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Background: In clinical practice, patient self-monitoring is crucial in achieving therapeutic goals in various diseases. In heart failure (HF), it is particularly important due to the increasing role of urine composition. Therefore, we proposed this study to assess the accuracy of urine chloride (uCl−) assessment via strip test in relation to chloride and sodium (uNa+) measurements in a gold-standard laboratory method. Methods: Urine samples were collected before administering morning medications. Afterwards, they were analyzed concurrently using the strip test and gold-standard laboratory method. Results: The study cohort comprised 66 patients (82% male, mean age 68 ± 12 years), of whom 65% were diagnosed with HF and 35% without HF. Across the entire cohort, a strong correlation was observed between uCl− measured by both methods (r = 0.85; p < 0.001). However, the strip test was found to underestimate uCl− relative to the laboratory measurements (mean difference of 18 mmol/L). Furthermore, strong correlations were observed between the methods among patients with HF and without HF (r = 0.88 vs. r = 0.71, respectively; p < 0.001 for both), where they presented similar relationship patterns. Interestingly, in patients with a low glomerular filtration rate (eGFR ≤ 60 mL/min/1.73 m2), the correlation between both methods was greater compared to those with high eGFR (>60 mL/min/1.73 m2) (r = 0.94 vs. r = 0.76, respectively; p < 0.001 for both). The relationship between uCl− from the strip test and uNa+ from the laboratory measurement was weaker than for uCl−, but it was significant. Conclusions: These findings suggest that point-of-care strip tests for assessing urinary chloride demonstrate high accuracy and potential utility, particularly in patients with reduced eGFR.

Pathomechanisms responsible for recovery from acute myocarditis (MCD) or progression to non-ischemic cardiomyopathy have not been comprehensively investigated. Iron, positioned at the crossroads of inflammation and the energy metabolism of cardiomyocytes, may contribute to the pathophysiology of inflammatory myocardial disease. The aim of this study was to evaluate whether systemic iron parameters are related to myocardial dysfunction in MCD patients. We prospectively enrolled 42 consecutive patients hospitalized for MCD. Their iron status and their clinical, laboratory, and echocardiographic indices were assessed during hospitalization and during ambulatory visits six weeks after discharge. A control group comprising healthy volunteers was recruited. The MCD patients had higher serum ferritin and hepcidin and lower serum iron concentration and transferrin saturation (TSAT) than the healthy controls (all p < 0.01). Six weeks after discharge, the iron status of the MCD patients was already comparable to that of the control group. During hospitalization, lower serum iron and TSAT correlated with higher NT-proBNP (both p < 0.05). In-hospital lower serum iron and TSAT correlated with both a lower left ventricular ejection fraction (LVEF) and worse left ventricular global longitudinal strain at follow-up visits (all p < 0.05). In conclusion, in patients with acute MCD, iron status is altered and normalizes within six weeks. Low serum iron and TSAT are related to greater in-hospital neurohormonal activation and subtle persistent left ventricular dysfunction.

Viral respiratory infections (VRI) are the most prevalent type of infectious diseases and constitute one of the most common causes of contact with medical care. Regarding the pathophysiology of the cardiovascular system, VRI can not only exacerbate already existing chronic cardiovascular disease (such as coronary artery disease or heart failure) but also trigger new adverse events or complications (e.g., venous thromboembolism), the latter particularly in subjects with multimorbidity or disease-related immobilization. In the current paper, we provide a narrative review of diverse cardiovascular complications of VRI as well as summarize available data on the pathology of the circulatory system in the course of coronavirus disease 2019 (COVID-19).

Acute heart failure (AHF) is a common and severe condition with a poor prognosis. Its course is often complicated by worsening renal function (WRF), exacerbating the outcome. The population of AHF patients experiencing WRF is heterogenous, and some novel possibilities for its analysis have recently emerged. Clustering is a machine learning (ML) technique that divides the population into distinct subgroups based on the similarity of cases (patients). Given that, we decided to use clustering to find subgroups inside the AHF population that differ in terms of WRF occurrence. We evaluated data from the three hundred and twelve AHF patients hospitalized in our institution who had creatinine assessed four times during hospitalization. Eighty-six variables evaluated at admission were included in the analysis. The k-medoids algorithm was used for clustering, and the quality of the procedure was judged by the Davies–Bouldin index. Three clinically and prognostically different clusters were distinguished. The groups had significantly (p = 0.004) different incidences of WRF. Inside the AHF population, we successfully discovered that three groups varied in renal prognosis. Our results provide novel insight into the AHF and WRF interplay and can be valuable for future trial construction and more tailored treatment.

Neurohormone activation plays an important role in Acute Heart Failure (AHF) pathophysiology. Serum osmolarity can affect this activation causing vasopressin excretion. The role of serum osmolarity and vasopressin concentration and its interaction remain still unexplored in AHF. The objective of our study was to evaluate the relationship of serum osmolarity with clinical parameters, vasopressin concentration, in-hospital course, and outcomes in AHF patients. The study group consisted of 338 AHF patients (male (76.3%), mean age of 68 ± 13 years) with serum osmolarity calculated by the equation: 1.86 × sodium [mmol/L] + (glucose [mg/dL]/18) + (urea [mg/dL]/2.8) + 9 and divided into osmolarity quartiles marked as: low: 304 mOsm/L. There was an increasing age gradient in the groups and patients differed in the occurrence of comorbidities and baseline clinical and laboratory parameters. Importantly, analysis revealed that vasopressin presented a linear correlation with osmolarity (r = −0.221, p = 0.003) and its concentration decreased with quartiles (61.6 [44.0–81.0] vs. 57.8 [50.0–77.3] vs. 52.7 [43.1–69.2] vs. 45.0 [30.7–60.7] pg/mL, respectively, p = 0.034). This association across quartiles was observed among de novo AHF (63.6 [55.3–94.5] vs. 58.0 [50.7–78.6] vs. 52.0 [46.0–58.0] vs. 38.0 [27.0–57.0] pg/mL, respectively, p = 0.022) and was not statistically significant in patients with acute decompensated heart failure (ADHF) (59.5 [37.4–80.0] vs. 52.0 [38.0–74.5] vs. 57.0 [38.0–79.0] vs. 50.0 [33.0–84.0] pg/mL, respectively, p = 0.849). The worsening of renal function episodes were more frequent in quartiles with higher osmolarity (4 vs. 2 vs. 13 vs. 11%, respectively, p = 0.018) and patients that belonged to the quartiles with low and high osmolarity were characterized more often by incidence of worsening heart failure (20 vs. 9 vs. 10 vs. 22%, respectively, p = 0.032). There was also a U-shape distribution in relation to one-year mortality (31 vs. 19 vs. 23 vs. 37%, respectively, p = 0.022). In conclusion, there was an association of serum osmolarity with clinical status and both in-hospital and out-of-hospital outcomes. Moreover, the linear dependence between vasopressin concentration and serum osmolarity in the AHF population was identified and was driven mainly by patients with de novo AHF which suggests different pathophysiological paths in ADHF and AHF de novo.

Acute heart failure (AHF) is a life-threatening, heterogeneous disease requiring urgent diagnosis and treatment. The clinical severity and medical procedures differ according to a complex interplay between the deterioration cause, underlying cardiac substrate, and comorbidities. This study aimed to analyze the natural phenotypic heterogeneity of the AHF population and evaluate the possibilities offered by clustering (unsupervised machine-learning technique) in a medical data assessment. We evaluated data from 381 AHF patients. Sixty-three clinical and biochemical features were assessed at the admission of the patients and were included in the analysis after the preprocessing. The K-medoids algorithm was implemented to create the clusters, and optimization, based on the Davies-Bouldin index, was used. The clustering was performed while blinded to the outcome. The outcome associations were evaluated using the Kaplan-Meier curves and Cox proportional-hazards regressions. The algorithm distinguished six clusters that differed significantly in 58 variables concerning i.e., etiology, clinical status, comorbidities, laboratory parameters and lifestyle factors. The clusters differed in terms of the one-year mortality (p = 0.002). Using the clustering techniques, we extracted six phenotypes from AHF patients with distinct clinical characteristics and outcomes. Our results can be valuable for future trial constructions and customized treatment.

The perception of acute heart failure (AHF) as a single entity is increasingly outdated, as distinct patient profiles can be discerned. Key heart failure (HF) studies have previously highlighted the difference in both the course and prognosis of de novo AHF and acute decompensated chronic HF (ADHF). Accordingly, distinct AHF profiles with differing underlying pathophysiologies of disease progression can be shown. We compared a range of selected biomarkers in order to better describe the profile of de novo AHF and ADHF, including the inter alia—serum lactate, bilirubin, matrix metallopeptidase 9 (MMP-9), follistatin, intercellular adhesion molecule 1 (ICAM-1), lipocalin and galectin-3. The study comprised 248 AHF patients (de novo = 104), who were followed up for one year. The biomarker data of the de novo AHF and ADHF profiles was then compared in order to link biomarkers to their prognosis. Our study demonstrated that, although there are similarities between each patient profile, key biomarker differences do exist—predominantly in terms of NTproBNP, serum lactate, bilirubin, ICAM-1, follistatin, ferritin and sTfR (soluble transferrin receptor). ADHF tended to have compromised organ function and higher risks of both one-year mortality and composite endpoint (one-year mortality or rehospitalization for heart failure) hazard ratios (HR) (95% CI): 3.4 (1.8–6.3) and 2.8 (1.6–4.6), respectively, both p < 0.0001. Among the biomarkers of interest: sTfR HR (95% CI): 1.4 (1.04–1.8), NGAL(log) (neutrophil gelatinase-associated lipocalin) HR (95% CI): 2.0 (1.3–3.1) and GDF-15(log) (growth/differentiation factor-15) HR (95% CI): 4.0 (1.2–13.0) significantly impacted the one-year survival, all p < 0.05.

Cardiac fibroblasts and cardiomyocytes are the main cells involved in the pathophysiology of myocarditis (MCD). These cells are especially sensitive to changes in iron homeostasis, which is extremely important for the optimal maintenance of crucial cellular processes. However, the exact role of iron status in the pathophysiology of MCD remains unknown. We cultured primary human cardiomyocytes (hCM) and cardiofibroblasts (hCF) with sera from acute MCD patients and healthy controls to mimic the effects of systemic inflammation on these cells. Next, we performed an initial small-scale (n = 3 per group) RNA sequencing experiment to investigate the global cellular response to the exposure on sera. In both cell lines, transcriptomic data analysis revealed many alterations in gene expression, which are related to disturbed canonical pathways and the progression of cardiac diseases. Moreover, hCM exhibited changes in the iron homeostasis pathway. To further investigate these alterations in sera-treated cells, we performed a larger-scale (n = 10 for controls, n = 18 for MCD) follow-up study and evaluated the expression of genes involved in iron metabolism. In both cell lines, we demonstrated an increased expression of transferrin receptor 1 (TFR1) and ferritin in MCD serum-treated cells as compared to controls, suggesting increased iron demand. Furthermore, we related TFR1 expression with the clinical profile of patients and showed that greater iron demand in sera-treated cells was associated with higher inflammation score (interleukin 6 (IL-6), C-reactive protein (CRP)) and advanced neurohormonal activation (NT-proBNP) in patients. Collectively, our data suggest that the malfunctioning of cardiomyocytes and cardiofibroblasts in the course of MCD might be related to alterations in the iron homeostasis.

Long-distance running and, in particular, running marathons has become an increasingly popular activity among the elderly. The aim of the study was to examine the effects of a marathon effort on the psychomotor performance and catecholamine concentration in runners over 50 years of age. The participants were male runners (n = 28) who completed the 32nd Wrocław Marathon in Poland. The runners’ psychomotor performance was assessed on the basis of their choice reaction times (CRT), heart rate (HR) and running speed measurements. In addition, the adrenaline (A) and noradrenaline (NA) as well as lactate (LA) levels and anaerobic threshold (AT) were measured. The runners’ CRT after crossing the finish line was significantly longer by 50 ms (p < 0.05) in response to each emitted audiovisual stimulus, as compared with baseline. The mean running speed was reduced by 1 km/h between the first speed measurement (5th km of the run) and the last (42.195 km) (p < 0.05). The observed three-fold increase in adrenaline and noradrenaline levels indicates an intense activity of the sympathetic−adrenergic system. The cognitive function levels in the studied marathon runners returned to baseline after 30 min of recovery, and the function of the sympathetic−adrenergic system by seven days after completing the marathon race.

(1) Background: Oxidative energy metabolism is presumed to rely on the optimal iron supply. Primary human cardiac myocytes (HCM) exposed to different iron availability conditions during mechanical stretch are anticipated to demonstrate expression changes of genes involved in aerobic and anaerobic metabolic pathways. (2) Methods: HCM were cultured for 48 h either in static conditions and upon mechanical stretch at the optimal versus reduced versus increased iron concentrations. We analyzed the expression of pyruvate kinase (PKM2), lactate dehydrogenase A (LDHA), and mitochondrial complexes I–V at the mRNA and protein levels. The concentration of l-lactate was assessed by means of lactate oxidase method-based kit. (3) Results: Reduced iron concentrations during mechanical work caused a decreased expression of complexes I–V (all p < 0.05). The expression of PKM2 and LDHA, as well as the medium concentration of l-lactate, was increased in these conditions (both p < 0.05). HCM exposed to the increased iron concentration during mechanical effort demonstrated a decreased expression of mitochondrial complexes (all p < 0.01); however, a decrement was smaller than in case of iron chelation (p < 0.05). The iron-enriched medium caused a decrease in expression of LDHA and did not influence the concentration of l-lactate. (4) Conclusions: During mechanical effort, the reduced iron availability enhances anaerobic glycolysis and extracellular lactate production, whilst decreasing mitochondrial aerobic pathway in HCM. Iron enrichment during mechanical effort may be protective in the context of intracellular protein machinery of non-oxidative metabolism with no effect on the extracellular lactate concentration.