Minerva cardiology and angiology最新文献

Background: Arterial stiffness, particularly aortic stiffness (AoS), is associated with an increased risk of cardiovascular disease. Endovascular repair for abdominal (EVAR) and thoracic (TEVAR) aortic disease may increase AoS. This study protocol aims to assess changes in AoS before and after interventions for aortic disease.

Methods: Patients scheduled for EVAR or TEVAR during a three-year period will be enrolled. An indirect AoS indicator, carotid-to-femoral pulse wave velocity (cf-PWV) will be measured non-invasively using applanation tonometry and reported with others perioperative data before and after the endovascular treatment. Moreover, cardiological data will be collected through echocardiography.

Results: Fifty EVAR and 50 TEVAR will be enrolled. We will primarily analyze changes in cf-PWV. To ensure the reliability of our findings, we will also include supplementary data such as clinical information, morphological data, and functional echocardiographic data.

Conclusions: By examining AoS modifications before and after endovascular aortic repair, this study aims to enhance our understanding of how arterial stiffness changes following endoprosthesis deployment. The findings from the applied protocol are expected to be informative for innovative graft designs with minimized mechanical mismatch with the aortic wall and with improved vascular hemodynamic, aligning with the current trend in improving patient outcomes. Moreover, understanding these modifications is important for predicting and improving long-term cardiovascular outcomes in patients undergoing such interventions.

Background: Data on predictors of poor hemodynamic presentation and rehospitalizations following transcatheter aortic valve replacement (TAVR) are limited. We evaluate the association between neighborhood socioeconomic status (NSES) on echocardiographic presentation and post-TAVR readmission at a high-volume institution.

Methods: All patients undergoing TAVR at a single institution between 2012 and 2022 were included. Patient addresses, baseline variables including Society of Thoracic Surgeons (STS) preoperative risk of mortality and frailty, and post-procedural outcomes were extracted from electronic health records. Using a validated US Census Bureau Index, the NSES of each patient (1-100) was tabulated, with lower values correlating to increased social deprivation. Patients were separated into four ranked groups based on NSES (rank 1: 1-25, rank 4: 76-100). Multivariable regression was performed to determine variables associated with number of days hospitalized in one-year following index TAVR procedure.

Results: A total of 2031 patients were included. The median NSES was 68 (IQR: 53-80). There was a total of 232 (11.4%) readmissions. The median number of days hospitalized in one year following TAVR was 4 (interquartile range [IQR]: 2-7) After adjusting for baseline variables including STS risk score and patient frailty, compared to patients in the lowest ranked socioeconomic group, patients of higher NSES were associated with lower aortic valve gradients at baselines (Exp[β]=0.997, 95% CI: 0.993-0.999, P=0.049). Additionally, compared to patients in the lowest ranked socioeconomic group, patients of NSES were associated with shorter duration of readmission after risk-factor adjustments (Exp[β]=0.996, 95% CI: 0.992-0.999, P=0.032).

Conclusions: Patients of lower socioeconomic status are associated with higher aortic valve gradient at baseline and more days hospitalized in the first year after their index TAVR procedure after adjusting for other risk factors. As TAVR volume continues to expand, physicians and health systems must consider this independent factor when determining patient prognosis and readmission policies.

This tutorial provides a comprehensive guide on leveraging ChatGPT for systematic literature reviews, leveraging actual applications in cardiovascular research. Systematic reviews, while essential, are resource-intensive, and ChatGPT offers a potential solution to streamline the process. The tutorial covers the entire review process, from preparation to finalization. In the preparation phase, ChatGPT assists in defining research questions and generating search strings. During the screening phase, ChatGPT can efficiently screen titles and abstracts, processing multiple abstracts simultaneously. The tutorial also introduces an intermediate step of generating study summaries that leads to the generation of reliable data extraction tables. For assessing the risk of bias, ChatGPT can be prompted to perform these tasks. Using each tool's explanation document to generate an appropriate prompt is an efficient method of reliable risk of bias assessments using ChatGPT. However, users are cautioned about potential hallucinations in ChatGPT's outputs and the importance of manual validation. The tutorial emphasizes the need for vigilance, continuous refinement, and gaining experience with ChatGPT to ensure accurate and reliable results. The methods presented have been successfully tried in several projects, but they remain in nascent stages, with ample room for improvement and refinement.

Eosinophilic myocarditis (EM) is a rare, potentially life-threatening, form of inflammatory heart disease characterized by eosinophilic infiltration of the myocardium. Different diseases are involved in its etiopathogeneses, such as eosinophilic granulomatosis with polyangiitis (or Churg-Strauss Syndrome), hypereosinophilic syndromes, parasitic infections, drug reactions, paraneoplastic syndromes and primary immunodeficiencies (e.g. Omenn Syndrome). There is a wide spectrum of clinical pictures at presentation ranging from chronic restrictive cardiomyopathy (Loeffler cardiomyopathy) to acute necrotizing myocarditis with cardiogenic shock. The genetic contribution and the environmental interplay, such as SARS-CoV-2 infection and related vaccines, are fields not well studied yet. Many non-invasive tools, mainly echocardiography and cardiac magnetic resonance imaging, along with invasive procedures, such as endomyocardial biopsy, are the crucial steps in the diagnostic workup. The correct diagnosis is a challenge but mandatory for timely and appropriate immunosuppressive therapy.

Background: Doxorubicin (DOX) is a potent anti-cancer medication that is associated with numerous adverse effects, particularly concerning damage to the heart.

Methods: This study aimed to investigate the impact of sophocarpine (SOP) on DOX-induced heart injury through both in vivo and in vitro experiments. The experimental techniques employed encompassed echocardiography, hematoxylin/eosin (H&E) staining, Masson staining, immunohistochemical staining, western blotting, and so on.

Results: Echocardiography showed that SOP alleviated DOX-induced cardiac dysfunction, as evidenced by the improvements in both left ventricle ejection fraction and left ventricle fractional shortening. DOX caused upregulations of creatine kinase-MB and lactate dehydrogenase, while SOP decreased these indices. Staining methods such as H&E and Masson showed that SOP reversed the pathological changes induced by DOX. DOX elevated the expression levels of fibrosis-associated proteins such as Collagen I, Collagen III, α-SMA, Fibronectin, MMP-2, and MMP-9. However, SOP reversed these changes. Moreover, the study further revealed that SOP inhibited the TGF-β1/Smad3 signaling pathway.

Conclusions: These findings imply that SOP has the potential to mitigate DOX-induced heart injury by suppressing fibrosis. The underlying molecular mechanism may involve the inhibition of the TGF-β1/Smad3 signaling pathway.

Background: Early diagnosis of hypertension (HT) is crucial for preventing end-organ damage. This study aims to identify the risk factors for future HT in young individuals through the application of machine learning (ML) models.

Methods: The study included individuals aged 18-40 years who had not been diagnosed with HT through ambulatory blood pressure monitoring (ABPM). These participants were monitored for hypertension diagnosis from the date of ABPM application until the date of data collection. Hypertension prediction was carried out using three distinct ML methods: Support Vector Machine, Random Forest, and Least Absolute Shrinkage and Selection Operator. The identification of variables significant for future HT was based on the outcomes of these models.

Results: This study comprised 516 patients, with a mean follow-up duration of 793.4±58.6 days. Following the integration of demographic data, laboratory results, and ABPM findings into the ML models, age, high-density lipoprotein cholesterol, triglycerides, and the standard deviation of systolic blood pressure (SDsis) were identified as predictors for future HT. A logistic regression with the selected variables (age, diabetes mellitus history, HDL, triglycerides, white blood cell count, and SDsis) using the full data set gave the following log odds 0.0737 (P<0.001), 0.7146 (P<0.001), -0.0160 (P=0.071), 0.0026 (P=0.002), 0.0857 (P=0.069), and 0.0850 (P=0.005), respectively. The corresponding probability values of age, diabetes mellitus history, HDL, triglycerides, white blood cell count, and SDsis were 0.5184, 0.6714, 0.4960, 0.5006, 0.5214, and 0.5212, respectively. This indicates a unit increase in all factors, except diabetes mellitus history, increases the probability of future HT by 50%. A history of diabetes, however, increases the probability of future HT by more than two thirds. The history of diabetes mellitus emerged as the most crucial predictor of future HT across all applied methods.

Conclusions: ML methods appear to be valuable tools for predicting future HT. The widespread adoption of these methods and the refinement of more comprehensive models will lay the groundwork for future studies.

Background: Sjogren's Syndrome (SS) plays important roles in the development of essential hypertension. Nevertheless, with the limitation of reverse causality and confounder in observational studies, such a relationship remains unclear. We aimed to assess the causal relationship of SS and hypertension by the Mendelian randomization (MR) approach.

Methods: We used MR to investigate a causal association between SS and essential hypertension. Inverse variance weighted (IVW), MR Egger regression, Maximum likelihood, Weighted median, and MR pleiotropy residual sum and outlier test (MR-PRESSO) were used in this MR analysis.

Results: In this study, we found that the ratio of IVW is 1.00024 (95% CI: 1.00013- 1.00036, P=0.0387), This result was also confirmed by sensitivity analysis methods such as Maximum likelihood is 1.00025 (95% CI: 1.00013-1.00037, P=0.036), MR Egger is 1.00071 (95% CI: 1.00047-1.00095, P=0.0045), and Weighted median is 1.00040 (95% CI: 1.00021- 1.00059, P=0.0322). And MR-Egger intercept method revealed the absence of horizontal pleiotropy in this investigation (P>0.05). The Cochran's Q Test indicated an absence of heterogeneity among them (P>0.05). Heterogeneity and horizontal pleiotropy tests further demonstrate that the results of MR are relatively stable. The above results all suggest that pSS may promote the risk of hypertension.

Conclusions: Our study provides evidence of a causal relationship of SS and hypertension. It is suggested to pay attention to early screening for hypertension, reduce disability and mortality rates, and improve patient prognosis in patients with SS.

Background: Catheter ablation (CA) of atrial fibrillation is routinely used to obtain rhythm control. Evidence suggest that catheter ablation should be done during uninterrupted oral anticoagulation.

Methods: Italian Registry in the setting of atrial fibrillation ablation with rivaroxaban (IRIS) is an Italian multicenter, non-interventional, prospective study which enrolled 250 consecutive atrial fibrillation patients eligible for catheter ablation on rivaroxaban. The decision for rivaroxaban management was left to the physician: uninterrupted or shortly interrupted prior to Catheter ablation. Patients received a follow-up visit at 1 month and 12 months after the procedure.

Results: The primary outcome, represented by all-cause death and systemic embolism at 1 month and 12 months was characterized by one transient ischemic attack and one myocardial infarction in the first 30 days. Both events happened in patients with shortly interrupted strategy (P=0.147), and both in patients who underwent radiofrequency ablation (P=0.737). In the primary safety outcome represented by major bleeding we did not register any event in the 12-month follow-up. The secondary outcome constituted by minor bleeding registered 1 event, after the first 30 days since CA.

Conclusions: IRIS is the biggest real-life data registry regarding CA ablation on rivaroxaban in Italian setting, proving the safety and efficacy of rivaroxaban.

Background: Immune infiltration plays a vital role in the course of acute myocardial infarction (AMI). Cuproptosis is a new type of programmed cell death discovered recently. Currently, there is no study on the mechanism of cuproptosis gene regulating immune infiltration in AMI. Therefore, by integrating cuproptosis-related genes and GEO database-related microarray data, this study analyzed the association between cuproptosis genes and immune infiltration and built a risk model.

Methods: The GSE59867 was used to extract cuproptosis gene expression profile. The R limma package was used to analyze the differentially expressed genes associated with AMI-Cuproptosis. The risk model was constructed according to AMI-cuproptosis differentially expressed genes. Prediction of AMI-cuproptosis-related gene drugs through Coremine Medical database. The upstream miRNAs were predicted using miRWalk, TargetScan, and miRDB libraries, and a miRNA-mRNA network was constructed.

Results: Cuproptosis-related genes (DLST, LIAS, DBT, ATP7A, LIPT1, PDHB, GCSH, DLD, DLAT) were down-regulated in AMI patients. One (ATP7B) gene was up-regulated in AMI patients (P<0.05). These 10 Cuproptosis-related genes were significantly associated with immune cell infiltration. Based on these 10 differential genes, the AMI risk prediction model was constructed, and the AUC value was 0.825, among which the abnormal expression of DLST was a risk factor for AMI. Additionally, we also predicted DLAT upstream miRNAs and associated drug targets, finding that 9 miRNAs were upstream of DLST.

Conclusions: DLST is a potential cuproptosis gene associated with AMI, but its specific mechanism remains unclear and requires further investigation in future studies.