Energetic phenotyping in heart failure: From Starling curves to composite variables

Despite advances in treatment, mortality rates for advanced heart failure and cardiogenic shock remain unchanged due to delays in identifying shock types and challenges in choosing the right therapy. Accurate patient phenotyping can help clarify the patient's condition and guide better treatment. In this study, we used in silico modeling to investigate the dynamic relationships among power, efficiency, and the shock phenotype in six advanced heart failure hypothetical phenotypes and a healthy control. We simulated phenotype-specific Starling curves by changing volume loading. We calculated advanced hemodynamic and energetic variables-pulsatility index, power output, myocardial performance score, and efficiency for the left and right ventricles. We proposed composite cardiac indices for energetic phenotyping. Adding a dynamic energetic assessment with volume loading showed that cardiac efficiency limits cardiac performance in each heart failure phenotype, but not in healthy controls. Advanced hemodynamic and energetic phenotyping-both at rest and during volume loading-especially with biventricular assessment, can accurately distinguish clinical shock phenotypes. This approach offers mechanistic insight into the causes of cardiac underperformance and helps guide optimal therapeutic interventions.