A risk score for iliofemoral patients with deep vein thrombosis

Objective: Deep vein thrombosis (DVT) is a common condition with a high risk of post-thrombotic morbidity, especially in patients with a proximal thrombus. Successful iliofemoral clot removal has been shown to decrease the severity of postthrombotic syndrome. It is assumed that earlier thrombus lysis is associated with a better outcome. Generally, the earlier IFDVT is confirmed, the earlier thrombus lysis could be performed. D-Dimer levels and Wells score are currently used to assess the preduplex probability for DVT; however, some studies indicate that the D-dimer value varies depending on the thrombus extent and localization. Using D-dimer and other risk factors might facilitate development of a model selecting those with an increased risk of IFDVT that might benefit from early referral for additional analysis and adjunctive iliofemoral thrombectomy.Methods: All consecutive adult patients from a retrospective cohort of STAR diagnostic center (primary care) in Rotterdam suspected of having DVT between September 2004 and August 2016 were assessed for this retrospective study. The diagnostic workup for DVT including Wells score and D-dimer were performed as well as complete duplex ultrasound examination. Patients with objective evidence of DVT were categorized according to thrombus localization using the Lower Extremity Thrombolysis classification. Logistic regression analysis was done for a model predicting IFDVT. The cutoff value of the model was determined using a receiver operating characteristic curve.Results: A total of 3381 patients were eligible for study recruitment, of whom 489 (14.5%) had confirmed DVT. We developed a multivariate model (sensitivity of 77% and specificity of 82%; area under the curve, 0.90; 0.86-0.93) based on D-dimer, Wells score, age, and anticoagulation use, which is able to distinguish IFDVT patients from all patients suspected of DVT.Conclusions: This multivariate model adequately distinguishes IFDVT among all suspected DVT patients. Practically, this model could give each patient a preduplex risk score, which could be used to prioritize suspected IFDVT patients for an immediate imaging test to confirm or exclude IFDVT. Further validation studies are needed to confirm potential of this prediction model for IFDVT