Analysis of risk factors for complications in echocardiography-guided percutaneous intramyocardial septal radiofrequency ablation.

BACKGROUND: The feasibility of percutaneous intramyocardial septal radiofrequency ablation (PIMSRA) for the treatment of hypertrophic obstructive cardiomyopathy (HOCM) has been previously reported. However, limited investigation has been conducted regarding the complications associated with this procedure. OBJECTIVE: This study aims to analyze the risk factors affecting the occurrence of complications during PIMSRA, such as pericardial effusion, ventricular premature beats, and interventricular septal perforation. In this study, the optimal cut-off values for these risk factors are also explored, and corresponding strategies for prevention are proposed. METHODS: A total of 101 patients diagnosed with HOCM who underwent the PIMSRA procedure from 2021 to 2022 were included in this retrospective analysis. Patients were classified into subgroups with or without complications based on procedural records. Univariate and multivariate regression analyses were conducted to identify independent risk factors for complications during the PIMSRA procedure. RESULTS: There were 48 patients with complications and 53 patients without complications. The heart rate at the start of the procedure and the maximum left ventricular outflow tract gradient (LVOTG) were independent risk factors related to PIMSRA complications. The optimal cut-off values for predicting complication occurrence were a heart rate > 49 bpm at the start of the procedure (OR: 3.79, 95% CI: 1.64-8.78, p = 0.002) and a maximum LVOTG > 92 mmHg (OR: 2.57, 95% CI: 1.15-5.75, p = 0.022), respectively. CONCLUSIONS: The occurrence of PIMSRA complications is primarily associated with the heart rate at the start of the procedure and the maximum LVOTG. It is recommended to establish a comprehensive control plan to minimize the risk of complications during PIMSRA procedures.

Accuracy of death risk prediction models for acute coronary syndrome patients: a systematic review and meta-analysis.

INTRODUCTION: This study systematically evaluates the accuracy of several death risk prediction models for patients with acute coronary syndrome (ACS) through evidence-based methods. We identify the most accurate and effective ACS death risk prediction model and provide an evidence-based basis for clinical healthcare personnel to evaluate their choice of death risk prediction model for ACS patients. EVIDENCE ACQUISITION: An evidence-based approach was used to study the current death risk prediction model for ACS. First, a literature search was carried out using computer-based and manual searching. The literature databases searched include Cochrane Library, MEDLINE, EMBASE, PubMed, Web of Science, WanFang Data, CNKI, VPCS, and SinoMed. The search period was limited to 2009 to 2022. Screening, quality evaluation and data extraction were carried out for the included articles. The PROBAST was used to conduct a migration risk assessment. RevMan 5.3 and Meta-DiSc 1.4 were used in combination to determine the model effect sizes. A descriptive analysis was conducted for the data that could not be meta-analyzed. EVIDENCE SYNTHESIS: A total of 8277 articles were initially included in this study. After screening, 25 articles were finally included, involving 11 different risk prediction models. A total of 306,390 patients with ACS were included of which 158,080 (51.6%) were male and 147,793 (48.4%) were female. The patients stemmed from 11 different countries (e.g., China, the USA, Spain, the UK, etc.). The total number of deaths was 23,601. The sensitivity of the GRACE risk prediction model was 0.78, with a specificity of 0.76 and an AUC value of 0.86. The sensitivity of the CAMI risk prediction model was 0.78, with a specificity of 0.70 and an AUC value of 0.85. The sensitivity of the TIMI risk prediction model was 0.51, with a specificity of 0.81, and an AUC value of 0.64. The sensitivity of the REMS risk prediction model was 0.78, with a specificity of 0.46 and an AUC value of 0.41. Eight different risk prediction models (EPICOR, CRUSADE, SAMI, GWTG, LNS, SYNTAX II, APACHE II) that could not be combined with the effect size were also included, with sensitivities ranging from 0.77-0.95, specificities ranging from 0.22-0.99, and AUC values ranging from 0.71-0.92. CONCLUSIONS: The GRACE and CAMI risk prediction models demonstrate good accuracy for evaluating the death risk of ACS patients. The accuracy of the TIMI risk prediction model is similar to that of the REMS risk prediction model. The APACHE II, SYNTAX II, EPICOR, and CAMI risk prediction models also show good accuracy for estimating the risk of death in ACS patients, although further validation is needed due to limited evidence. For improved predictive accuracy and to help advance medical interventions, the author recommends that clinical medical staff use the GRACE model to predict the death risk of ACS patients.

Targeting pro-inflammatory T cells as a novel therapeutic approach to potentially resolve atherosclerosis in humans.

Atherosclerosis (AS), a leading cause of cardio-cerebrovascular disease worldwide, is driven by the accumulation of lipid contents and chronic inflammation. Traditional strategies primarily focus on lipid reduction to control AS progression, leaving residual inflammatory risks for major adverse cardiovascular events (MACEs). While anti-inflammatory therapies targeting innate immunity have reduced MACEs, many patients continue to face significant risks. Another key component in AS progression is adaptive immunity, but its potential role in preventing AS remains unclear. To investigate this, we conducted a retrospective cohort study on tumor patients with AS plaques. We found that anti-programmed cell death protein 1 (PD-1) monoclonal antibody (mAb) significantly reduces AS plaque size. With multi-omics single-cell analyses, we comprehensively characterized AS plaque-specific PD-1+ T cells, which are activated and pro-inflammatory. We demonstrated that anti-PD-1 mAb, when captured by myeloid-expressed Fc gamma receptors (FcγRs), interacts with PD-1 expressed on T cells. This interaction turns the anti-PD-1 mAb into a substitute PD-1 ligand, suppressing T-cell functions in the PD-1 ligands-deficient context of AS plaques. Further, we conducted a prospective cohort study on tumor patients treated with anti-PD-1 mAb with or without Fc-binding capability. Our analysis shows that anti-PD-1 mAb with Fc-binding capability effectively reduces AS plaque size, while anti-PD-1 mAb without Fc-binding capability does not. Our work suggests that T cell-targeting immunotherapy can be an effective strategy to resolve AS in humans.

Association between dietary patterns and cardiovascular diseases: A review.

Cardiovascular disease (CVD), especially atherosclerosis, is the primary cause of global deaths. It accounts for millions of deaths annually. Even a small reduction in CVD through preventive treatment can have a substantial impact. Dietary patterns and substances are strongly linked to chronic diseases such as atherosclerosis, hypertension, heart failure, and type 2 diabetes. An unhealthy diet could lead to traditional risk factors such as LDL levels, TG levels, diabetes, and high blood pressure while accelerating atherosclerosis progression. Recent research has shown the potential of dietary interventions to prevent and treat cardiovascular disease, particularly through healthy dietary patterns such as the Mediterranean diet or DASH. In 2016, the World Health Organization (WHO) and the US Centers for Disease Control and Prevention (CDC) launched a new initiative aimed at enhancing the prevention and control of cardiovascular disease (CVD) by improving the management of CVD in primary care, including the optimization of dietary patterns. Here, this review summarizes several large cohort researches about the effects of dietary patterns on atherosclerosis, refines dietary components, and outlines some typical anti-atherosclerosis dietary agents. Finally, this review discusses recent mechanisms by which dietary interventions affect atherosclerosis progression.