Background and Objectives: Hypertrophic cardiomyopathy (HCM) depends on the primary impairment of sarcomeres, but it can also be associated with secondary alterations in the heart related to oxidative stress. The present study aimed to examine oxidative-antioxidant disturbances in patients with HCM compared with control individuals. Materials and Methods: We enrolled 52 consecutive HCM patients and 97 controls without HCM. The groups were matched for age, body mass index, and sex. Peripheral blood was collected from all patients to determine the total antioxidant capacity (TAC), total oxidant status (TOS), lipid hydroperoxide (LPH), and malondialdehyde (MDA). The oxidative stress index (OSI) was defined as the ratio of the TOS level to the TAC level. Results: The median age was 52 years, and 58.4% were female. The area under the curve (AUC) indicated good predictive power for the TAC and TOS [AUC 0.77 (0.69–0.84) and 0.83 (0.76–0.90), respectively], as well as excellent predictive power for the OSI [AUC 0.87 (0.81–0.93)] for HCM detection. Lipid peroxidation markers also demonstrated good predictive power to detect HCM patients [AUC_LPH = 0.73, AUC_MDA = 0.79]. Conclusions: The TOS, the TAC, LPH levels, and MDA levels have good predictive power for HCM detection. The holistic assessment of oxidative stress by the OSI had excellent power and could identify patients with HCM.

Heart failure (HF) is a common condition and one of the main morbidity and mortality factors in elderly patients. The incidence of HF progressively increases with age, reaching >10% in those aged 70 years or over. In the elderly population, both the diagnosis and the management of HF prove challenging, often requiring specialized care and a multidisciplinary approach. In seniors, atypical presentation of HF is much more common than in younger patients; thus, a holistic assessment with biomarkers related to HF allows for early diagnosis and accurate risk stratification in this group of patients. This article reviews the clinical and diagnostic differences in elderly patients with HF, highlighting the presence of comorbidities, frailty, cognitive impairment, and polypharmacy, as well as discussing potential biomarkers that may have clinical application in this population.

Despite the important roles of vascular smooth muscle cells and endothelial cells in atherosclerotic lesion formation, data regarding the associations of functional polymorphisms in the genes encoding growth factors with the severity of coronary artery disease (CAD) are lacking. The aim of the present study is to analyze the relationships between functional polymorphisms in genes encoding basic fibroblast growth factor (bFGF, FGF2), epidermal growth factor (EGF), insulin-like growth factor-1 (IGF-1), platelet derived growth factor-B (PDGFB), transforming growth factor-β1 (TGF-β1) and vascular endothelial growth factor A (VEGF-A) and the severity of coronary atherosclerosis in patients with stable CAD undergoing their first coronary angiography. In total, 319 patients with stable CAD who underwent their first coronary angiography at the Silesian Centre for Heart Diseases in Zabrze, Poland were included in the analysis. CAD burden was assessed using the Gensini score. The TaqMan method was used for genotyping of selected functional polymorphisms in the FGF2, PDGFB, TGFB1, IGF1 and VEGFA genes, while rs4444903 in the EGF gene was genotyped using the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. The associations between the selected polymorphisms and the Gensini were calculated both for the whole cohort and for a subgroup of patients without previous myocardial infarction (MI). There were no differences in the distribution of the Gensini score between the genotypes of the analyzed polymorphisms in FGF2, EGF, IGF1, PDFGB, and TGFB1 in the whole cohort and in the subgroup of patients without previous MI. The Gensini score for VEGFA rs699947 single-nucleotide polymorphism (SNP) in patients without previous myocardial infarction, after correction for multiple testing, was highest in patients with the A/A genotype, lower in heterozygotes and lowest in patients with the C/C genotype, (p value for trend = 0.013, false discovery rate (FDR) = 0.02). After adjustment for clinical variables, and correction for multiple comparisons the association between the VEGFA genotype and Gensini score remained only nominally significant (p = 0.04, FDR = 0.19) under the dominant genetic model in patients without previous MI. We were unable to find strong association between analyzed polymorphisms in growth factors and the severity of coronary artery disease, although there was a trend toward association between rs699947 and the severity of CAD in patients without previous MI.

Background/Objective: Risk stratification in elderly patients with heart failure (HF) is very difficult. There is a lack of reliable tools for assessing the risk of death in this population of patients. The aim of this study was to determine the association between albumin–bilirubin (ALBI) score and long-term mortality in hospitalized elderly patients with decompensated HF. Methods: The study included 242 consecutive HF patients aged over 65 years hospitalized for worsening chronic HF at our institution between 2019 and 2023. The ALBI score was calculated according to the appropriate formula. Results: The median (IQR) age of the study population was 68.00 (range 66.0 to 74.6) years and 21.1% were female. The mean follow-up time was 352 ± 293 days. During the follow-up period, 47.1% patients died. The ALBI score generated good prognostic power (area under the curve = 0.822, p < 0.01) and specificity (86%) as well as acceptable sensitivity (68%) when predicting long-term mortality. Patients with higher ALBI scores (≥−2.191) had significantly worse long-term survival than patients with lower ALBI scores (<−2.191) [37 (25.2%) vs. 77 (81.1%); log rank p < 0.001]. Conclusions: This is the first study demonstrating that ALBI score has good prognostic power and allows for the successful prediction of mortality during long-term follow-up in the analyzed cohort.