Publication Details

AFRICAN RESEARCH NEXUS

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biochemistry, genetics and molecular biology

Digital ulcers predict a worse disease course in patients with systemic sclerosis

Annals of the Rheumatic Diseases, Volume 75, No. 4, Year 2016

Objective: Systemic sclerosis (SSc) is a systemic autoimmune disease with high morbidity and significant mortality. There is a great need of predictors that would allow risk stratification of patients with SSc and ultimately initiation of treatment early enough to ensure optimal clinical results. In this study, we evaluated whether a history of digital ulcers (HDU) at presentation may be a predictor of vascular outcomes and of overall clinical worsening and death in patients with SSc. Methods: Patients from the EULAR Scleroderma Trials and Research (EUSTAR) database, satisfying at inclusion the 1980 American College of Rheumatology classification criteria for SSc, who had a follow-up of at least 3 years since baseline or who have died, were included in the analysis. HDU at presentation as a predictor of disease worsening or death was evaluated by Cox proportional hazards regression analysis. Results :3196 patients matched the inclusion criteria (male sex 13.2%, 33.4% diffuse subset). At presentation, 1092/3196 patients had an HDU (34.1%). In multivariable analysis adjusting for age, gender and all parameters considered potentially significant, HDU was predictive for the presence of active digital ulcers (DUs) at prospective visits (HR (95% CI)): 2.41(1.91 to 3.03), p<0.001, for an elevated systolic pulmonary arterial pressure on heart ultrasound (US-PAPs):1.36 (1.03 to 1.80), p=0.032, for any cardiovascular event (new DUs, elevated US-PAPs or LV failure):3.56 (2.26 to 5.62), p<0.001, and for death (1.53 (1.16 to 2.02), p=0.003). Conclusions :In patients with SSc, HDU at presentation predicts the occurrence of DUs at follow-up and is associated with cardiovascular worsening and decreased survival.

Statistics
Citations: 126
Authors: 111
Affiliations: 15
Research Areas
Noncommunicable Diseases
Study Design
Cohort Study
Study Approach
Quantitative
Participants Gender
Male