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DataSheet_1_Four clinical and biological phenotypes in antiphospholipid syndrome: a cluster analysis of 174 patients with antinuclear antibody tests.docx

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NIAID Data Ecosystem2026-05-01 收录
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https://figshare.com/articles/dataset/DataSheet_1_Four_clinical_and_biological_phenotypes_in_antiphospholipid_syndrome_a_cluster_analysis_of_174_patients_with_antinuclear_antibody_tests_docx/25242334
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IntroductionAntiphospholipid syndrome (APS) is an autoimmune thrombotic disease with various systemic presentations. This study aimed to identify homogeneous groups of patients based on a non-supervised hierarchical cluster analysis and assess the rate of relapse associated with antinuclear antibodies (ANA). MethodsThis retrospective observational study enrolled patients, over a 90-month period, who had APS as defined by the 2006 Sydney classification criteria, and for whom ANA workup was performed. Agglomerative unsupervised hierarchical clustering was conducted to classify patients into subgroups using 24 variables reflecting a range of clinical and biological baseline features associated with APS. ResultsHundred and seventy-four patients were included and were categorized into four phenotypes. Cluster 1 (n=73) associated mostly middle-aged men with risk factors for cardiovascular disease. Obstetrical APS with low-risk thrombosis made up cluster 2 (n=25). Patients with venous thromboembolism (VTE), microvascular findings and double/triple positive APL antibodies (50%) were represented in cluster 3 (n=33). Whereas cluster 4 (n=43) characterized a predominantly female subpopulation with positive ANA and systemic lupus (n=23) that exhibited a high thrombotic risk and more frequent relapses (n=38) (p<0.001). ConclusionsThis study identified four homogenous groups of patients with APS listed as: i) cardiovascular and arterial risk, ii) obstetrical, iii) VTE and microvascular, and iv) ANA-positive APS. We found that ANA-positivity was associated with higher rates of relapse. Applying ANA status to classification criteria could constitute a novel approach to tailoring management for APS, based on phenotypic patterns and risk assessment.
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2024-02-19
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