Progress in cardiovascular diseases最新文献

Background: Giant cell myocarditis (GCM) and cardiac sarcoidosis (CS) are rare inflammatory diseases of the myocardium with poor prognosis. Cardiovascular disease outcomes among both diseases have not been well studied with limited literature.

Objective: This study aims to investigate the cardiovascular outcomes among patients with GCM and CS.

Method: We queried the TriNeTX Global Collaborative Network for adult patients with giant cell myocarditis and cardiac sarcoidosis between January 2000 to May 2023 and created two groups: one with giant cell myocarditis and second with cardiac sarcoidosis. Both the groups were followed for 6 months and 12 months.

Result: After propensity score matched analysis (PSM), among the 4804 patients (2402 patients in each group), the mean age of patients was 57.1 and 57.6 years in GCM and CS groups, respectively. PSM analysis showed that primary outcome i.e., all-cause mortality was significantly higher in GCM group both after 6 months [relative risk (RR) 2.33, 95 % confidence interval (CI): 1.64-3.30, p < 0.01] and 1 year follow up [RR, 1.54 (95 % CI: 1.20-1.98), p < 0.01] as compared with CS group. However, secondary outcomes i.e., heart failure (HF) at 6 month (RR 0.66, 95 % CI: 0.52-0.85, p < 0.01), and at 1 year (RR 0.60, 95 % CI: 0.49-0.73, p < 0.01), ventricular tachycardia (VT) at 6 months (RR 0.34, 95 % CI: 0.25-0.46, p < 0.01), and at 1 year (RR 0.32, 95 % CI: 0.25-0.41, p < 0.01), atrioventricular (AV) node block at 6 month (RR 0.45, 95 % CI: 0.33-0.61, p < 0.01), and at 1 year (RR 0.43, 95 % CI: 0.34-0.55, p < 0.01), and atrial flutter and fibrillation (AF) at 6 months (RR 0.67, 95 % CI: 0.48-0.94, p = 0.02), and at 1 year (RR 0.59, 95 % CI: 0.45-0.76, p < 0.01) were found significantly lower in GCM group as compared to CS group. On the other hand, heart transplant incidence was comparable between both the groups.

Conclusion: These findings suggest that GCM patients have high risk of mortality and lower risk of HF, VT, AV node block, and AF when compared with CS.

The American Heart Association recently defined the complex interactions among the cardiovascular, renal, and metabolic systems as CKM syndrome. To promote better patient outcomes, having a more profound understanding of CKM pathophysiology and pursuing holistic preventative and therapy strategies is critical. Despite many gaps in understanding CKM syndrome, this study attempts to elucidate two of these gaps: the new emerging biomarkers for screening and the role of inflammation in its pathophysiology. For this review, an extensive search for specific terms was conducted in the following databases: PubMed, Scopus, Web of Science, and Google Scholar. Studies were first assessed by title, abstract, keywords, and selected for portfolio according to eligibility criteria, which led to 38 studies. They provided background information about CKM syndrome; data suggested that serum uric acid, leptin, aldosterone, bilirubin, soluble neprilysin, lipocalin-type-prostaglandin-D-synthase, and endocan could be valuable biomarkers for CKM screening; and finally, the inflammation role in CKM.

The prevalence of coronary microvascular dysfunction (CMD) beyond the spectrum of chronic coronary syndromes (CCS) is non-negligible, pertaining to pathophysiological and therapeutical implications. Thanks to the availability of accurate and safe non-invasive technique, CMD can be identified as a key player in heart failure, cardiomyopathies, Takotsubo syndrome, aortic stenosis. While CMD is widely recognized as a cause of myocardial ischemia leading to a worse prognosis even in the absence of obstructive coronary artery disease, the characterization of CMD patterns beyond CCS might provide valuable insights on the underlying disease progression, being potentially a "red flag" of adverse cardiac remodeling and a major determinant of response to therapy and outcomes. In this review, we aimed to provide an overview of the latest evidence on the prevalence, mechanistic and prognostic implications of CMD beyond the spectrum of CCS (i.e. heart failure, cardiomyopathies, Takotsubo syndrome, aortic stenosis).

As the field of percutaneous coronary intervention grows in volume, expertise, and available tools, interventional cardiologists are increasingly performing more complex and higher-risk coronary artery procedures. Mechanical circulatory support devices, previously used only in urgent situations, are now being utilized as supplementary tools to enhance outcomes in elective complex cases. This shift has sparked significant discussions about patient and device selection, as well as the potential risks involved. In this article, we explore the various devices and their distinct features. Additionally, we also introduce algorithms for device selection, placement and weaning to help guide physicians during their care for their high-risk PCI patients.

Cardiovascular disease (CVD) continues to be a leading cause of global mortality and morbidity. Various established risk factors are linked to CVD, and modifying these risk factors is fundamental in CVD management. Clinical studies underscore the association between dyslipidemia and CVD, and therapeutic interventions that target low-density lipoprotein cholesterol elicit clear benefits. Despite the correlation between low high-density lipoprotein cholesterol (HDLC) and heightened CVD risk, HDL-raising therapies have yet to showcase significant clinical benefits. Furthermore, evidence from epidemiological and genetic studies reveals that not only low HDL-C levels, but also very high levels of HDL-C are linked to increased risk of CVD. In this review, we focus on HDL metabolism and delve into the relationship between HDL and CVD, exploring HDL functions and the observed alterations in its roles in disease. Altogether, the results discussed herein support the conventional wisdom that "too much of a good thing is not always a good thing". Thus, our recommendation is that a careful reconsideration of the impact of high HDL-C levels is warranted, and shall be revisited in future research.

Background: Natural language processing (NLP) can facilitate research utilizing data from electronic health records (EHRs). Large language models can potentially improve NLP applications leveraging EHR notes. The objective of this study was to assess the performance of zero-shot learning using Chat Generative Pre-trained Transformer 4 (ChatGPT-4) for extraction of symptoms and signs, and compare its performance to baseline machine learning and rule-based methods developed using annotated data.

Methods and results: From unstructured clinical notes of the national EHR data of the Veterans healthcare system, we extracted 1999 text snippets containing relevant keywords for heart failure symptoms and signs, which were then annotated by two clinicians. We also created 102 synthetic snippets that were semantically similar to snippets randomly selected from the original 1999 snippets. The authors applied zero-shot learning, using two different forms of prompt engineering in a symptom and sign extraction task with ChatGPT-4, utilizing the synthetic snippets. For comparison, baseline models using machine learning and rule-based methods were trained using the original 1999 annotated text snippets, and then used to classify the 102 synthetic snippets. The best zero-shot learning application achieved 90.6 % precision, 100 % recall, and 95 % F1 score, outperforming the best baseline method, which achieved 54.9 % precision, 82.4 % recall, and 65.5 % F1 score. Prompt style and temperature settings influenced zero-shot learning performance.

Conclusions: Zero-shot learning utilizing ChatGPT-4 significantly outperformed traditional machine learning and rule-based NLP. Prompt type and temperature settings affected zero-shot learning performance. These findings suggest a more efficient means of symptoms and signs extraction than traditional machine learning and rule-based methods.

Endothelial dysfunction and microvascular remodeling underly the development and progression of a host of cardiovascular disease (CVD). However, current methods to assess coronary epicardial microvascular function are invasive, time-intensive, and costly. Optical coherence tomography angiography (OCTA) is an established technology within ophthalmology that provides a quick, noninvasive assessment of vascular structures within the retina. As a growing body of evidence reveals strong associations between the retinal changes on OCTA and the development and progression of CVD, OCTA may indeed be a surrogate test for end-organ dysfunction. OCTA has potential to enhance diagnostic performance, refine cardiovascular risk assessment, strengthen prognostication, and ultimately, improve patient care. We explore the current literature on OCTA in cardiovascular diseases to summarize the clinical utility of retinal OCTA imaging and discuss next-generation cardiovascular applications.