Natriuretic Peptides Improve Classification of People at Low Risk of Atrial Fibrillation after Stroke

Author:

Cameron AlanORCID,Arnold Markus,Katsas Georgios,Yang Jason,Quinn Terence J,Abdul-Rahim Azmil H,Campbell Ross,Docherty Kieran,De Marchis Gian MarcoORCID,Arnold Marcel,Kahles Timo,Nedeltchev Krassen,Cereda Carlo,Kaegi Georg,Bustamante Alejandro,Montaner Joan,Ntaios GeorgeORCID,Foerch Christian,Spanaus Katharina,Von Eckardstein Arnold,Dawson Jesse,Katan Mira

Abstract

AbstractBackgroundProlonged cardiac monitoring (PCM) increases atrial fibrillation detection after stroke (AFDAS) but access is limited. We aimed to assess the utility of midregional pro-atrial natriuretic peptide (MR-proANP) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) to identify people who are unlikely to have AFDAS and improve healthcare resource allocation for PCM..MethodsWe analysed people from the BIOSIGNAL (Biomarker Signature of Stroke Aetiology) study with ischaemic stroke, no known AF and ≥3 days cardiac monitoring. External validation was in the PRECISE (Preventing Recurrent Cardioembolic Stroke: Right Approach, Right Patient) study of 28-days cardiac monitoring after stroke.The main outcome is no AFDAS. We assessed the discriminatory value of MR-proANP and NT-proBNP combined with clinical variables to identify people with no AFDAS. We determined the net reduction in people who would undergo PCM using the models with 15% AFDAS threshold probability.ResultsWe included 621 people from BIOSIGNAL. The clinical model included age, National Institutes of Health Stroke Scale score, lipid-lowering therapy, creatinine and smoking status. The AUROC was 0.68 (95%CI 0.62-0.74) with clinical variables, which improved with log10MR-proANP (0.72,0.66-0.78;p=0.001) or log10NT-proBNP (0.71,0.65-0.77;p=0.009). Performance was similar for log10MR-proANP versus log10NT-proBNP (p=0.28).In 239 people from PRECISE, the AUROC for clinical variables was 0.68 (0.59-0.76), which improved with log10NT-proBNP (0.73,0.65-0.82;p<0.001) or log10MR-proANP (0.79,0.72-0.86;p<0.001). Performance was better with log10MR-proANP versus log10NT-proBNP (p=0.03).The models could reduce the number who would undergo PCM by 30% (clinical+log10MR-proANP), 27% (clinical+log10NT-proBNP) or 20% (clinical).ConclusionsMR-proANP and NT-proBNP help classify people who are unlikely to have AFDAS and could reduce the number who need PCM by 30%.

Publisher

Cold Spring Harbor Laboratory

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