A predictive model of pregnancy loss using pre-pregnancy endocrine and immunological parameters in women with abnormal glucose/lipid metabolism and previous pregnancy loss

• Published in: Endocrine 2024, Vol.86 (1), p.441-450
• Main Authors: Mu, Fangxiang, Wang, Mei, Zeng, Xianghui, Liu, Lin, Wang, Fang
• Format: Article
• Language: English
• Subjects: Cardiolipin; Cholesterol; Diabetes; Endocrinology; Glucose; Glucose metabolism; Humanities and Social Sciences; Immunoglobulin G; Immunoglobulin M; Internal Medicine; Iodide peroxidase; Lipid metabolism; Lipids; Medicine; Medicine & Public Health; Metabolism; multidisciplinary; Nomograms; Original; Original Article; Prediction models; Pregnancy; Risk factors; Science; Thyroxine
• ISSN: 1559-0100; 1355-008X; 1559-0100
• DOI: 10.1007/s12020-024-03937-7

Objective To investigate the clinical and endocrine risk factors for pregnancy loss in women with abnormal glucose/lipid metabolism and a history of pregnancy loss, and to develop a predictive model to assess the risk of pregnancy loss in these women’s subsequent pregnancies. Methods Patients with a history of pregnancy loss who had abnormal glucose/lipid metabolism were retrospectively included in this study, and their pre-pregnancy baseline and clinical characteristics were collected. A predictive nomogram was constructed based on the results of the multivariable logistic regression model analysis, and its calibration and discriminatory capabilities were evaluated. The internal validation was then performed and the net benefits were assessed by the clinical decision curve. Results The predictive model was eventually incorporated eight variables, including maternal age, previous pregnancy losses, anticardiolipin antibody (aCL) IgG, aCL IgM, thyroid peroxidase antibody, complement 4, free thyroxine and total cholesterol. The area under the curve (AUC) of the nomogram was 0.709, and Chi-square value and P value of the Hosmer–Lemeshow test were 12.786 and 0.119, respectively, indicating that the nomogram had a satisfactory calibration and discriminatory performance. The validation cohort showed a similar result for the discrimination of the nomogram (AUC = 0.715). The clinical decision curve demonstrated the nomogram had good positive net benefits. Conclusions This is the first study to predict the risks of subsequent pregnancy loss in women with abnormal glucose/lipid metabolism and history of pregnancy loss using pre-pregnancy clinical and endocrine parameters. This predictive nomogram may provide clinicians assistance to personalize the management of subsequent pregnancies in these patients.