SAT0550 THROMBIN GENERATION ASSAY AND GLOBAL ANTIPHOSPHOLIPID SCORE (GAPSS) FOR RISK STRATIFICATION IN ANTIPHOSPHOLIPID SYNDROME

Abstract

Background: Thrombin generation assay (TGA) is a simple and reproducible technique, that could potentially be used in coagulation laboratories, that measures the concentration of generated thrombin after plasma recalcification. The clinical usefulness of TGAs in assessing thrombotic risk has been a matter of growing interest, however, it has not been applied on a large scale to a large cohort of patients with antiphospholipid syndrome (APS). Objectives: The aim of our study was to assess the potential use of TGA in monitoring the pro-coagulant state in APS patients and its role in predicting the relative risk score in developing APS clinical manifestations, by comparing its parameters to the validated global antiphospholipid score (GAPSS). Methods: After chart-reviewing all APS patients that presented at San Giovanni Bosco Hospital in the last 5 years, we enrolled 4 groups of patients for the sake of this study, matched for age and sex. Clinical and laboratory characteristics were retrospectively collected. Inclusion criteria were as follows: Group A) Fulfilled the diagnosis of Thrombotic APS defined as per Sidney criteria [1]: 60. Group B) Patients with aPL positivity, but with no clinical manifestations of APS defined as per Sidney criteria [1]: 30. Group C) Patients treated with Warfarin (target INR 2-3), negative for aPL and other autoimmune conditions: 60. Group D) Healthy Controls: 60. Results: Figure 1 resumes the representative TGA profiles between groups. Healthy controls and patients with aPL positivity, but no APS clinical manifestations, had similar TGA profiles [mean tLag (min) 9.6 ±2.9 v.s. 8.6 ±3.2; mean tPeak (min) 16.2 ±4.7 v.s. 13.7 ±5.8; mean Peak (nM) 209.2 ±103.8 v.s. 265.4 ±106.2; mean AUC (nM) 2023 ±489.2 v.s. 2057.1 ±571.8, respectively]. When analyzing the TGA profile curve of the patient with APS compared with healthy controls and aPL positive patients with no clinical manifestations of APS, we observed a statistically significant higher tLag (13.3 ±5.9 min; p= 0.003; p= 0.008, respectively) and tPeak (21.3 ±9.2 min; p= 0.006; p= 0.014, respectively) with lower Peak (99.1 ±71.8 nM; p Furthermore, also when analyzing the TGA profile of APS patients compared to patients treated with warfarin and no APS, APS patients had significant higher tLag (13.3 ±5.9 min v.s. 8.2 ±2.1; p When analyzing a correlation model between GAPSS and TGA parameters, we observed a statistically significant correlation for tLag (Pearson 0.444; p= 0.002), tPeak (Pearson 0.464; p= 0.001) and Peak (Pearson -0.382; p= 0.008). AUC showed no statistical significant correlation (Pearson -0.255; p= 0.083). Correlation analysis between GAPSS and TGA parameters is resumed in Figure 2. When stratifying the patients for clinical manifestations, patients with a more aggressive clinical profile, who experienced both arterial and venous thrombosis, when compared with patients who had an history of either arterial or venous thrombosis, had significant different levels of GAPSS (mean GAPSS 17.5 ± 2.1 v.s. 12.4± 5.5, respectively; p= 0.001) and had a significant higher tLag (16.5 ± 7.4 v.s. 11.9± 4.5, respectively; p= 0.048) and tPeak (27.4 ± 13.5 v.s. 19± 6.3, respectively; p= 0.027). Conclusion: TGA might represent a valuable tool to stratify the risk of developing clinical manifestations in APS patients.