Cardiovascular Death Risk in Recovered Mid-Range Ejection Fraction Heart Failure: Insights From Cardiopulmonary Exercise Test

What about chronotropic incompetence in heart failure with mildly reduced ejection fraction? Clinical and prognostic implications from the Metabolic Exercise combined with Cardiac and Kidney Indexes score dataset

AIMS

Chronotropic incompetence (CI) is a strong predictor of outcome in heart failure with reduced ejection fraction, however no data on its clinical and prognostic impacts in heart failure with mildly reduced ejection fraction (HFmrEF) are available. Therefore, the study aims to investigate, in a large multicentre HFmrEF cohort, the prevalence of CI as well as its relationship with exercise capacity and its prognostic role over the cardiopulmonary exercise testing (CPET) parameters.

METHODS AND RESULTS

Within the Metabolic Exercise combined with Cardiac and Kidney Indexes (MECKI) database, we analysed data of 864 HFmrEF out of 1164 stable outpatients who performed a maximal CPET at the cycle ergometer and who had no significant rhythm disorders or comorbidities. The primary study endpoint was cardiovascular (CV) death. All-cause death was also explored. Chronotropic incompetence prevalence differed depending on the method (peak heart rate, pHR% vs. pHR reserve, pHRR%) and the cut-off adopted (pHR% from ≤75% to ≤60% and pHRR% ≤ 65% to ≤50%), ranging from 11% to 62%. A total of 84 (9.7%) CV deaths were collected, with 39 (4.5%) occurring within 5 years. At multivariate analysis, both pHR% [hazard ratio 0.97 (0.95-0.99), P < 0.05] and pHRR% [hazard ratio 0.977 (0.961-0.993), P < 0.01] were associated with the primary endpoint. A pHR% ≤ 75% and a pHRR% ≤ 50% represented the most accurate cut-off values in predicting the outcome.

CONCLUSION

The study suggests an association between blunted exercise-HR response, functional capacity, and CV death risk among patients with HFmrEF. Whether the CI presence might be adopted in daily HFmrEF management needs to be addressed in larger prospective studies.

The role of smart devices and mobile application on the change in peak VO2 in patients with high cardiovascular risk: a sub-study of the LIGHT randomised clinical trial

BACKGROUND

This investigation aims to assess the influence of a mobile application and smart devices on cardiopulmonary exercise testing (CPET) over a one-year period in individuals who have high risk for cardiovascular disease.

METHODS

This is a post-hoc subgroup analysis of Lifestyle Intervention Using Mobile Technology in Patients with High Cardiovascular Risk: A Pragmatic Randomised Clinical Trial (LIGHT). In the intervention plus standard care standard standard care arms, 138 and 103 patients were recruited, respectively. The 1-year VO2 measurements were adjusted to the baseline VO2 measurements as the study's endpoint. VO2 measurements were taken for each subject during the randomisation and final CPET examinations.

RESULTS

The intervention plus standard care improved VO2 measurements by 1.1 (adjusted treatment effect 1.1, 95% confidence interval (CI): 0.8, 1.4, p < 0.001) compared to standard care following 1-year follow-up.

CONCLUSION

At a 1-year follow-up, the smart device and mobile application technologies increased VO2 measurements in individuals with high cardiovascular risk compared to conventional treatment alone.

Heart failure classifications via non-invasive pressure volume loops from echocardiography

BACKGROUND

Left ventricular pressure-volume (LV-PV) loops provide comprehensive characterization of cardiovascular system in both health and disease, which are the essential element of the hemodynamic evaluation of heart failure (HF). This study attempts to achieve more detailed HF classifications by non-invasive LV-PV loops from echocardiography and analyzes contribution of parameters to HF classifications.

METHODS

Firstly, non-invasive PV loops are established by time-varying elastance model where LV volume curves were extracted from apical-four-chambers view of echocardiographic videos. Then, 16 parameters related to cardiac structure and functions are automatically acquired from PV loops. Next, we applied six machine learning (ML) methods to divide four categories. On this premise, we choose the best performing classifier among machine learning approaches for feature ranking. Finally, we compare the contributions of different parameters to HF classifications.

RESULTS

By the experimental, the PV loops were successfully acquired in 1076 cases. When single left ventricular ejection fraction (LVEF) is used for HF classifications, the accuracy of the model is 91.67%. When added parameters extracted from ML-derived LV-PV loops, the classification accuracy is 96.57%, which improved by 5.1%. Especially, our parameters have a great improvement in the classification of non-HF controls and heart failure with preserved ejection fraction (HFpEF).

CONCLUSIONS

We successfully presented the classification of HF by machine derived non-invasive LV-PV loops, which has the potential to improve the diagnosis and management of heart failure in clinic. Moreover, ventriculo-arterial (VA) coupling and ventricular efficiency were demonstrated important factors for ML-based HF classification model besides LVEF.

Heart failure with preserved ejection fraction: key stumbling blocks for experimental drugs in clinical trials

INTRODUCTION

Heart failure with preserved ejection fraction (HFpEF) is a disease process with a high prevalence. Accounting for more than 50% of all heart failure cases, it carries a significant mortality. So far, there has been a lack of therapeutic options that truly show improvement in morbidity and mortality. Certain novel therapies have shown a decrease in heart failure hospitalizations, however, this beneficial effect was more pronounced for heart failure patients with mildly reduced ejection fraction (EF).

AREAS COVERED

This review summarizes the pathophysiology of the disease to help elucidate the differences between heart failure with reduced ejection fraction (HFrEF), and HFpEF, which could explain why therapies are successful in one (rather than the other). At the focus of this review are non-standardized nomenclature across major trials, the challenges of finding a therapeutic agent for such a heterogeneous population, and identification of specific phenotypes that have different outcomes and could be a target for future therapies.

EXPERT OPINION

Lack of standardized diagnostic criteria, associated with population heterogeneity, might explain why trials have failed to improve outcomes for patients with HFpEF. Standardizing phenotypes and recapitulating these phenotypes in animal models, as well as understanding the mechanisms of the disease at the molecular level could be the first steps in identifying promising therapeutic options.

Risk stratification in heart failure with mild reduced ejection fraction

Heart failure with mid-range ejection fraction represents a heterogeneous and relatively young heart failure category accounting for nearly 20-30% of the overall heart failure population. Due to its complex phenotype, a reliable clinical picture of heart failure with mid-range ejection fraction patients as well as a definite risk stratification are still relevant unsolved issues. In such a context, there is growing interest in a comprehensive functional assessment by means of a cardiopulmonary exercise test, yet considered a cornerstone in the clinical management of patients with heart failure and reduced ejection fraction. Indeed, the cardiopulmonary exercise test has also been found to be particularly useful in the heart failure with mid-range ejection fraction category, several cardiopulmonary exercise test-derived parameters being associated with a poor outcome. In particular, a recent contribution by the metabolic exercise combined with cardiac and kidney indexes research group showed an independent association between the peak oxygen uptake and pure cardiovascular mortality in a large cohort of recovered heart failure with mid-range ejection fraction patients. Contextually, the same study supplied an easy approach to identify a high-risk heart failure with mid-range ejection fraction subset by using a combination of peak oxygen uptake and ventilatory efficiency cut-off values, namely 55% of the maximum predicted and 31, respectively. Thus, looking at the above-mentioned promising results and waiting for specific trials, it is reasonable to consider cardiopulmonary exercise test assessment as part of the heart failure with mid-range ejection fraction work-up in order to identify those patients with an unfavourable functional profile who probably deserve a close clinical follow-up and, probably, more aggressive therapeutic strategies.

Future developments in the MECKI score initiative

The Metabolic Exercise combined with Cardiac and Kidney Indexes [MECKI) score is a validated prognostic score for heart failure with reduced ejection fraction which combines commonly available clinical and metabolic parameters with two cardiopulmonary exercise test derived prognostic measurements. It has been validated to predict prognosis and to aid clinical decision making and it has been shown to be superior in predicting mortality compared with other commonly used prognostic scores for heart failure. In the future it would be valuable to establish whether the score holds true also in other settings, and in particular in under-represented groups – the elderly, women, and people of different ethnic backgrounds – and in other heart failure syndromes. In future it may be extended to assess its value in the presence of a range of co-morbidities such as chronic obstructive pulmonary disease, pulmonary hypertension and frailty and cachexia as well as in other conditions such as hypertrophic cardiomyopathy, amyloid, asymptomatic left ventricular dysfunction and hypertension. It may also be a candidate end-point for adaptive trials designed to prove an improvement in the MECKI score as an approvable interim end-point whilst larger mortality and morbidity trials are still underway.