Cardiology最新文献

Introduction: Angiotensin-converting enzyme 2 (ACE2) of the renin-angiotensin-aldosterone system (RAAS) serves as a functional receptor to gain entry into the cells for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19). The interaction between SARS-CoV-2 and ACE2 is a potential virulent factor in infectivity. Our study aimed to ascertain the association of RAAS inhibitors with adverse cardiovascular and other outcomes in hospitalized COVID-19 patients.

Methods: This is a retrospective study of medical records of ≥18-year-old patients hospitalized for COVID-19 from March 2020 to October 2020. Primary outcomes were acute cardiovascular events (ST-elevation myocardial infarction, non-ST-elevation myocardial infarction type 1, acute congestive heart failure, acute stroke) and mortality. Secondary outcomes were respiratory failure, need for and duration of mechanical ventilation, acute deep vein thrombosis or pulmonary embolism (DVT/PE), and readmission rate.

Results: Among 376 hospitalized COVID-19 patients, 149 were on RAAS inhibitors. No statistically significant differences were found between RAAS inhibitor and non-RAAS inhibitor groups with respect to acute cardiovascular events (6% vs. 6.2%, p = 0.94), acute DVT/PE (4.7% vs. 4.8%, p = 0.97), hypoxia (62.4% vs. 58.6%, p = 0.46), need for mechanical ventilation (18.1% vs. 16.7%, p = 0.72), mortality (19.5% vs. 22%, p = 0.56), and readmission rate (11.4% vs. 14.1%, p = 0.45). Some nuances discovered were a higher rate of hospitalizations among Native Americans receiving RAAS inhibitors (30.2% vs. 19.8%) and significantly lower levels of procalcitonin in patients on RAAS inhibitors.

Conclusions: Among hospitalized patients with COVID-19, those on RAAS inhibitors showed no significant differences in acute cardiovascular events, acute DVT/PE, hypoxia, need for mechanical ventilation, readmission, or mortality rate compared to those not on them. However, further large-scale studies are needed to validate these findings.

Introduction: Atrial fibrillation (AF) increases the risk for stroke, dementia and impaired health related quality of life (HRQL). Elective direct current cardioversion (ECV) is often used to restore sinus rhythm, but is associated with thromboembolism. While larger strokes usually produce symptoms, subclinical ones may go unrecognized and may cause cognitive and functional decline over time. In the current study, we sought to evaluate the effects of ECV on silent brain infarctions and HRQL in patients with AF.

Methods: Patients with AF (n=46) underwent brain magnetic resonance imaging (MRI) and HRQL assessment using the EuroQL-5D5L questionnaire before and after ECV. Implantable loop recorders (ILR) were used to observe the rate of early AF recurrences within the first thirty days. All patients were treated with anticoagulants according to guidelines. The primary endpoint was silent brain infarction assessed by brain MRI within the first two weeks after ECV. Secondary endpoints were the change in HRQL and its association with AF recurrence at follow-up and by ILR recordings.

Results: New silent brain infarction after ECV was detected in one patient. At follow-up visit after 19.1 days AF recurrence was detected by 12-lead ECG in 13 patients (28.3 %), whereas 27 patients (58.7 %) had AF recurrence recorded by ILR within the first thirty days after ECV. European Heart Rhythm Association (EHRA) symptom score and the EuroQL-5d5L score were improved after ECV.

Conclusion: Silent brain infarctions may occur after ECV despite anticoagulation treatment. Early AF recurrence is frequent. ECV positively affects HRQL mainly in those patients with sustained sinus rhythm at follow-up.

Introduction: The AIRCARD study is designed to investigate the relationship between long-term exposure to air and noise pollution and cardiovascular disease incidence and mortality. We aim to conduct a robust prospective cohort analysis assessing the cumulative and differential impacts of air and noise pollution exposure on cardiovascular disease and mortality. This study will adjust for relevant confounders, including traditional cardiovascular risk factors, socioeconomic indicators, and lipid-lowering agents.

Methods: This prospective cohort study will include 27,022 male participants aged 65-74, recruited from the two large Danish DANCAVAS and VIVA trials, both population-based randomized, multicentered, clinically controlled studies. We will assess long-term exposure to air pollutants using the state-of-the-art DEHM/UBM/AirGIS modeling system and noise pollution through the Nord2000 and SoundPLAN models, covering data from 1979 to 2019. This statistical analysis plan is strictly formulated to predefine the analytical approach for all outcomes and key study variables before data access. The primary analysis will utilize Cox proportional hazards models, adjusted for confounders identified in our cohort (age, body mass index, hypertension, diabetes, smoking status, family history of heart disease, socioeconomic factors, and lipid-lowering agents). This statistical analysis plan further includes Spearman rank correlation to explore inter-pollutant associations.

Conclusion: The AIRCARD study addresses global concerns about the impact of air and noise pollution on cardiovascular disease. This research is important for understanding how the pollutants contribute to cardiovascular disease. We aim to provide insights into this area, emphasizing the need for public health measures to mitigate pollution exposure. Our goal is to provide policymakers and healthcare professionals with information on the role of environmental factors in cardiovascular health that could influence global strategies to reduce the cardiovascular disease burden associated with pollution. The design of this SAP ensures transparency and verifiability, considering the complexities of evaluating environmental health impacts over an extended period.

Introduction: The aim of this study was to investigate the expression and predictive value of NOD-like receptor thermal protein domain-related protein 3 (NLRP3) in patients with non-valvular atrial fibrillation (NVAF) with heart failure with preserved ejection fraction (HFpEF).

Methods: This was a retrospective analysis of 121 patients diagnosed with NVAF. According to the occurrence of HFpEF, 81 patients were assigned to the NVAF group and 40 patients to the NVAF/HFpEF group. The levels of NLRP3, B natriuretic peptide (BNP), and interleukin-1β (IL-1β) were determined using ELISA. Independent predictors for HFpEF in NVAF were determined using logistic regression. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of each factor.

Results: Expression levels of NLRP3, BNP, and IL-1β in the NVAF/HFpEF group, as well as the H2FPEF score were significantly higher than those in the NVAF group. Pearson analysis showed that NLRP3, BNP, and IL-1β expression levels in NVAF patients and the H2FPEF score was positively correlated (r = 0.409, r = 0.244, r = 0.299, p < 0.001). Multivariate logistic regression analysis showed that the NLRP3, BNP, or H2FPEF score can be used as independent factor for predicting the occurrence of HFpEF in NVAF. ROC curves showed that the areas under the curve of NLRP3, BNP, and H2FPEF scores for predicting the occurrence of HFpEF in NVAF patients were 0.856, 0.831, and 0.811, respectively.

Conclusion: The NLRP3 level is elevated in the peripheral blood of NVAF patients with HFpEF and is positively correlated with the H2FPEF score. NLRP3 may serve as a potential predictor of HFpEF in patients with NVAF.

Coronary artery disease (CAD) affects over 20 million Americans and its' spectrum of impact leads to an estimated 7 million deaths, as well as the loss of 129 million disability-adjusted life years, worldwide, each year. CAD develops as atherosclerotic plaque forms in the coronary arteries. These plaques can eventually limit blood flow to myocardial tissue resulting in ischemia a risk for acute plaque rupture and acute coronary syndrome. While chest pain may represent a wide array of underlying diseases, given the high morbidity and mortality associated with CAD, an ischemic cardiac etiology must always be considered. Early diagnosis and treatment of CAD can improve patient outcomes through guiding risk factor modification and treatment modalities including medical and invasive approaches. While discovering coronary disease early can allow for treatments which can yield great benefit13, many tests are equivocal and can be associated with additional risk and unnecessary cost. This leaves the question; if there is some concern for stable CAD, who should we test, and which modality should be used? This comprehensive review aims to describe the available CAD testing modalities, detail their risks and benefits, and describe when each should be considered in the evaluation of a patient with suspected CAD. (Central illustration).

Introduction: The prevalence of atrial fibrillation (AF) increases with age. Although most AF cases are caused by irregular electrical impulses near the pulmonary vein, not all elderly individuals develop AF. Moreover, risk factors such as hypertension and diabetes do not always lead to AF, even in severe conditions such as pneumonia. We aimed to examine iron kinetics, including ferritin, in patients with AF and individuals in normal sinus rhythm (NSR) using peripheral blood samples.

Methods: This case-control study included 178 patients who visited the outpatient clinic of a cardiovascular and arrhythmia specialist at the National Center for Geriatrics and Gerontology between August and October 2023. Patients with missing iron-related blood tests and those with pacemaker implantation were excluded. Iron parameters (ferritin, free iron, transferrin saturation) were compared between AF (n = 53) and NSR (n = 125) groups.

Results: The AF group had higher log brain natriuretic peptide (BNP) levels, indicating increased cardiac load (AF 2.18 vs. NSR 1.53). However, there were no significant differences in iron parameters between the AF and NSR groups. After matching for age, sex, and coronary artery disease, the AF group showed an increasing trend in ferritin and a decreasing trend in free iron with BNP elevation, suggesting chronic inflammation. In contrast, the NSR group showed no significant changes in iron parameters with BNP elevation.

Conclusion: Patients with AF are more likely to have elevated ferritin levels and decreased free iron levels during cardiac overload. Thus, they are more likely to present with chronic inflammation associated with cardiac overload in AF. Future studies should investigate the mechanisms underlying this phenomenon and its implications for AF treatment.

Introduction: High-molecular-weight (HMW) von Willebrand factor (VWF) multimer deficiency occurs in classical low-flow, low-gradient (LF/LG) aortic stenosis (AS) due to shear force-induced proteolysis. The prognostic value of HMW VWF multimer deficiency is unknown. Therefore, we sought to evaluate the impact of HMW VWF multimer deficiency on clinical outcome.

Methods: In this prospective research study, a total of 83 patients with classical LF/LG AS were included. All patients underwent dobutamine stress echocardiography to distinguish true-severe (TS) from pseudo-severe (PS) classical LF/LG AS. HMW VWF multimer ratio was calculated using densitometric Western blot band quantification. The primary endpoint was all-cause mortality.

Results: Mean age was 79 ± 9 years, and TS classical LF/LG AS was diagnosed in 73% (n = 61) and PS classical LF/LG AS in 27% (n = 22) of all patients. Forty-six patients underwent aortic valve replacement (AVR) and 37 were treated conservatively. During a mean follow-up of 27 ± 17 months, 47 deaths occurred. Major bleeding complications after AVR (10/46; 22%) were more common in patients with HMW VWF multimer ratio <1 (8/17; 47%) in comparison to patients with a normal multimer pattern (2/29; 7%) at baseline (p = 0.003). In a multivariable Cox regression analysis, HMW VWF multimer deficiency was a predictor of all-cause mortality (HR: 3.02 [95% CI: 1.31-6.96], p = 0.009) in the entire cohort. This association was driven by higher mortality rates in the AVR group (multivariable-adjusted HR: 9.4; 95% CI 2.0-43.4, p = 0.004).

Conclusions: This is the first study to demonstrate the predictive value of HMW VWF multimer ratio for risk stratification in patients with classical LF/LG AS. HMW VWF multimer deficiency was associated with an increased risk of all-cause mortality and major bleeding complications after AVR.

Introduction: Cardiovascular disease nursing is a critical clinical application that necessitates real-time monitoring models. Previous models required the use of multi-lead signals and could not be customized as needed. Traditional methods relied on manually designed supervised algorithms, based on empirical experience, to identify waveform abnormalities and classify diseases, and were incapable of monitoring and alerting abnormalities in individual waveforms.

Methods: This research reconstructed the vector model for arbitrary leads using the phase space-time-delay method, enabling the model to arbitrarily combine signals as needed while possessing adaptive denoising capabilities. After employing automatically constructed machine learning algorithms and designing for rapid convergence, the model can identify abnormalities in individual waveforms and classify diseases, as well as detect and alert on abnormal waveforms.

Result: Effective noise elimination was achieved, obtaining a higher degree of loss function fitting. After utilizing the algorithm in Section 3.1 to remove noise, the signal-to-noise ratio increased by 8.6%. A clipping algorithm was employed to identify waveforms significantly affected by external factors. Subsequently, a network model established by a generative algorithm was utilized. The accuracy for healthy patients reached 99.2%, while the accuracy for APB was 100%, for LBBB 99.32%, for RBBB 99.1%, and for P-wave peak 98.1%.

Conclusion: By utilizing a three-dimensional model, detailed variations in electrocardiogram signals associated with different diseases can be observed. The clipping algorithm is effective in identifying perturbed and damaged waveforms. Automated neural networks can classify diseases and patient identities to facilitate precision nursing.