Abstract
Introduction: Pulmonary arterial hypertension is a major cause of mortality in systemic sclerosis. N-terminal probrain natriuretic peptide (NT-proBNP) has emerged as a candidate biomarker that may enable the early detection of systemic sclerosis-related pulmonary arterial hypertension (SSc-PAH). The objective of our study was to incorporate NT-proBNP into a screening algorithm for SSc-PAH that could potentially replace transthoracic echocardiography (TTE) as a more convenient and less costly “first tier” test. Methods: NT-proBNP levels were measured in patients from four clinical groups: a group with right heart catheter (RHC)-diagnosed SSc-PAH before commencement of therapy for PAH; a group at high risk of SSc-PAH based on TTE; a group with interstitial lung disease; and systemic sclerosis (SSc) controls with no cardiopulmonary complications. NT-proBNP levels were compared by using ANOVA and correlated with other clinical variables by using simple and multiple linear regression. ROC curve analyses were performed to determine the optimal cut point for NT-proBNP and other clinical variables in prediction of PAH. Results: NT-proBNP was highest in the PAH group compared with other groups (P < 0.0001), and higher in the risk group compared with controls (P < 0.0001). NT-proBNP was positively correlated with systolic pulmonary artery pressure (PAP) on TTE (P < 0.0001), and mean PAP (P = 0.013), pulmonary vascular resistance (P = 0.005), and mean right atrial pressure (P = 0.006) on RHC. A composite model wherein patients screened positive if NT-proBNP was ≥ 209.8 pg/ml, and/or DLCOcorr was < 70.3% with FVC/DLCOcorr ≥ 1.82, had a sensitivity of 100% and specificity of 77.8% for SSc-PAH. Conclusion: We have proposed a screening algorithm for SSc-PAH, incorporating NT-proBNP level and PFTs. This model has high sensitivity and specificity for SSc-PAH and, if positive, should lead to TTE and confirmatory testing for PAH. This screening algorithm must be validated prospectively.
| Original language | English |
|---|---|
| Article number | R143 |
| Pages (from-to) | 1-10 |
| Number of pages | 10 |
| Journal | Arthritis Research and Therapy |
| Volume | 14 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2012 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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