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Details

Autor(en) / Beteiligte
Titel
Significance of fully automated tests for the diagnosis of antiphospholipid syndrome
Ist Teil von
  • Thrombosis research, 2016-10, Vol.146, p.1-6
Ort / Verlag
United States: Elsevier Ltd
Erscheinungsjahr
2016
Link zum Volltext
Quelle
MEDLINE
Beschreibungen/Notizen
  • Abstract Antiphospholipid antibodies (aPLs) can vary both immunologically and functionally, thus it is important to effectively and correctly identify their presence when diagnosing antiphospholipid syndrome. Furthermore, since many immunological/functional tests are necessary to measure aPLs, complete examinations are often not performed in many cases due to significant burden on the testing departments. To address this issue, we measured aPLs defined according to the classification criteria (anticardiolipin antibody: aCL) IgG/IgM and anti-β2 glycoprotein I antibody (aβ2 GPI) (IgG/IgM) as well as non-criteria antibodies (aCL IgA, aβ2 GPI IgA and aβ2 GPI domain I), in a cohort of 211 patients (61 APS, 140 disease controls and 10 healthy individuals). APLs were measured using a fully automated chemiluminescent immunoassay instrument (BIO-FLASH®/ACL AcuStar®) and with conventional ELISA tests. We demonstrated that both sensitivity and accuracy of diagnosis of aCL IgG and aβ2 GPI IgG were high, in agreement with the past reports. When multiple aPLs were examined, the accuracy of diagnosis increased. The proportion of APS patients that were positive for 2 or more types of aPLs (47/61, 77%) was higher than that of patients with systemic lupus erythematosus (SLE)(3/37, 9%), those with non-SLE connective tissues diseases (1/53,2%), those with other diseases or healthy volunteers. Based on these findings, it was concluded that the fully automated chemiluminescent immunoassay instrument, which allows the simultaneous evaluation of many types of aPLs, offers clear advantages for a more complete, more rapid and less labor-intensive alternative to running multiple ELISA and could help in better diagnosis for suspected APS patients.

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