Thrombotic risk assessment in antiphospholipid syndrome: do noncriteria antibodies contribute?


Creative Commons License

Uludağ Ö., ÇINAR S., McDonnell T., ÇENE E., Yalçinkaya Y., GÜL A., ...Daha Fazla

Turkish Journal of Medical Sciences, cilt.53, sa.5, ss.1067-1074, 2023 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 53 Sayı: 5
  • Basım Tarihi: 2023
  • Doi Numarası: 10.55730/1300-0144.5671
  • Dergi Adı: Turkish Journal of Medical Sciences
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, CAB Abstracts, MEDLINE, Veterinary Science Database, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.1067-1074
  • Anahtar Kelimeler: Antiphospholipid syndrome, global antiphospholipid syndrome score, non-criteria antiphospholipid antibodies, thrombotic risk
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

Background/aim: In this cross-sectional study, it was aimed to test the predictive value of noncriteria antiphospholipid antibodies (aPL) in addition to the global antiphospholipid syndrome score (GAPSS) in predicting vascular thrombosis (VT) in a cohort of patients with APS and aPL (+) systemic lupus erythematosus (SLE). Material and methods: This study included 50 patients with primary APS, 68 with SLE/APS, and 52 with aPL (+) SLE who were classified according to VT as VT ± pregnancy morbidity (PM), PM only or aPL (+) SLE. Antiphospholipid serology consisting of lupus anticoagulant (LA), anticardiolipin (aCL) immunoglobulin G (IgG)/IgM/IgA, antibeta2 glycoprotein I (aβ2GPI) IgG/IgM/IgA, antiphosphatidylserine/prothrombin (aPS/PT) IgG/IgM and antidomain-I (aDI) IgG was determined for each patient. The GAPSS and adjusted GAPSS (aGAPSS) were calculated for each patient, as previously defined. Logistic regression analysis was carried out with thrombosis as the dependent variable and high GAPSS, aCL IgA, aβ2GPI IgA, and aDI IgG as independent variables. Results: The mean GAPSS and aGAPSS of the study population were 11.6 ± 4.4 and 9.6 ± 3.8. Both the VT ± PM APS (n = 105) and PM only APS (n = 13) groups had significantly higher GAPSS and aGAPSS values compared to the aPL (+) SLE (n = 52) group. The patients with recurrent thrombosis had higher aGAPSS but not GAPSS than those with a single thrombotic event. The computed area under the receiver operating characteristic curve demonstrated that a GAPSS ≥13 and aGAPSS ≥10 had the best predictive values for thrombosis. Logistic regression analysis including a GAPSS ≥13, aCL IgA, aβ2GPI IgA, and aDI IgG showed that none of the factors other than a GAPSS ≥13 could predict thrombosis. Conclusion: Both the GAPSS and aGAPSS successfully predict the thrombotic risk in aPL (+) patients and aCL IgA, aβ2GPI IgA, and aDI IgG do not contribute to high a GAPSS or aGAPSS.