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. 2020 Jul:191:42-49.
doi: 10.1016/j.thromres.2020.03.025. Epub 2020 Apr 23.

Developing a model for predicting venous thromboembolism in obese pregnant women in a national study

Affiliations

Developing a model for predicting venous thromboembolism in obese pregnant women in a national study

Julia Ellis-Kahana et al. Thromb Res. 2020 Jul.

Abstract

Introduction: Venous thromboembolism (VTE) in pregnancy and postpartum is a leading cause of maternal morbidity and mortality in developed countries, where obesity is a known risk for this complication. Current guidelines vary in which patients qualify for VTE prophylaxis, precluding a uniform approach for management. We sought to derive a risk prediction model for VTE in obese pregnant women.

Materials and methods: We performed a retrospective cohort analysis using the Consortium on Safe Labor (CSL) database. Women ages 16-45 who were pregnant with singletons and had an obese body mass index (>30 kg/m2) were included in our study population. Multivariable logistic regression was used in order to identify predictors of venous thromboembolism.

Results: Of the 83,500 women who met inclusion criteria, on average women were 27.8 years old, 38.6 weeks gestation, with body mass index of 35.8, and cesarean delivery incidence of 35.2%. 109 women (0.13%) experienced a VTE event. Independent predictors of VTE in our final multivariable predictive model included: mode of delivery, body mass index, pregestational diabetes, chronic heart disease, preeclampsia, blood transfusion (intrapartum or postpartum), prenatal history of thromboembolic disorder, and postpartum maternal length of stay. A receiver operating characteristic curve was developed to assess the model; area under the curve was 0.826.

Conclusions: We developed a strong predictive model using a large, retrospective database to distinguish risk of VTE in obese pregnant women, which may provide the foundation for future protocol development of obstetrical thromboprophylaxis in obese women.

Keywords: Low molecular weight heparin; Maternal morbidity; Obesity; Pregnancy; Thromboprophylaxis; Venous thromboembolism.

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Conflict of interest statement

Declaration of competing interest The authors report no conflict of interest.

Figures

Figure 1.
Figure 1.. Equation for Prediction Model Calculator using Table 3.
Where: P=predicted probability of VTE; Csec=Cesarean section (CD), enter 1 if CD, enter 0 if vaginal delivery; BMInew=Maternal BMI on admission, enter continuous BMI value; Prediab=Pre-gestational diabetes, enter 1 if present, 0 if absent; Heartdis=Chronic heart disease, enter 1 if present, 0 if absent; Preeclamp=Preeclampsia, enter 1 if present, 0 if absent; Bloodtrans=Blood transfusion, enter 1 if present, 0 if absent; Antethrombo=Prenatal history of thromboembolic disorder, enter 1 if present, 0 if absent; momLOS=Maternal length of stay, enter continuous LOS value (in days).
Figure 2.
Figure 2.
Receiver operating characteristic curve for prediction model of venous thromboembolism in obese pregnant women (Table 3)
Figure 3.
Figure 3.. Equation for Prediction Model Calculator using Table 4.
Where: P=predicted probability of VTE; Csec=Cesarean section (CD), enter 1 if CD, enter 0 if vaginal delivery; BMInew=Maternal BMI on admission, enter continuous BMI value; GA=Gestational age, enter continuous value in weeks; Prediab=Pre-gestational diabetes, enter 1 if present, 0 if absent; Heartdis=Chronic heart disease, enter 1 if present, 0 if absent;Preeclamp=Preeclampsia, enter 1 if present, 0 if absent; Bloodtrans=Blood transfusion, enter 1 if present, 0 if absent; Druguse=Drug use during pregnancy, enter 1 if present, 0 if absent;momLOS=Maternal length of stay, enter continuous LOS value (in days).
Figure 4.
Figure 4.
Receiver operating characteristic curve for prediction model of venous thromboembolism in obese pregnant women without antepartum thromboembolic disorder (Table 4)
Figure 5.
Figure 5.
Observed by Predicted Calibration by Predicted Decile, Overall
Figure 6.
Figure 6.
Observed by Predicted Calibration by Decile, Top Prediction Decile

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