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Screening for Pulmonary Hypertension in Connective Tissue Diseases: Literature Review and Multidisciplinary Consensus
Alper Sarı1, Duygu Temiz Karadağ2, Mustafa Erdoğan3
1Department of Rheumatology, Etlik City Hospital, Ankara, Türkiye.
Abstract:
Patients with connective tissue diseases (CTDs) are at increased risk for the development of pulmonary hypertension (PH) and pulmonary arterial hypertension (PAH), which is a specific subtype of PH characterized by progressive remodeling of precapillary pulmonary arterioles. Evidence suggests that early detection of PH through screening in this patient group may be associated with better outcomes. Various methods, including cardiac and thoracic imaging, blood biomarkers, pulmonary function tests, and composite algorithms, have been employed for screening of PH. Here, a multidisciplinary consensus group composed of 10 rheumatologists, 4 cardiologists, and 3 pulmonologists was formed with the objective of developing recommendations and a screening algorithm for PH in patients with CTD. A systematic literature review in the PubMed database focusing on the studies evaluating the performance of different screening methods on detecting PH in CTDs was conducted. The literature review identified 33 relevant articles after title, abstract, and full-text evaluation. The included studies had considerable heterogeneity regarding hemodynamic definitions of PH and PAH, the diagnostic cutoff values of screening methods utilized, and the symptom status of the patients. With the exception of 2 studies, the populations in included studies consisted of only patients with systemic sclerosis (SSc). Consensus-based recommendations and an algorithm prioritizing echocardiography for screening and early detection of PH in patients with SSc and patients with CTD exhibiting overlap features of SSc were developed based on literature data and incorporating the perspectives of group members. No recommendations could be made for asymptomatic patients with CTDs without overlap features of SSc due to limited data.
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