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

Background: 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.

Objectives: We hypothesized that ACP would also correlate with clinical outcomes in patients with chronic heart failure (HF).

Design: A retrospective study.

Methods: 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 CO/CO × 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.

Results: A total of 965 individual measurements from 290 eligible patients were used to establish the expected CO-SVR curve model (CO = 53.468 × SVR ). Patients with ACP ⩽ 60% had higher serum NT-proBNP levels ( < 0.001), lower left ventricular ejection fraction ( = 0.001), and required dopamine more frequently ( < 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  < 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  < 0.05).

Conclusion: 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.

Clinical Trial Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT02664818.