EUREKA algorithm predicts obstetric risk and response to treatment in women with different subsets of
Francesca Pregnolato1, Maria Gerosa2,3, Maria Gabriella Raimondo2,3
1Experimental Laboratory of Immunological and Rheumatologic Researches, Istituto Auxologico Italiano, IRCCS, Cusano Milanino, Milan, Italy.
Objectives:
aPL, the serum biomarkers of APS, are the most common acquired causes of pregnancy morbidity (PM). This study investigates the impact of aPL positivity fulfilling classification criteria ('criteria aPL') and at titres lower than thresholds considered by classification criteria ('low-titre aPL') on PM and assesses the effectiveness of low-dose aspirin (LDASA), low molecular weight heparin (LMWH) and HCQ in reducing the probability of PM (PPM).
Methods:
Longitudinal data on 847 pregnancies in 155 women with persistent aPL at any titre and 226 women with autoimmune diseases and negative aPL were retrospectively collected. A generalized estimating equations model for repeated measures was applied to quantify PPM under different clinical situations.
Results:
EUREKA is a novel algorithm that accurately predicts the risk of aPL-associated PM by considering aPL titres and profiles. aPL significantly impact PPM when at low titres and when fulfilling classification criteria. PPM was further stratified upon the aPL tests: aCL IgG/IgM and anti-β2-glycoprotein I (β2GPI) IgM, alone or combined, do not affect the basal risks of PPM, an increase occurs in case of positive LA or anti-β2GPI IgG. LDASA significantly affects PPM exclusively in women with low-titre aPL without anti-β2GPI IgG. The LDASA + LMWH combination significantly reduces PPM in all women with low-titre aPL and women with criteria aPL, except those carrying LA and anti-β2GPI IgG. In this group, the addition of HCQ further reduces PPM, although not significantly.
Conclusion:
EUREKA allows a tailored therapeutic approach, impacting everyday clinical management of aPL-positive pregnant women.
