Risk Estimates of Imminent Cardiovascular Death and Heart Failure Hospitalization Are Improved Using Serial Natriuretic Peptide Measurements in Patients With Coronary Artery Disease and Type 2 Diabetes

Background Baseline and temporal changes in natriuretic peptide (NP) concentrations have strong prognostic value with regard to long-term cardiovascular risk stratification. To increase the clinical utility of NP sampling for patient management, we wanted to assess the incremental predictive value of 2 serial NP measurements compared with a single measurement and provide absolute risk estimates for cardiovascular death or heart failure hospitalization (HFH) within 6 months based on 2 serial NP measurements. Methods and Results Consecutive NP samples obtained from 5393 patients with a recent coronary event and type 2 diabetes enrolled in the ELIXA (Evaluation of Cardiovascular Outcomes in Patients With Type 2 Diabetes After Acute Coronary Syndrome During Treatment With Lixisenatide) trial were used to construct best logistic regression models with outcome of cardiovascular death or HFH (136 events). Absolute risk estimates of cardiovascular death or HFH within 6 months using either BNP (B-type natriuretic peptide) or NT-proBNP (N-terminal pro-BNP) serial measurements were depicted based on the concentrations of 2 serial NP measurements. During the 6-month follow-up periods, the incidence rate (±95% CIs) of cardiovascular death or HFH for patients was 14.0 (11.8‒16.6) per 1000 patient-years. Risk prediction depended on NP concentrations from both prior and current sampling. NP sampling 6 months apart improved the predictive value and reclassification of patients compared with a single sample (AUROC [Area Under the Receiver Operating Characteristic curve]: BNP, =0.003. NT-proBNP, <0.0001), with a majority of moderate-risk patients (6-month risk between 1% and 10%) being reclassified on the basis of the second NP sample. Conclusions Serial NP measurements improved prediction of imminent cardiovascular death or HFH in patients with coronary artery disease and type 2 diabetes. The absolute risk estimates provided may aid clinicians in decision-making and help patients understand their short-term risk profile.