Abstract 15903: An Improvement of Score Models in the Prediction of Deep Vein Thrombosis of Upper and Lower Limbs in Hospitalized Patients

Abstract

Introduction:Deep Vein Thrombosis (DVT) of both lower and upper limbs is increasingly being recognized as a clinical entity in patients with chronic diseases hospitalized for several comorbidities. The occurrence of DVT in sites other than lower limbs is an emerging clinical presentation in a setting of a Department of Medicine. The relationship between score models, based on risk factors, symptoms and clinical signs of lower limbs DVT, and circulating biomarkers is not well studied. Hypothesis:We hypothesized to give an additional value to score models using circulating biomarkers in the prediction of DVT in patients hospitalized in Internal Medicine Department. Methods:We prospectively recruited 178 consecutive patients who presented a D-dimer value >500 ng/ml. In each patient Wells modified score for DVT, Hamilton score, Kahn score and St. André Hospital score were applied. We measured serum levels of albumin (%) and protein S (%). Diagnosis of DVT was made by Extended Compression Ultra-Sonography (ECUS) standardized procedure. All patients underwent also an angiographic-CT-scan Results:In 85 (48%) patients the diagnosis of DVT was confirmed. Sites of DVT were as follows: Lower limbs venous thrombosis n=71 (84%); Upper limb venous thrombosis n=8 (9%); portal vein thrombosis n=6 (7%). Patients with DVT had significantly lower albumin levels as compared with controls (mean ± SD 47.6 ± 7.9 vs 55.4 ± 4.6 %, respectively, P<0.001) and lower Protein S (60.7 ± 26.3 vs. 87.6 ± 11.9 %, P<0.001). In this setting, the use of clinical risk scores based on symptoms and clinical signs showed low accuracy (AUC 0.690). We gave an additional value to these scores by testing in combination biomarkers and two of the best items of all clinical score models used to predict DVT: we evaluated a ROC curve analysis including value of Albumin (%), Protein S (%), previous DVT and cancer obtaining a higher accuracy (AUC 0.901, Positive Likelihood Ratio (LR+) 12.97 and Negative Likelihood Ratio (LR-) 0.17). Conclusions:This study demonstrates that biomarkers improve the prediction of clinical scores in the diagnosis of DVT of all sites in hospitalized patients.