A novel predictive model for evaluating thrombus regression in postpartum venous thromboembolism patients

Key Points

• The aim is to develop a predictive model for thrombus regression in postpartum patients with venous thromboembolism (VTE).
• Data analysis from three cohorts of postpartum VTE patients
• Development of a random forest (RF) model
• Identification of key predictors including anti-Xa activity and D-dimer levels
• The RF model was identified as the optimal predictive model for thrombus regression events
• Key predictors include anti-Xa activity, antithrombin III levels, D-dimer levels, and BMI
• The model may assist in assessing changes in the thrombotic state of postpartum VTE patients

Study Design

Structured PICO

Abstract