Publication: Exploring the association between autoantibody profiles and the development of digital ulcers in systemic sclerosis patients: a comprehensive analysis
Program
KU-Authors
KU Authors
Co-Authors
Yamancan, G.
Karatas, A.
Erden, A.
Sari, A.
Babayigit, A.
Guler, A. Avanoglu
Dogru, A.
Avcu, A.
Yilmaz, A.
Sulu, B.
Publication Date
Language
Type
Embargo Status
No
Journal Title
Journal ISSN
Volume Title
Alternative Title
Abstract
Background:
Systemic sclerosis (SSc) is a chronic, multisystemic autoimmune disease. Vasculopathy is a prevalent feature in nearly all patients with SSc, and it can manifest as digital ulcers (DUs) in a subset of these individuals. DUs represent a significant complication, with the potential to lead to tissue necrosis, infection, and even auto-amputation, thereby severely impacting patients' daily activities and overall quality of life [1]. The relationship between the development of DUs and the presence of autoantibodies is crucial for understanding disease progression and improving patient management strategies [2].
Objectives:
The principal aim of this study was to examine the association between the emergence of DUs and the presence of autoantibodies in patients diagnosed with SSc. Through the analysis of clinical parameters and autoantibody profiles, the objective was to identify potential predictors of DUs development, with a view to enhancing our understanding of the disease's progression and informing therapeutic strategies.
Methods:
This study included 305 patients who were diagnosed with SSc within the last year. Clinical parameters such as gender, age, the onset age of Raynaud's phenomenon, the onset age of the first symptom other than Raynaud's phenomenon, disease duration, and organ involvement were meticulously recorded. Furthermore, we collected data on smoking history, the presence of digital ulcers, digital gangrene, calcinosis, the modified Rodnan skin score (mRSS), and existing comorbidities. A thorough statistical analysis of the gathered data was conducted to identify significant relationships among these variables, employing binomial logistic regression to assess the associations between autoantibody profiles and DUs development.
Source
Publisher
Elsevier
Subject
Rheumatology
Citation
Has Part
Source
Annals of the Rheumatic Diseases
Book Series Title
Edition
DOI
10.1016/j.ard.2025.06.1975
