Borlaug, B

Importance Clinical trials in cardiovascular medicine aim to deliver high-quality evidence with greater efficiency, including smaller sample sizes and shorter timelines. The selection of sensitive and reliable end points is central to this goal. Right ventricular (RV) structure and function play a critical role in many cardiovascular conditions; however, RV-specific parameters remain underused and inconsistently applied in interventional clinical trials. In this article, the current and emerging role of RV-focused imaging and hemodynamic parameters as end points in clinical trials are explored and a comprehensive framework for their development, validation, and broader implementation is proposed. Observations Across multiple disease domains, RV-focused parameters derived from echocardiography, cardiac magnetic resonance imaging, computed tomography, and right-sided heart catheterization demonstrate potential value in assessing the therapeutic effects of new medicines or devices across a wide range of conditions including heart failure, cardiomyopathies, valve diseases, pulmonary hypertension, and congenital heart conditions. However, their use is inconsistent, and feasibility challenges are common, particularly in multicenter clinical trial settings. Key limitations include variability in imaging acquisition, incomplete data capture, lack of standardized protocols, and insufficient validation linking short-term RV changes to long-term clinical outcomes. Emerging tools such as artificial intelligence may improve reproducibility and efficiency, while collaborative, multidisciplinary efforts are essential for advancing end-point development. Conclusions and Relevance RV-specific end points hold substantial promise for enhancing the sensitivity and mechanistic insight of clinical trials but remain inadequately integrated into current practice. Optimal end-point selection requires balancing clinical relevance, analytical validity, and operational feasibility, with consideration of disease-specific pathophysiology and trial design. Standardization of acquisition, validation of clinically meaningful changes, and centralized data analysis are important next steps. Broader adoption of robust RV metrics supported by technological innovation and cross-sector collaboration has the potential to improve trial efficiency, accelerate therapeutic development, and ultimately enhance patient outcomes.

Abstract Background Cardiogenic shock (CS) is characterized by critically low cardiac output and impaired myocardial energy transfer to cardiac work. Left-ventricular (LV) cardiac mechanical efficiency (CE), defined as the fraction of total pressure-volume area (PVA) converted to external work (EW), captures how effectively the LV converts energy into stroke work. Because CE integrates load, chamber volumes, and pump performance into a single physiologic construct, it may directly reflect the energy-work mismatch that characterizes CS. The prognostic value of transthoracic echocardiography (TTE)-derived CE for in-hospital outcomes in CS remains uncertain. Purpose To determine whether TTE-derived CE measured within 24 hours of admission predicts in-hospital mortality in patients with CS, and to compare its discriminatory performance with LV ejection fraction (LVEF). Methods Data from CS patients admitted between 2007 and 2018 were analyzed. First LV end-systolic pressure (LVESP=0.9×systolic blood pressure), stroke volume (SV), and LV end-diastolic pressure (LVEDP, estimated using the Nagueh formula) was estimated. CE was then estimated based on EW (EW=(LVESP×SV)−(SV×LVEDP)), potential energy (PE=0.5×LVESP×LV end-systolic volume) and PVA (EW+PE) as CE=EW/PVA×100. We assessed CE and LVEF by TTE performed within 24 hours of admission. Patients were separated into tertiles of CE: high (>47%), moderate (36% < CE ≤47%), and low (CE ≤36%). The primary endpoint was in-hospital mortality. A key secondary endpoint was cardiac intensive care unit (CICU) mortality. Associations were tested with multivariable logistic regression (pre-specified covariates including LVEF). Results A total of 577 patients were included. Median age was 69 (IQR: 59-78) years, 38% were females and 65% had acute coronary syndrome. CICU mortality was 20% and total in-hospital mortality was 29%. Patients with low CE had a lower LVEF compared with patients with moderate or high CE (21% (IQR:19-24%) vs 31% (IQR: 28-33%) and 45% (39-51%) respectively). Median CE was 40.5% (IQR 31.8–51.0%) and was lower for in-hospital deaths (37.1% vs 42.1%, P<0.001). Patients with lower CE exhibited significantly higher CICU (P=0.003) and in-hospital mortality (P<0.001; Figure 1). Patients with CE in the lowest tertile had significantly increased risk of CICU and in-hospital death (Figure 2) compared with moderate or high CE tertiles. In multivariate analysis, every 1% decrease in CE corresponded to an 10% increased risk of CICU death and an 8% increased risk of in-hospital death. When both CE and LVEF were included in the same multivariate model, both were significant predictors of CICU death, while only CE remained a significant predictor of in-hospital death. Conclusion In patients with CS, TTE-derived CE measured within 24 hours of admission predicts early risk of death, underscoring the prognostic importance of LV energy-work coupling as a marker of disease severity beyond LVEF measurement.Figure 1: Figure 2: