World Journal of Cardiology最新文献

Point-of-care ultrasound (POCUS) of the internal jugular vein (IJV) offers a non-invasive means of estimating right atrial pressure (RAP), especially in cases where the inferior vena cava is inaccessible or unreliable due to conditions such as liver disease or abdominal surgery. While many clinicians are familiar with visually assessing jugular venous pressure through the internal jugular vein, this method lacks sensitivity. The utilization of POCUS significantly enhances the visualization of the vein, leading to a more accurate identification. It has been demonstrated that combining IJV POCUS with physical examination enhances the specificity of RAP estimation. This review aims to provide a comprehensive summary of the various sonographic techniques available for estimating RAP from the internal jugular vein, drawing upon existing data.

Physical inactivity remains in high levels after cardiac surgery, reaching up to 50%. Patients present a significant loss of functional capacity, with prominent muscle weakness after cardiac surgery due to anesthesia, surgical incision, duration of cardiopulmonary bypass, and mechanical ventilation that affects their quality of life. These complications, along with pulmonary complications after surgery, lead to extended intensive care unit (ICU) and hospital length of stay and significant mortality rates. Despite the well-known beneficial effects of cardiac rehabilitation, this treatment strategy still remains broadly underutilized in patients after cardiac surgery. Prehabilitation and ICU early mobilization have been both showed to be valid methods to improve exercise tolerance and muscle strength. Early mobilization should be adjusted to each patient's functional capacity with progressive exercise training, from passive mobilization to more active range of motion and resistance exercises. Cardiopulmonary exercise testing remains the gold standard for exercise capacity assessment and optimal prescription of aerobic exercise intensity. During the last decade, recent advances in healthcare technology have changed cardiac rehabilitation perspectives, leading to the future of cardiac rehabilitation. By incorporating artificial intelligence, simulation, telemedicine and virtual cardiac rehabilitation, cardiac surgery patients may improve adherence and compliance, targeting to reduced hospital readmissions and decreased healthcare costs.

Background: Acute myocardial infarction (AMI) is a severe cardiovascular disease caused by the blockage of coronary arteries that leads to ischemic necrosis of the myocardium. Timely medical contact is critical for successful AMI treatment, and delays increase the risk of death for patients. Pre-hospital delay time (PDT) is a significant challenge for reducing treatment times, as identifying high-risk patients with AMI remains difficult. This study aims to construct a risk prediction model to identify high-risk patients and develop targeted strategies for effective and prompt care, ultimately reducing PDT and improving treatment outcomes.

Aim: To construct a nomogram model for forecasting pre-hospital delay (PHD) likelihood in patients with AMI and to assess the precision of the nomogram model in predicting PHD risk.

Methods: A retrospective cohort design was employed to investigate predictive factors for PHD in patients with AMI diagnosed between January 2022 and September 2022. The study included 252 patients, with 180 randomly assigned to the development group and the remaining 72 to the validation group in a 7:3 ratio. Independent risk factors influencing PHD were identified in the development group, leading to the establishment of a nomogram model for predicting PHD in patients with AMI. The model's predictive performance was evaluated using the receiver operating characteristic curve in both the development and validation groups.

Results: Independent risk factors for PHD in patients with AMI included living alone, hyperlipidemia, age, diabetes mellitus, and digestive system diseases (P < 0.05). A nomogram model incorporating these five predictors accurately predicted PHD occurrence. The receiver operating characteristic curve analysis indicated area under the receiver operating characteristic curve values of 0.787 (95% confidence interval: 0.716-0.858) and 0.770 (95% confidence interval: 0.660-0.879) in the development and validation groups, respectively, demonstrating the model's good discriminatory ability. The Hosmer-Lemeshow goodness-of-fit test revealed no statistically significant disparity between the anticipated and observed incidence of PHD in both development and validation cohorts (P > 0.05), indicating satisfactory model calibration.

Conclusion: The nomogram model, developed with independent risk factors, accurately forecasts PHD likelihood in AMI individuals, enabling efficient identification of PHD risk in these patients.

Transcatheter aortic valve replacement (TAVR) has emerged as a formidable treatment option for severe symptomatic aortic stenosis ahead of surgical aortic valve replacement. The encouraging results from large randomized controlled trials has resulted in an exponential rise in the use of TAVR even in the low-risk patients. However, this is not without challenges. Need for permanent pacemaker (PPM) post-TAVR remains the most frequent and clinically relevant challenge. Naturally, identifying risk factors which predispose an individual to develop high grade conduction block post-TAVR is important. Various demographic factors, electrocardiographic features, anatomic factors and procedural characteristics have all been linked to the development of advanced conduction block and need for PPM following TAVR. Amongst these electrophysiological variables, most notably a prolonged QRS > 120 ms regardless of the type of conduction block seems to be one of the strongest predictors on logistic regression models. The index study by Nwaedozie et al highlights that patients requiring PPM post-TAVR had higher odds of having a baseline QRS > 120 ms and were more likely to be having diabetes mellitus that those who did not require PPM.