Canadian Journal of Cardiology最新文献

Extracorporeal membrane oxygenation (ECMO) is a form of critical care support for patients with severe respiratory or circulatory failure where conventional medical treatments have failed. Two main configurations of ECMO exist: Venovenous (VV) to support failing lungs, and venoarterial (VA) for circulatory shock. Echocardiography is an invaluable tool in the assessment of patients requiring ECMO. It can be utilised for decision-making regarding the most appropriate configuration, detection and management of complications, and to guide weaning. This concise review is intended to be a primer on the role of echocardiography for patients requiring ECMO for circulatory failure.

Atrial fibrillation (AF) is largely co-morbid with heart failure (HF), worsening prognosis in patients with ventricular dysfunction. Treating AF through ablation can improve outcomes and reduce the transition to end-stage HF, highlighting the importance of early recognition in patients with ventricular dysfunction. Circulating NT-proBNP is a well-known biomarker for AF in patients with ventricular dysfunction, however, large individual variability limits its predictive power and therefore utility. With the rise of high-throughput proteomics in the era of precision medicine, novel and stable biomarkers may be identified with the potential to improve risk stratification, detection, and management.

The Bayesian analytical framework is clinically intuitive, characterized by the incorporation of previous evidence into the analysis, and allowing an estimation treatment effects and their associated uncertainties. The application of Bayesian statistical inference is not new to the cardiovascular field, as illustrated by various recent randomized trials that applied a primary Bayesian analysis. Given the guideline-shaping character of trials, a thorough understanding of the concepts and technical details of Bayesian statistical methodology is of utmost importance to the modern practicing cardiovascular physician. Therefore, this Review aims to present a step-by-step guide to interpreting and performing a Bayesian (re-)analysis of cardiovascular clinical trials, while highlighting the main advantages of Bayesian inference for the clinical reader. After an introduction of the concepts of frequentist and Bayesian statistical inference and reasons to apply Bayesian methods, key steps for performing a Bayesian analysis are presented, including: the verification of the clinical appropriateness of the research question, the quality and completeness of the trial design, as well as the adequate elicitation of the prior (i.e., ones belief towards a certain treatment before the current evidence becomes available), identification of the likelihood, and their combination into a posterior distribution. Examination of this posterior distribution offers the possibility of not only determining the probability of treatment superiority, but also the probability of exceeding any chosen minimal clinically important difference. Multiple priors should be transparently prespecified, limiting post-hoc manipulations. Using this guide, three cardiovascular randomized controlled trials are re-analysed, demonstrating the clarity and versatility of Bayesian inference.

Cardio-oncology has become a well-established subspecialty due to the growing burden of cardiovascular diseases in oncology patients, resulting from the cardiac toxicities of cancer therapies and the coexistence of both conditions in the same population. As with other cardiovascular conditions, cardiac arrhythmias have emerged as an important concern in cancer patients. However, the management of arrhythmias is more complicated in these patients because of complex interactions between onco-therapeutics and arrhythmia treatment strategies. Similarly, patients with cardiac implantable electronic devices (CIED), who require cancer treatment strategies that involve radiation therapy require specific management strategies. Thus, there is a need for a specific mechanistic understanding of electrophysiological abnormalities, arrhythmia, and device management in oncology patients, especially given the expanding range of oncological therapies and radiation strategies. This increasingly prevalent clinical challenge requires new expertise that expands on a yearly basis. This narrative review deals with this recent expansion and addresses key areas of onco-electrophysiology, including the mechanistic basis of common ECG changes, diagnosis and management of arrhythmias attributable to onco-therapeutics, and the care of arrhythmia patients who require oncological therapies, especially device patients and drug interactions leading to arrhythmias as seen by cardiac physicians dealing with oncology patients. Additionally, it reviews evolving management strategies and protocols for patients with implantable devices, especially if urgent radiation is needed. This review aims to bridge the recent knowledge growth in arrhythmia care for cancer patients and highlight the evolution of onco-electrophysiology as a subspeciality.

Background: According to recent guidelines, the selection of transcatheter vs. surgical aortic valve replacement (TAVR vs SAVR) in low-risk patients depends on age and life expectancy. Our objective was to understand independent risk factors for reduced life expectancy following isolated SAVR and the rate of re-do aortic valve (AV) intervention in different age groups, to delineate optimal intervention depending on patient characteristics.

Methods: Between 2000-2015, 2026 patients underwent isolated SAVR with Edwards pericardial tissue valves. Multivariable models were conducted to determine independent risk factors for long-term survival in three age groups.

Results: The 10-year survival rates were 83.4±2.3%, 72.7± 2.6% and 39.8±3.0% in Group I (age <65 years, n=577), II (age 65 - <75 years, n=693) and III (age ≥75 years, n=756), respectively. Independent factors for the reduced long-term survival were pulmonary hypertension (PH), renal failure, peripheral vascular disease, diabetes, and NYHA class IV in Group I; PH, diabetes, current smoking, and atrial arrhythmia in Group II; and PH, anemia, and NYHA class IV in Group III. The re-do AV intervention rate at 10 years was much higher in Group I than in Groups II and III (14.7±2.5% vs. 3.4±1.1% and 0.8±0.4%, P<0.001).

Conclusions: We identified risk factors for reduced long-term survival following isolated SAVR in different age groups and PH being the only risk factor across all ages, which should assist in decision-making for SAVR vs. TAVR. Our results also support the current recommendation of bioprostheses in patients aged >65 years given extremely low rate of re-do AV intervention.