Mid-regional atrial natriuretic peptide and C-terminal pro-endothelin-1 for early diagnosis of acute heart failure in unselected older patients presenting to the emergency department

Abstract

Purpose: Symptoms and signs of heart failure (HF) are difficult to interpret in older patients. Moreover, NT-proBNP (N-terminal pro B-type natriuretic peptide) is ambiguous for the diagnosis of HF in older patients due to impairment of renal function. The recent ESC-guideline alternatively propose mid-regional atrial natriuretic peptide (MR-proANP), which has been shown to be non-inferior to NT-proBNP in the acute setting. This study investigated the diagnostic accuracy of MR-proANP for diagnosis of HF in unselected older patients. We also examined whether a tree-building algorithm is useful for early diagnosis Methods: This prospective observational study recruited 302 consecutive older patients (age 81 ±6 years, 49% men) presenting to hospital as an emergency with suspected HF and acute onset of symptoms. In all patients, electrocardiographic (ECG) and echocardiographic exams were performed and NT-proBNP (gray zone ≥ 300 and <1800 pg/mL, cut-off ≥1800 pg/mL) was immediately measured. To determine the final diagnosis of HF for each patient, two cardiologists independently reviewed all available medical records of the index hospital stay. Disagreement in final diagnosis was resolved by consensus involving a third cardiologist Additionally, MR-proANP (cut-off ≥120 pmol/L), C-terminal pro-endothelin-1 (CT-proET-1) and mid-region pro-adrenomedullin (MR-proADM) were analyzed in a blinded fashion during a secondary laboratory assessment. Patients were followed for up to 1 year after initial evaluation for the primary end point of cardiovascular related mortality. An algorithm for early diagnosis of HF was developed using classification and regression tree analysis. Optimal cut-offs were obtained by including the variables MR-proANP, CT-proET-1, MR-proADM, ischemic ECG features, and left ventricular ejection fraction ≤50%. Results: Among 302 patients, 161 (53%) patients had HF. The median MR-proANP values was 277 pmol/L (IQR 166-471) and the optimal cut-off for MR-proANP was estimated at ≥266 pmol/L. An algorithm using optimal MR-proANP and CT-proET-1 cut-offs correctly classified HF in 84% and incorrectly classified HF in 16%. When CT-proET-1 was added to MR-proANP, the net reclassification improvement for diagnosis was estimated at 0.0259 and was significant (p=0.0034). Cumulative 1-year survival was 84% or 99% in patients classified as having HF or not, respectively. Conclusions: MR-proANP values and the optimal cut-off for diagnosis of HF seem to be age dependent. An algorithm incorporating MR-proANP and CT-proET-1 was useful for early diagnosis of HF in older patients with increased 1-year mortality.