MR-proADM Predicts Exercise Capacity and Survival Superior to Other Biomarkers in PH View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2015-12

AUTHORS

Martin Kolditz, Hans-Jürgen Seyfarth, Heinrike Wilkens, Ralf Ewert, Tom Bollmann, Christiane Dinter, Sabine Hertel, Hans Klose, Christian Opitz, Ekkehard Grünig, Gert Höffken, Michael Halank

ABSTRACT

PURPOSE: Besides the established biomarker NT-proBNP, the new cardiovascular biomarkers MR-proANP, MR-proADM, Copeptin, and CT-proET-1 are promising to evaluate hemodynamics, exercise parameters, and prognosis in patients with pulmonary hypertension (PH). METHODS: 125 consecutive patients with pulmonary arterial hypertension (PAH) or chronic thromboembolic pulmonary hypertension (CTEPH) were prospectively enrolled at five German PH centers. Blood samples were taken during right heart catheterization. The primary study endpoint was the correlation between biomarkers and hemodynamic and exercise parameters. As secondary endpoint, prediction of 1-year mortality was evaluated. RESULTS: MR-proADM showed the strongest correlations with 6MWD and VO2peak, whereas NT-proBNP showed the strongest correlations with PVR, PAPm, and CI. In multivariate analysis, only MR-proADM was independently associated with exercise variables, whereas only NT-proBNP independently predicted hemodynamic parameters. All biomarkers were associated with 1-year survival, with MR-proADM showing the highest C index of 0.78. In multivariate analysis, MR-proADM predicted survival independent of age, 6-MWD, CI, RAP, and NT-proBNP. The cut-off of 1.08 nmol/l provided a sensitivity of 83 % and specificity of 66 %. CONCLUSIONS: Different biomarkers reflect distinctive disease aspects in PH. NT-proBNP best predicts hemodynamic impairment while MR-proADM strongly correlates with exercise capacity. Additionally, MR-proADM represents a promising new marker to evaluate prognosis in patients with PAH and CTEPH. Multi-marker strategies should further be evaluated. More... »

PAGES

901-910

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00408-015-9802-y

DOI

http://dx.doi.org/10.1007/s00408-015-9802-y

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1012589757

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/26363916


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