Noncardiac comorbidity clustering in heart failure: an overlooked aspect with potential therapeutic door

The role and application of current pharmacological management in patients with advanced heart failure

In the last decades, several classifications and definitions have been proposed for advanced heart failure (ADVHF) patients, including clinical, functional, hemodynamic, imaging, and electrocardiographic features. Despite different inclusion criteria, ADVHF is characterized by some common items, such as drug intolerance, low arterial pressure, multiple organ dysfunction, chronic kidney disease, and diuretic use dependency. Additional features include fatigue, hypotension, hyponatremia, and unintentional weight loss associated with a specific laboratory profile reflecting systemic multiorgan dysfunction. Notably, studies evaluating guideline-directed medical therapy recently endorsed by guidelines in stable HF, including the 4 drug classes all together (i.e., betablocker, mineral corticoid antagonist, renin angiotensin inhibitors/neprilysin inhibitors, and sodium glucose transporter inhibitors), remain scarcely analyzed in ADVHF and New York Heart Association (NYHA) Class IV. Additionally, due to the common conditions associated with advanced stages, the balance between drug tolerance and potential benefits of the contemporary use of all agents is questioned. Therefore, less hard endpoints, such as exercise tolerance, quality of life (QoL) and self-competency, are not clearly demonstrated. Specific analyses evaluating outcome and rehospitalization of each drug provided conflicting results and are often limited to subjects with stable conditions and less advanced NYHA class. Current European Society of Cardiology/American Heart Association (ESC/AHA) Guidelines do not indicate the type of treatment, dosage, and administration modalities, and they do not suggest specific indications for ADVHF patients. Due to these concerns, there is an impelling need to understand what drugs may be used as the first line, what management leads to the better outcome, and what is the best treatment algorithm in this setting. In this paper, we summarize the most common pitfalls and limitations for the use of the traditional agents, and we propose a personalized approach aiming at preserve drug tolerance and maintaining adverse event protection and satisfactory QoL.

Risk Factors and Cellular Differences in Heart Failure: The Key Role of Sex Hormones

Patients with heart failure are conventionally stratified into phenotypic groups based on their ejection fraction. The aim of this stratification is to improve disease management with a more targeted therapeutic approach. A further subdivision based on patient gender is justified. It is recognized that women are underrepresented in randomized controlled clinical trials, resulting in limited clinical and molecular differentiation between males and females. However, many observational studies show that the onset, development, and clinical course of the disease may substantially differ between the two sexes. According to the emerging concept of precision medicine, investigators should further explore the mechanisms responsible for the onset of heart failure due to sex differences. Indeed, the synergistic or opposing effects of sex hormones on the cardiovascular system and underlying heart failure mechanisms have not yet been clarified. Sex hormones, risk factors impact, and cardiovascular adaptations may be relevant for a better understanding of the intrinsic pathophysiological mechanisms in the two sexes. Despite the differences, treatment for HF is similar across the whole population, regardless of sex and gender. In our review, we describe the main differences in terms of cardiovascular dysfunction, risk factors, and cellular signaling modifications related to the hormonal pattern.

Development and validation of dynamic nomogram of frailty risk for older patients hospitalized with heart failure

Objective

This study aimed to establish and validate a dynamic online nomograph for predicting the risk of frailty in older patients hospitalized with heart failure in China.

Methods

A total of 451 older adults with heart failure hospitalized were selected between December 2021 and November 2022 at the Department of Cardiovascular Medicine in a Class A tertiary hospital in Shandong, China. The data of patients were obtained by using Barthel Index, instrumental activity of daily living scale, mini nutrition assessment-short form, Pittsburgh sleep quality index scale, Morse fall risk assessment scale and general information scale. The brain natriuretic peptide and echocardiographic indexes of patients were collected by electronic medical records. All participants were randomly divided into the training set (n = 319) and the validation set (n = 132) at the ratio of 7:3. The training set is used for model construction, and the validation set is used for internal validation. Using the Least Absolute Shrinkage and Selection Operator (LASSO) regression method to filter modeling variables, while the multivariable logistic regression was used to establish the nomogram based on the screened optimal variables. The performance of the model was evaluated by the area under the curve (AUC) of the receiver operator characteristic (ROC) curve, Hosmer-Lemeshow test, calibration plot, and decision curve analysis (DCA).

Results

The prevalence of frailty in 451 patients was 50.6%, 51.4%, and 48.5% in the training and validation sets, respectively. Drinking, grip strength, New York Heart Association (NYHA) class, multimorbidity, hospitalization history of heart failure, Barthel Index, the instrumental activities of daily living, nutritional status, sleep, fall, and left atrial end-diastolic diameter were used for LASSO regression analysis as the significant predictors of frailty. According to internal validation, the AUC of the ROC curve for the nomogram was 0.920, with a sensitivity of 86.8% and specificity of 84.4%. Moreover, in the validation set, the P-values of the H-L test were 0.742, and the calibration curve had good concordance between the estimated frailty risk and actual observation, indicating the model was well-calibrated. The DCA results confirmed that the nomogram had a well-performance in clinical suitability.

Conclusions

An online dynamic nomogram predicting frailty for older patients hospitalized for heart failure in China was well-established and identified in this study. This model benefits medical professionals in identifying high-risk frailty in older hospitalized patients with heart failure, which could reduce the medical and disease burden of heart failure to a certain extent. However, further verification is needed in the future.

Loss of perceived social role, an index of social frailty, is an independent predictor of future adverse events in hospitalized patients with heart failure

Aims

Although the impact of physical frailty on prognosis and the effect of cardiac rehabilitation in HF patients has been well established, data for the prognostic impact of social frailty (SF) in HF patients are limited. In addition, the relative importance of each SF domain in clinical outcomes remains unclear. We aimed to get a new insight into the associations of SF with clinical outcomes in elderly hospitalized HF patients.

Methods

A single-center, retrospective cohort study was conducted using data from 310 in-hospital HF patients aged ≥ 65 years (mean age of 78 ± 8 years; 49% women). Makizako's five questions, a self-reported questionnaire, were used to define SF. The primary outcome was composite events defined by all-cause death and cardiovascular events.

Results

Of the 310 elderly HF patients, 188 patients (61%) had SF. Seventy-five patients (24%) had composite events during a mean follow-up period of 1.93 ± 0.91 years. Kaplan-Meier curves showed that patients with SF had a significantly higher composite event rate than patients without SF. In multivariate Cox regression analyses, SF was independently associated with a higher composite event rate after adjusting for prognostic markers [adjusted hazard ratio (HR), 2.01; 95% confidence interval (CI), 1.07-3.78; p = 0.04]. Of the 5 questions for defining SF, an answer of yes to the question about not feeling helpful toward friends or family, which indicates loss of perceived social role, was an independent predictor of composite events (adjusted HR, 2.28; 95% CI, 1.36-3.82; p < 0.01). Inclusion of loss of perceived social role into the baseline prognostic model improved both the continuous net reclassification improvement (0.562; 95% CI, 0.298-0.827; p < 0.01) and integrated discrimination improvement (0.031; 95% CI, 0.006-0.056; p = 0.02).

Conclusion

Loss of perceived social role is associated with increased adverse event risk and provides additive prognostic information in elderly HF patients.

Clinical Support through Telemedicine in Heart Failure Outpatients during the COVID-19 Pandemic Period: Results of a 12-Months Follow Up

Background: Heart failure (HF) patients are predisposed to recurrences and disease destabilizations, especially during the COVID-19 outbreak period. In this scenario, telemedicine could be a proper way to ensure continuous care. The purpose of the study was to compare two modalities of HF outpatients’ follow up, the traditional in-person visits and telephone consultations, during the COVID-19 pandemic period in Italy. Methods: We conducted an observational study on consecutive HF outpatients. The follow up period was 12 months, starting from the beginning of the COVID-19 Italy lockdown. According to the follow up modality, and after the propensity matching score, patients were divided into two groups: those in G1 (n = 92) were managed with traditional in-person visits and those in G2 (n = 92) were managed with telephone consultation. Major adverse cardiovascular events (MACE) were the primary endpoints. Secondary endpoints were overall mortality, cardiovascular death, cardiovascular hospitalization, and hospitalization due to HF. Results: No significant differences between G1 and G2 have been observed regarding MACE (p = 0.65), cardiovascular death (p = 0.39), overall mortality (p = 0.85), hospitalization due to acute HF (p = 0.07), and cardiovascular hospitalization (p = 0.4). Survival analysis performed by the Kaplan–Meier method also did not show significant differences between G1 and G2. Conclusions: Telephone consultations represented a valid option to manage HF outpatients during COVID-19 pandemic, comparable to traditional in-person visits.