Afterload-related cardiac performance is a powerful hemodynamic predictor of mortality in patients with chronic heart failure.

Abstract

Afterload-related cardiac performance (ACP), a diagnostic parameter for septic cardiomyopathy, integrates both cardiac performance and vascular effects and could predict prognosis in septic shock. We hypothesized that ACP would also correlate with clinical outcomes in patients with chronic heart failure (HF). A retrospective study. We retrospectively studied consecutive patients with chronic HF who underwent right heart catheterization and established an expected cardiac output-systemic vascular resistance (CO-SVR) curve model in chronic HF for the first time. ACP was calculated as COmeasured/COpredicted × 100%. ACP > 80%, 60% < ACP ⩽ 80%, and ACP ⩽ 60% represented less impaired, mildly impaired, and severely impaired cardiovascular function, respectively. The primary outcome was all-cause mortality, and the secondary outcome was event-free survival. A total of 965 individual measurements from 290 eligible patients were used to establish the expected CO-SVR curve model (COpredicted = 53.468 × SVR -0.799). Patients with ACP ⩽ 60% had higher serum NT-proBNP levels (P < 0.001), lower left ventricular ejection fraction (P = 0.001), and required dopamine more frequently (P < 0.001). Complete follow-up data were available in 263 of 290 patients (90.7%). After multivariate adjustment, ACP remained associated with both primary outcome (hazard ratio (HR) 0.956, 95% confidence interval (CI) 0.927-0.987) and secondary outcome (HR 0.977, 95% CI 0.963-0.992). Patients with ACP ⩽ 60% had the worst prognosis (all P < 0.001). ACP was significantly more discriminating (area under the curve of 0.770) than other conventional hemodynamic parameters in predicting mortality (Delong test, all P < 0.05). ACP is a powerful independent hemodynamic predictor of mortality in patients with chronic HF. ACP and the novel CO-SVR two-dimensional graph could be useful in assessing cardiovascular function and making clinical decisions. URL: https://www.clinicaltrials.gov. Unique identifier: NCT02664818.