Literature DB >> 28504829

Prediction of thrombophilia in patients with unexplained recurrent pregnancy loss using a statistical model.

Tongfei Wang1, Xiaomin Kang1, Liying He1, Zhilan Liu1, Haijing Xu1, Aimin Zhao1.   

Abstract

OBJECTIVE: To establish a statistical model to predict thrombophilia in patients with unexplained recurrent pregnancy loss (URPL).
METHODS: A retrospective case-control study was conducted at Ren Ji Hospital, Shanghai, China, from March 2014 to October 2016. The levels of D-dimer (DD), fibrinogen degradation products (FDP), activated partial thromboplastin time (APTT), prothrombin time (PT), thrombin time (TT), fibrinogen (Fg), and platelet aggregation in response to arachidonic acid (AA) and adenosine diphosphate (ADP) were collected. Receiver operating characteristic curve analysis was used to analyze data from 158 UPRL patients (≥3 previous first trimester pregnancy losses with unexplained etiology) and 131 non-RPL patients (no history of recurrent pregnancy loss). A logistic regression model (LRM) was built and the model was externally validated in another group of patients.
RESULTS: The LRM included AA, DD, FDP, TT, APTT, and PT. The overall accuracy of the LRM was 80.9%, with sensitivity and specificity of 78.5% and 78.3%, respectively. The diagnostic threshold of the possibility of the LRM was 0.6492, with a sensitivity of 78.5% and a specificity of 78.3%. Subsequently, the LRM was validated with an overall accuracy of 83.6%.
CONCLUSION: The LRM is a valuable model for prediction of thrombophilia in URPL patients.
© 2017 International Federation of Gynecology and Obstetrics.

Entities:  

Keywords:  Logistic regression model; ROC curve; Thrombophilia; Unexplained recurrent pregnancy loss

Mesh:

Substances:

Year:  2017        PMID: 28504829     DOI: 10.1002/ijgo.12213

Source DB:  PubMed          Journal:  Int J Gynaecol Obstet        ISSN: 0020-7292            Impact factor:   3.561


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