What Is the Current Best Drug Treatment for Hypertensive Heart Failure With Preserved Ejection Fraction? Review of the Totality of Evidence

Heart failure management with β-blockers: can we do better?

Heart failure (HF) is associated with disabling symptoms, poor quality of life, and a poor prognosis with substantial excess mortality in the years following diagnosis. Overactivation of the sympathetic nervous system is a key feature of the pathophysiology of HF and is an important driver of the process of adverse remodelling of the left ventricular wall that contributes to cardiac failure. Drugs which suppress the activity of the renin-angiotensin-aldosterone system, including β-blockers, are foundation therapies for the management of heart failure with reduced ejection fraction (HFrEF) and despite a lack of specific outcomes trials, are also widely used by cardiologist in patients with HF with preserved ejection fraction (HFpEF). Today, expert opinion has moved away from recommending that treatment for HF should be guided solely by the LVEF and interventions should rather address signs and symptoms of HF (e.g. oedema and tachycardia), the severity of HF, and concomitant conditions. β-blockers improve HF symptoms and functional status in HF and these agents have demonstrated improved survival, as well as a reduced risk of other important clinical outcomes such as hospitalisation for heart failure, in randomised, placebo-controlled outcomes trials. In HFpEF, β-blockers are anti-ischemic and lower blood pressure and heart rate. Moreover, β-blockers also reduce mortality in the setting of HF occurring alongside common comorbid conditions, such as diabetes, CKD (of any severity), and COPD. Higher doses of β-blockers are associated with better clinical outcomes in populations with HF, so that ensuring adequate titration of therapy to their maximal (or maximally tolerated) doses is important for ensuring optimal outcomes for people with HF. In principle, a patient with HF could have combined treatment with a β-blocker, renin-angiotensin-aldosterone system inhibitor/neprilysin inhibitor, mineralocorticoid receptor antagonist, and a SGLT2 inhibitor, according to tolerability.

β-blockers are not all the same: pharmacologic similarities and differences, potential combinations and clinical implications

β-blockers are a heterogeneous class, with individual agents distinguished by selectivity for β1- vs. β2- and α-adrenoceptors, presence or absence of partial agonist activity at one of more β-receptor subtype, presence or absence of additional vasodilatory properties, and lipophilicity, which determines the ease of entry the drug into the central nervous system. Cardioselectivity (β1-adrenoceptor selectivity) helps to reduce the potential for adverse effects mediated by blockade of β2-adrenoceptors outside the myocardium, such as cold extremities, erectile dysfunction, or exacerbation of asthma or chronic obstructive pulmonary disease. According to recently updated guidelines from the European Society of Hypertension, β-blockers are included within the five major drug classes recommended as the basis of antihypertensive treatment strategies. Adding a β-blocker to another agent with a complementary mechanism may provide a rational antihypertensive combination that minimizes the adverse impact of induced sympathetic overactivity for optimal blood pressure-lowering efficacy and clinical outcomes benefit.

Artificial Intelligence in Heart Failure: Friend or Foe?

In recent times, there have been notable changes in cardiovascular medicine, propelled by the swift advancements in artificial intelligence (AI). The present work provides an overview of the current applications and challenges of AI in the field of heart failure. It emphasizes the "garbage in, garbage out" issue, where AI systems can produce inaccurate results with skewed data. The discussion covers issues in heart failure diagnostic algorithms, particularly discrepancies between existing models. Concerns about the reliance on the left ventricular ejection fraction (LVEF) for classification and treatment are highlighted, showcasing differences in current scientific perceptions. This review also delves into challenges in implementing AI, including variable considerations and biases in training data. It underscores the limitations of current AI models in real-world scenarios and the difficulty in interpreting their predictions, contributing to limited physician trust in AI-based models. The overarching suggestion is that AI can be a valuable tool in clinicians' hands for treating heart failure patients, as far as existing medical inaccuracies have been addressed before integrating AI into these frameworks.

The Sympathetic Nervous System in Hypertensive Heart Failure with Preserved LVEF

The neurohormonal model of heart failure (HF) pathogenesis states that a reduction in cardiac output caused by cardiac injury results in sympathetic nervous system (SNS) activation, that is adaptive in the short-term and maladaptive in the long-term. This model has proved extremely valid and has been applied in HF with a reduced left ventricular (LV) ejection fraction (LVEF). In contrast, it has been undermined in HF with preserved LVEF (HFpEF), which is due to hypertension (HTN) in the vast majority of the cases. Erroneously, HTN, which is the leading cause of cardiovascular disease and premature death worldwide and is present in more than 90% of HF patients, is tightly linked with SNS overactivity. In this paper we provide a contemporary overview of the contribution of SNS overactivity to the development and progression of hypertensive HF (HHF) as well as the clinical implications resulting from therapeutic interventions modifying SNS activity. Throughout the manuscript the terms HHF with preserved LVEF and HfpEF will be used interchangeably, considering that the findings in most HFpEF studies are driven by HTN.