International journal of heart failure最新文献

The prevalence of heart failure (HF) is increasing, necessitating accurate diagnosis and tailored treatment. The accumulation of clinical information from patients with HF generates big data, which poses challenges for traditional analytical methods. To address this, big data approaches and artificial intelligence (AI) have been developed that can effectively predict future observations and outcomes, enabling precise diagnoses and personalized treatments of patients with HF. Machine learning (ML) is a subfield of AI that allows computers to analyze data, find patterns, and make predictions without explicit instructions. ML can be supervised, unsupervised, or semi-supervised. Deep learning is a branch of ML that uses artificial neural networks with multiple layers to find complex patterns. These AI technologies have shown significant potential in various aspects of HF research, including diagnosis, outcome prediction, classification of HF phenotypes, and optimization of treatment strategies. In addition, integrating multiple data sources, such as electrocardiography, electronic health records, and imaging data, can enhance the diagnostic accuracy of AI algorithms. Currently, wearable devices and remote monitoring aided by AI enable the earlier detection of HF and improved patient care. This review focuses on the rationale behind utilizing AI in HF and explores its various applications.

Heart failure (HF) stands as a prevalent chronic ailment, imposing a substantial burden on global healthcare systems due to recurrent hospitalizations, intricate management, persistent symptoms, and polypharmacy challenges. The augmentation of patient safety and treatment efficacy across various care stages, facilitated by a multidisciplinary HF team inclusive of a clinical pharmacist, emerges as paramount. Evidence underscores that the collaborative engagement of a physician and a clinical pharmacist engenders proficient and secure management, forestalling avoidable adversities stemming from drug reactions and prescription inaccuracies. This synergistic approach tailors treatments optimally to individual patients. Post-discharge, the vulnerability of HF patients to re-hospitalization looms large, historically holding sway as the foremost cause of 30-day readmissions. Diverse strategies have been instituted to fortify patient well-being, leading to the formulation of specialized transitional care programs that shepherd patients effectively from hospital to outpatient settings. These initiatives have demonstrably curtailed readmission rates. This review outlines a spectrum of roles assumed by clinical pharmacists within the healthcare cohort, spanning inpatient care, transitional phases, and outpatient services. Moreover, it traverses a compendium of studies spotlighting the affirmative impact instigated by integrating clinical pharmacists into these fields.

Background and objectives: Vitamin D, as a steroid hormone, has multiple effects on human body and its deficiency has been associated with an increased risk of heart failure (HF) and unfavorable outcomes. The present study investigated the prevalence of vitamin D deficiency (VDD) and its relationship with cardiometabolic parameters in patients hospitalized for HF living in the city of Recife (latitude 8° South).

Methods: Analytical cross-sectional study, with men and women aged 40-64 years. The HF group was recruited during hospitalization due to decompensation. A matched control group was recruited from the general endocrine clinics. Vitamin D status was assessed by measuring serum 25-hydroxyvitamin D (25OHD), considering deficiency when 25OHD <20 ng/mL (<50 nmol/L).

Results: A total of 243 patients were evaluated (HF group: 161, control group: 82). Lower serum 25OHD levels were observed in the HF group (25.2±9.4 vs. 30.0±7.7ng/mL; p<0.001), as well as a higher prevalence of VDD (27.3% vs. 9.8%; prevalence ratio, 2.80; 95% confidence interval, 1.38-5.67; p=0.002). In patients with HF, VDD was associated with diabetes mellitus (65.9% vs. 41.0%; p=0.005) and female sex (65.9% vs. 44.4%; p=0.015). In the subgroup with VDD, higher values of hemoglobin A1c (7.9% [6.0-8.9] vs. 6.2% [5.7-7.9]; p=0.006) and dyslipidemia were also observed.

Conclusions: We found higher rates of VDD in patients hospitalized for HF and this was associated with deleterious laboratory metabolic parameters.

Iron deficiency (ID) occurs at high frequency across the spectrum of heart failure (HF), with HF severity and race being potentially important predictors for its development. ID, irrespective of anaemia status, leads to poor outcomes in patients with HF, including exacerbated reduction in exercise capacity, poor quality of life (QoL) and increased risk of HF hospitalisation. As ID has a large public health and economic burden in Asia, and patients hospitalised with acute HF in the Asia Pacific vs. other regions commonly present with more severe clinical symptoms, there is a clear need to identify and treat ID promptly in Asian patients with HF. The biomarkers serum ferritin and transferrin saturation are used for ID diagnosis, and periodic screening is recommended in all patients with HF. The intravenous iron treatments, ferric carboxymaltose (FCM) and ferric derisomaltose, have demonstrated efficacy and tolerability in patients with acute or chronic HF and ID, with FCM shown to be cost-effective (and in some cases cost-saving). Meta-analyses support the likely benefits of intravenous FCM for improving QoL and reducing HF hospitalisation, without reducing mortality risk in patients with HF and ID. Accordingly, European Society of Cardiology guidelines recommend considering intravenous FCM for patients with symptomatic HF with left ventricular ejection fraction ≤50% who were recently hospitalised for HF and have ID. Although analyses of Asian patients with HF and ID are limited, the effects of intravenous iron would be expected to be similar to that in White populations; further clarifying studies may be of interest.

Background and objectives: Takotsubo syndrome (TTS) is a form of reversible cardiomyopathy often preceded by mental or physical stressors and predominantly affects elderly women. Several cardiac and inflammatory biomarkers are involved in the pathogenesis of the disease. We aimed to investigate the correlation of C-reactive protein (CRP) level with left ventricular ejection fraction (LVEF) and clinical outcomes in patients with TTS.

Methods: The study included patients with discharge-diagnosis of Takotsubo through 2017-2022 from the cardiology department. Demographic, laboratory, echocardiographic, and clinical outcomes were retrospectively obtained. We investigated the relation between CRP and LVEF, length of stay (LOS), in-hospital complications, and recurrence.

Results: A total of 86 patients (93% female, mean age 68.8±12.3 years) were included in the study. The median CRP level was 17.4 (interquartile range [IQR], 6.1-40.1) mg/L, and the mean LVEF was 41.5%, (IQR, 38-50%). Complications occurred in 24 (27.9%) of the patients, and the median LOS was 3 (IQR, 3-5) days. The level of CRP was associated with lower LVEF (r=-0.39, p<0.001), longer hospital stay (r=0.25, p=0.021), and recurrence. There was no correlation between CRP and in-hospital complications. In multivariate logistic regression, poor LVEF was associated with TTS recurrence (odds ratio, 1.22; 95% confidence interval, 1.08-1.37; p=0.001). Using linear regression, only CRP was correlated with longer LOS and lower LVEF (p<0.001).

Conclusions: Among patients hospitalized with TTS, CRP level was associated with poor LVEF and prolonged hospital stay but not with in-hospital complications. Poor LVEF was also associated with TTS recurrence.