Sex-stratified patterns of emergency cardiovascular admissions prior and during the COVID-19 pandemic.

The COVID-19 pandemic has had a significant impact on global public health, with long-term consequences that are still largely unknown. This study aimed to assess the data regarding acute cardiovascular hospital admissions in five European centers before and during the pandemic. A multicenter, multinational observational registry was created, comparing admissions to the emergency departments during a 3-months period in 2020 (during the pandemic) with the corresponding period in 2019 (pre-pandemic). Data on patient demographics, COVID-19 test results, primary diagnosis, comorbidities, heart failure profile, medication use, and laboratory results were collected. A total of 8778 patients were included in the analysis, with 4447 patients in 2019 and 4331 patients in 2020. The results showed significant differences in the distribution of cardiovascular diseases between the two years. The frequency of pulmonary embolism (PE) increased in 2020 compared to 2019, while acute heart failure (AHF) and other cardiovascular diseases decreased. The odds of PE incidence among hospitalized patients in 2020 were 1.316-fold greater than in 2019. The incidence of AHF was 50.83% less likely to be observed in 2020, and the odds for other cardiovascular diseases increased by 17.42% between the 2 years. Regarding acute coronary syndrome (ACS), the distribution of its types differed between 2019 and 2020, with an increase in the odds of ST-segment elevation myocardial infarction (STEMI) in 2020. Stratification based on sex revealed further insights. Among men, the incidence of AHF decreased in 2020, while other cardiovascular diseases increased. In women, only the incidence of STEMI showed a significant increase. When analyzing the influence of SARS-CoV-2 infection, COVID-positive patients had a higher incidence of PE compared to COVID-negative patients. COVID-positive patients with ACS also exhibited symptoms of heart failure more frequently than COVID-negative patients. These findings provide valuable information on the impact of the COVID-19 pandemic on acute cardiovascular hospital admissions. The increased incidence of PE and changes in the distribution of other cardiovascular diseases highlight the importance of monitoring and managing cardiovascular health during and post pandemic period. The differences observed between sexes emphasize the need for further research to understand potential sex-specific effects of COVID-19 on cardiovascular outcomes.

The Malaprade reaction mechanism for ethylene glycol oxidation by periodic acid based on density functional theory (DFT).

A general mechanism of the Malaprade oxidative carbon-carbon bond cleavage reaction of α-glycol in the presence of periodic acid has been proposed on the basis of density functional theory (DFT) computations. Ethylene glycol and periodic acid, both in their neutral forms, have been studied as noble substrate representatives in model reactions. The proposed reaction mechanism has been constructed based on and compared with previously published experimental kinetic, spectroscopic and temperature and pH-dependent studies. In the presented theoretical mechanistic considerations, four alternative molecular transformations have been analyzed from thermodynamic and kinetic points of view. Theoretically, the predicted activation energy barriers have been compared with experimental ones published elsewhere. The presented minimum energy pathway (MEP) unveiled the shape and conformation of the intermediate and transition state structures. The three-step reaction process involves the formation of a seven-membered quasi-ring assisted by an intramolecular hydrogen-bond intermediate structure forming one I-O bond (IC1_B), a cyclic ester intermediate forming two I-O bonds (IC2_C) and the final products formed at the two very last stages (HIO3, water and two formaldehyde molecules). The computed and energetically the most favourable reaction landscape proposed in this work uniforms and refines the mechanistic proposition given by Criegee for Malaprade type of reactions and further gives a detailed molecular understanding of the reaction rate and atomic connections en route the transformation. The molecular geometries of all stationary points (intermediate and transition state structures) lying on the potential energy hypersurface have been optimized at the four alternative DFT levels under the solvation model based on the density approximation: B3PW91, CAM-B3LYP, BMK, ωB97XD. The 6-311+G(2d,p) basis set for C, O, and H atoms and both the full (DGDZVP) and Ahlrichs-Weigend1 (def2-TZVP) basis sets for iodine atoms were used during the computations.

Role of dietary sodium restriction in chronic heart failure: systematic review and meta-analysis.

BACKGROUND: Dietary sodium restriction remains a guidelines-approved lifestyle recommendation for chronic heart failure (CHF) patients. However, its efficacy in clinical outcome improvement is dubious. OBJECTIVE: The study evaluated whether dietary sodium restriction in CHF reduces clinical events. METHODS: We performed a systematic review of the following databases: Academic Search Ultimate, ERIC, Health Source Nursing/Academic Edition, MEDLINE, Embase, Clinicaltrials.gov and Cochrane Library (trials) to find studies analysing the impact of sodium restriction in the adult CHF population. Both observational and interventional studies were included. Exclusion criteria included i.e.: sodium consumption assessment based only on natriuresis, in-hospital interventions or mixed interventions-e.g. sodium and fluid restriction in one arm only. The review was conducted following PRISMA guidelines. Meta-analysis was performed for the endpoints reported in at least 3 papers. Analyses were conducted in Review Manager (RevMan) Version 5.4.1. RESULTS: Initially, we screened 9175 articles. Backward snowballing revealed 1050 additional articles. Eventually, 9 papers were evaluated in the meta-analysis. All-cause mortality, HF-related hospitalizations and the composite of mortality and hospitalisation were reported in 8, 6 and 3 articles, respectively. Sodium restriction was associated with a higher risk of the composite endpoint (OR 4.12 [95% CI 1.23-13.82]) and did not significantly affect the all-cause mortality (OR 1.38 [95% CI 0.76-2.49]) or HF hospitalisation (OR 1.63 [95% CI 0.69-3.88]). CONCLUSIONS: In a meta-analysis, sodium restriction in CHF patients worsened the prognosis in terms of a composite of mortality and hospitalizations and did not influence all-cause mortality and HF hospitalisation rate.

A Methodological Perspective on the Function and Assessment of Peripheral Chemoreceptors in Heart Failure: A Review of Data from Clinical Trials.

Augmented peripheral chemoreceptor sensitivity (PChS) is a common feature of many sympathetically mediated diseases, among others, and it is an important mechanism of the pathophysiology of heart failure (HF). It is related not only to the greater severity of symptoms, especially to dyspnea and lower exercise tolerance but also to a greater prevalence of complications and poor prognosis. The causes, mechanisms, and impact of the enhanced activity of peripheral chemoreceptors (PChR) in the HF population are subject to intense research. Several methodologies have been established and utilized to assess the PChR function. Each of them presents certain advantages and limitations. Furthermore, numerous factors could influence and modulate the response from PChR in studied subjects. Nevertheless, even with the impressive number of studies conducted in this field, there are still some gaps in knowledge that require further research. We performed a review of all clinical trials in HF human patients, in which the function of PChR was evaluated. This review provides an extensive synthesis of studies evaluating PChR function in the HF human population, including methods used, factors potentially influencing the results, and predictors of increased PChS.

Machine Learning Approach to Understand Worsening Renal Function in Acute Heart Failure.

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.

COVID-19 Related Myocarditis in Adults: A Systematic Review of Case Reports.

Despite the progress of its management, COVID-19 maintains an ominous condition which constitutes a threat, especially for the susceptible population. The cardiac injury occurs in approximately 30% of COVID-19 infections and is associated with a worse prognosis. The clinical presentation of cardiac involvement can be COVID-19-related myocarditis. Our review aims to summarise current evidence about that complication. The research was registered at PROSPERO (CRD42022338397). We performed a systematic analysis using five different databases, including i.a. MEDLINE. Further, the backward snowballing technique was applied to identify additional papers. Inclusion criteria were: full-text articles in English presenting cases of COVID-19-related myocarditis diagnosed by the ESC criteria and patients over 18 years old. The myocarditis had to occur after the COVID-19 infection, not vaccination. Initially, 1588 papers were screened from the database search, and 1037 papers were revealed in the backward snowballing process. Eventually, 59 articles were included. Data about patients' sex, age, ethnicity, COVID-19 confirmation technique and vaccination status, reported symptoms, physical condition, laboratory and radiological findings, applied treatment and patient outcome were investigated and summarised. COVID-19-related myocarditis is associated with the risk of sudden worsening of patients' clinical status, thus, knowledge about its clinical presentation is essential for healthcare workers.

An Artificial Intelligence Approach to Guiding the Management of Heart Failure Patients Using Predictive Models: A Systematic Review.

Heart failure (HF) is one of the leading causes of mortality and hospitalization worldwide. The accurate prediction of mortality and readmission risk provides crucial information for guiding decision making. Unfortunately, traditional predictive models reached modest accuracy in HF populations. We therefore aimed to present predictive models based on machine learning (ML) techniques in HF patients that were externally validated. We searched four databases and the reference lists of the included papers to identify studies in which HF patient data were used to create a predictive model. Literature screening was conducted in Academic Search Ultimate, ERIC, Health Source Nursing/Academic Edition and MEDLINE. The protocol of the current systematic review was registered in the PROSPERO database with the registration number CRD42022344855. We considered all types of outcomes: mortality, rehospitalization, response to treatment and medication adherence. The area under the receiver operating characteristic curve (AUC) was used as the comparator parameter. The literature search yielded 1649 studies, of which 9 were included in the final analysis. The AUCs for the machine learning models ranged from 0.6494 to 0.913 in independent datasets, whereas the AUCs for statistical predictive scores ranged from 0.622 to 0.806. Our study showed an increasing number of ML predictive models concerning HF populations, although external validation remains infrequent. However, our findings revealed that ML approaches can outperform conventional risk scores and may play important role in HF management.

Novel Phenotyping for Acute Heart Failure-Unsupervised Machine Learning-Based Approach.

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.

Tablet-Based Assessment of Cognitive Function Among Heart Failure Patients.

BACKGROUND: Cognitive impairment accompanying heart failure (HF) is an additional HF comorbidity, which may potentially affect the patient's self-care and compliance. We aimed to assess cognitive function (CF) using an application with games created as a cognitive training tool for children and adults, applied using a tablet, and to compare the results obtained by HF patients with the results obtained by healthy age-matched controls. METHODS: A total of 69 individuals (49 HF patients and 10 healthy controls) were assessed using 4 games dedicated to measuring cognitive skills as well as questionnaires regarding their socioeconomic status. Additionally, HF patients were asked about their quality of life and anxiety and depression. RESULTS: HF patients demonstrated worse results in each game assessing their cognitive functions as compared to the healthy age-matched controls, which is consistent with the previous studies on CF in HF. We have also noticed interesting patterns of relations between CF and sleep and education. CONCLUSIONS: We have demonstrated that information and communication technology devices can be successfully applied as feasible tools for cognitive assessment in the HF population. This is important as tablet-based CF assessment can be done on a large population without the involvement of trained personnel.

Fractional flow reserve-guided treatment in coronary artery disease: Clinical practice.

The assessment of functional severity of moderate coronary stenoses is challenging. Coronary angiography remains the standard technique for diagnosis, although, due to its limitations, it is frequently insufficient to detect relevant myocardial ischemia. Fractional flow reserve (FFR) is defined as the ratio between the mean hyperemic coronary artery pressure distal to the lesion and mean pressure in the aorta. The FFR measurement is currently supported by guidelines to evaluate the hemodynamic significance of lesions. Proper identification of patients that have the potential to benefit from revascularization is crucial. Based on already published literature, we focus on the long-term follow-up of patients with FFR-driven treatment. We also provide a review of specific clinical cases such as borderline FFR values, comorbidities or lesions in anatomical risk locations, in which interpretation can be challenging during the physiological assessment. The aim of this paper is to provide an overview of the evidence of FFR implementation in daily clinical practice and determine issues that raise doubts.

Ultrafiltration in acute heart failure: Current knowledge and fields for further research.

Heart failure is one of the leading causes of death in developed countries and remains a significant burden to the healthcare system. Fluid overload is a process responsible for the majority of the heart failure symptoms. Pharmacotherapy is a first-line treatment for this condition; however, due to the phenomenon of diuretic resistance, drug therapy can frequently be insufficient. Ultrafiltration is a promising but still understudied procedure that effectively targets the underlying pathophysiological mechanisms of congestion. The increased availability of simplified ultrafiltration devices, especially in intensive care units, prompted us to perform a current literature review on this treatment. In the present paper, we provide a concise review of the published trials on ultrafiltration, with a brief commentary on their conclusions and shortcomings. We also discuss the practical aspects of this treatment that remain unclear, such as the accurate selection of patients, choosing a suitable protocol for ultrafiltration, the proper time of initiation, monitoring of the therapy, and its desirable effects on renal function with further restoration of diuretic agent responsiveness.