0.002) and 24 h urinary protein ≥ 1.0 g (P=0.000) were the risk factors of the predictive model of SLE pregnancy loss. When the risk score of the model was 0-3, the risk of SLE pregnancy loss was low, and when the risk score is more than 3, it is high risk, with a sensitivity and specificity of 60.5% and 93.3%, respectively. The model was used in the model validation group for external validation, and the prediction accuracy of SLE pregnancy loss was 90.1%. Conclusion: The predictive model of SLE pregnancy loss can help clinicians efficiently screen the high-risk population of SLE pregnancy loss in order to take relevant measures as soon as possible to obtain better pregnancy outcomes.
