Systemic sclerosis (SSc, AKA scleroderma) is an autoimmune condition characterized by endothelial damage and progressive fibrosis of the skin and internal organs. One of the leading causes of morbidity and mortality in patients with SSc is pulmonary hypertension (PH), which is estimated to occur in up to 31% of high risk SSc patients. Early detection of patients with SSc-PH may lead to improved outcomes and although there have been concerted efforts to accurately screen for SSc-PH, these patients continue to present with advanced disease and suffer from poor survival. Therefore, better methods to screen for patients with PH and, perhaps more importantly, to screen for those at risk for PH development are desperately needed. Since PH and SSc are disorders originating from the endothelium, biomarkers that reflect endothelial damage are very promising tools to identify early disease. Such potential biomarkers include endothelial microparticles, asymmetric dimethylarginine (ADMA), pentraxin-3, and soluble endoglin. No previous study has used a combination of these biomarkers to detect the presence of PH in patients with SSc, or studied the novel concept of exercise-induced changes in biomarker levels. The investigators will collect the above listed endothelial biomarkers before and after exercise, and combine these levels with exercise echocardiogram findings, and routine clinical information to derive a composite detection score for the early identification of systemic sclerosis-associated PH.
Study Type
OBSERVATIONAL
Enrollment
56
No intervention
University Medical Center-New Orleans
New Orleans, Louisiana, United States
RECRUITINGComposite pulmonary hypertension detection score
A score will be derived by incorporating biomarkers, exercise echo results, pulmonary function tests, autoantibody status, 6-minute walk results, etc. into a linear regression model
Time frame: At baseline
Composite pulmonary hypertension detection score
A score will be derived by incorporating biomarkers, exercise echo results, pulmonary function tests, autoantibody status, 6-minute walk results, etc. into a linear regression model
Time frame: At 12 months
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.