Do the Current Guidelines for Heart Failure Diagnosis and Treatment Fit with Clinical Complexity?

Heart failure (HF) is a clinical syndrome defined by specific symptoms and signs due to structural and/or functional heart abnormalities, which lead to inadequate cardiac output and/or increased intraventricular filling pressure. Importantly, HF becomes progressively a multisystemic disease. However, in August 2021, the European Society of Cardiology published the new Guidelines for the diagnosis and treatment of acute and chronic HF, according to which the left ventricular ejection fraction (LVEF) continues to represent the pivotal parameter for HF patients’ evaluation, risk stratification and therapeutic management despite its limitations are well known. Indeed, HF has a complex pathophysiology because it first involves the heart, progressively becoming a multisystemic disease, leading to multiorgan failure and death. In these terms, HF is comparable to cancer. As for cancer, surviving, morbidity and hospitalisation are related not only to the primary neoplastic mass but mainly to the metastatic involvement. In HF, multiorgan involvement has a great impact on prognosis, and multiorgan protective therapies are equally important as conventional cardioprotective therapies. In the light of these considerations, a revision of the HF concept is needed, starting from its definition up to its therapy, to overcome the old and simplistic HF perspective

Chaotic Signatures of Heart Rate Variability and Its Power Spectrum in Health, Aging and Heart Failure

A paradox regarding the classic power spectral analysis of heart rate variability (HRV) is whether the characteristic high- (HF) and low-frequency (LF) spectral peaks represent stochastic or chaotic phenomena. Resolution of this fundamental issue is key to unraveling the mechanisms of HRV, which is critical to its proper use as a noninvasive marker for cardiac mortality risk assessment and stratification in congestive heart failure (CHF) and other cardiac dysfunctions. However, conventional techniques of nonlinear time series analysis generally lack sufficient sensitivity, specificity and robustness to discriminate chaos from random noise, much less quantify the chaos level. Here, we apply a ‘litmus test’ for heartbeat chaos based on a novel noise titration assay which affords a robust, specific, time-resolved and quantitative measure of the relative chaos level. Noise titration of running short-segment Holter tachograms from healthy subjects revealed circadian-dependent (or sleep/wake-dependent) heartbeat chaos that was linked to the HF component (respiratory sinus arrhythmia). The relative ‘HF chaos’ levels were similar in young and elderly subjects despite proportional age-related decreases in HF and LF power. In contrast, the near-regular heartbeat in CHF patients was primarily nonchaotic except punctuated by undetected ectopic beats and other abnormal beats, causing transient chaos. Such profound circadian-, age- and CHF-dependent changes in the chaotic and spectral characteristics of HRV were accompanied by little changes in approximate entropy, a measure of signal irregularity. The salient chaotic signatures of HRV in these subject groups reveal distinct autonomic, cardiac, respiratory and circadian/sleep-wake mechanisms that distinguish health and aging from CHF

Virtual Patients and Sensitivity Analysis of the Guyton Model of Blood Pressure Regulation: Towards Individualized Models of Whole-Body Physiology

Mathematical models that integrate multi-scale physiological data can offer insight into physiological and pathophysiological function, and may eventually assist in individualized predictive medicine. We present a methodology for performing systematic analyses of multi-parameter interactions in such complex, multi-scale models. Human physiology models are often based on or inspired by Arthur Guyton's whole-body circulatory regulation model. Despite the significance of this model, it has not been the subject of a systematic and comprehensive sensitivity study. Therefore, we use this model as a case study for our methodology. Our analysis of the Guyton model reveals how the multitude of model parameters combine to affect the model dynamics, and how interesting combinations of parameters may be identified. It also includes a “virtual population” from which “virtual individuals” can be chosen, on the basis of exhibiting conditions similar to those of a real-world patient. This lays the groundwork for using the Guyton model for in silico exploration of pathophysiological states and treatment strategies. The results presented here illustrate several potential uses for the entire dataset of sensitivity results and the “virtual individuals” that we have generated, which are included in the supplementary material. More generally, the presented methodology is applicable to modern, more complex multi-scale physiological models

Comparison between passive drag and drag during leg kicking of the crawl stroke in top level swimmers.

A body moving through water encounters a resistance called drag. Sixteen crawl swimmers (ten females and six males) and 11 breaststrokers (seven females and four males) were subjected to measurements of the force resisting towing in the prone position (Ft). Towing was performed in a 25-m swimming pool with a new device (Ben Hur, APLab, Rome) that measures Ft at a predetermined constant speed. Each crawl swimmer performed: I) six passive tows at constant speed (from 1.2 to 2.2 ms-1) in order to assess Ft1, which corresponds to passive drag; II) four tows at constant speed (from 1.6 to 2.2 ms-1) during leg kicking of the crawl stroke performed at maximum intensity for 8-12 s in order to assess Ft2. In breaststrokers, Ft1 was measured at the water surface and at a depth of 0.5 m. In eight swimmers (five females and three males), Ft1 was measured at the water surface twice to evaluate the reliability of the Ben Hur device. Ft1 was significantly higher in males than in females (p Ft1). We conclude that Ben Hur is a simple and effective measurement device for the evaluation of the individual passive drag in a common swimming pool. The effect of leg kicking on drag is very different among swimmers of the same technical level, especially in females. The individual comparison between Ft2 and Ft1 provides information about the effectiveness of leg kicking at race speed