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ORIGINAL RESEARCH article
Front. Immunol.
Sec. Autoimmune and Autoinflammatory Disorders : Autoimmune Disorders
Volume 15 - 2024 |
doi: 10.3389/fimmu.2024.1459548
This article is part of the Research Topic Reproductive Issues In Lupus, Antiphospholipid Syndrome And Other Autoimmune Rheumatic Diseases: Highlights From RheumaPreg2023 View all 6 articles
Development of a risk prediction model for the first occurrence of thrombosis in patients with OAPS
Provisionally accepted- 1 Xijing Hospital, Air Force Medical University, Xi’an, China
- 2 Department of Clinical Immunology, Xijing Hospital, Fourth Military Medical University, Xi’an, Shanxi Province, China
- 3 Xijing Hospital of Digestive Diseases, Air Force Medical University, Xi'an, China
- 4 Xijing Hospital of Digestive Diseases,, Air Force Medical University, Xi'an, China
The aim of this study is to assess the risk factors associated with thrombotic events in obstetric antiphospholipid syndrome (OAPS) patients and to develop a predictive model specifically tailored to predict the risk of postpartum thrombosis in OAPS patients without prior thrombotic events. This research seeks to enhance clinician's awareness regarding the postpartum care and monitoring of OAPS patients.: A retrospective study was conducted at the First Affiliated Hospital of the Fourth Military Medical University including 269 consecutive inpatients diagnosed with antiphospholipid syndrome (APS) from July 1, 2008 to July 31, 2022. All participants met the 2006 Sydney APS classification criteria or the "non-criteria OAPS classification". Out of 98 candidate clinical and laboratory parameters considered, 40 potential variables were selected for analysis based on expert opinion. The logistic regression mode with the Least Absolute Shrinkage and Selection Operator (LASSO)were used to identify optimal predictive characteristics. All samples were included in the model building and a nomogram was generated based on these characteristics. The differentiation, calibration, and clinical utility of the predictive model were evaluated using the area under the curve (AUC), calibration curve, and decision curve analysis.The model was also validated by a 1000 bootstrap tests.Results: 126 patients with OAPS were enrolled, and a total of 89 OAPS patients who had never experienced thrombosis were retrospectively analyzed. After 3 years followup, 32.58% of the patients (29/89) developed thrombosis. In order to create, LASSO logistic regression identified three optimal variables: the platelet count less than 125×109/L, more than one positive aPLs (antiphospholipid antibody), and the use of low molecular weight heparin (LMWH) or low dose aspirin (LDA) after delivery. A predictive model was conducted using these three predictive indicators for patients with OAPS who experience thrombosis for the first-time. This prediction model has good distinction, good calibration, and fair clinical practicality.Our model has good predictive ability in assessing the risk of thrombosis in patients with OAPS without prior thrombotic events. This model is easy to predict, has good discriminability and calibration, and can be utilized as a routine tool for thrombus screening in OAPS patients.
Keywords: Antiphospholipid Syndrome, Thrombosis, obstetric antiphospholipid syndrome, Antiphospholipid antibodies, nomogram
Received: 04 Jul 2024; Accepted: 17 Sep 2024.
Copyright: © 2024 Gao, Zheng, Wang, Jia, Wan, Han, Zheng, Liu, Zheng, Wu and Zhu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Yan Zheng, Department of Clinical Immunology, Xijing Hospital, Fourth Military Medical University, Xi’an, Shanxi Province, China
Zhuo Wang, Xijing Hospital of Digestive Diseases, Air Force Medical University, Xi'an, China
Qing Han, Department of Clinical Immunology, Xijing Hospital, Fourth Military Medical University, Xi’an, Shanxi Province, China
Renli Liu, Department of Clinical Immunology, Xijing Hospital, Fourth Military Medical University, Xi’an, Shanxi Province, China
Zhaohui Zheng, Department of Clinical Immunology, Xijing Hospital, Fourth Military Medical University, Xi’an, Shanxi Province, China
Kaichun Wu, Xijing Hospital of Digestive Diseases,, Air Force Medical University, Xi'an, China
Ping Zhu, Department of Clinical Immunology, Xijing Hospital, Fourth Military Medical University, Xi’an, Shanxi Province, China
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