Archivos Peruanos de cardiologia y cirugia cardiovascular最新文献

Objective: Evaluate the impact and clinical applicability of artificial intelligence (AI) models in cardiovascular diagnosis, assessing their potential to improve diagnostic accuracy, operational efficiency, and reliability compared with conventional methods.

Materials and: Methods. A critical review of the recent literature was conducted, encompassing retrospective studies, multicenter trials, and external validations that employed machine learning and deep learning algorithms applied to imaging modalities, electrocardiographic and phonocardiographic signals, as well as clinical and proteomic biomarkers.

Results: Evidence indicates that in cardiac imaging, automated segmentation and ventricular dysfunction detection achieved accuracy metrics exceeding 90%, suggesting readiness for clinical integration. In cardiac signals, deep learning models demonstrated area under the ROC curve values of approximately 0.99 for predicting atrial fibrillation and ischemic heart disease, further supported by explainability techniques. Regarding biomarkers, ensemble models achieved diagnostic accuracies above 95%, and the integration of proteomic and clinical data substantially enhanced predictive performance. Nonetheless, decreased performance in external validations, limited generalizability to heterogeneous populations, and clinicians' reluctance due to insufficient explainability remain major barriers.

Conclusion: Artificial intelligence in cardiovascular diagnostics holds transformative potential by improving accuracy, reducing interobserver variability, and expanding access in resource-limited settings. However, its consolidation into routine practice requires robust multicenter validations, seamless interoperability with clinical workflows, and strengthened explainability, prerequisites for incorporation into clinical guidelines and precision medicine strategies.

Objective: There are limited data on the prevalence and prognostic impact of significant valvular heart disease in patients with wild-type transthyretin cardiac amyloidosis (ATTRwt). The aim of this study was to describe the prevalence of aortic stenosis (AS), mitral regurgitation (MR), and tricuspid regurgitation (TR) in this population and, secondarily, to evaluate their impact on survival.

Methods: This was a retrospective, single-center cohort study including patients diagnosed with ATTRwt between 2011 and 2024. We calculated the prevalence of each significant valvular heart disease, and Kaplan-Meier survival curves were generated to estimate two-year all-cause mortality, stratified according to the presence or absence of each significant valvular disease. Finally, a multivariable Cox regression was performed to assess their association with survival.

Results: We included 154 patients, with a mean age of 81 (±7) years; 85% (n=131) were male. Significant TR was the most prevalent valvular disease (27%, n=41), followed by significant MR (20%, n=30) and AS (13%, n=20). Patients with significant TR had a higher incidence of all-cause mortality compared to those without significant TR (41% vs. 16%, log-rank test, p=0.0007), whereas no differences were observed between patients with and without significant AS or MR. In multivariable Cox models, significant TR was independently associated with higher mortality, regardless of age, the presence of other valvular diseases, and NT-proBNP levels.

Conclusions: Significant TR was the most prevalent valvular disease in patients with ATTRwt and was associated with lower survival in this population.

Aortic arch hypoplasia associated with ventricular septal defect (VSD) is a life-threatening congenital condition that demands early intervention. In low-resource settings, the lack of advanced tools complicates the safe use of selective antegrade cerebral perfusion (SACP) and innovative repair techniques such as interdigitating patch reconstruction. We describe the case of a newborn with severe aortic arch hypoplasia and a large perimembranous VSD who underwent successful one-stage surgical correction. The repair included aortic arch reconstruction using an interdigitating bovine pericardial patch and VSD closure under SACP delivered via direct brachiocephalic trunk cannulation. Despite the challenges of limited monitoring and equipment, the infant had an excellent clinical outcome. This case highlights the feasibility of adapting high-complexity cardiac techniques in resource-limited environments when surgical fundamentals and teamwork are prioritized. With strategic planning, multidisciplinary coordination, and adherence to evidence-based principles, successful single-stage repair of complex congenital heart disease is achievable even in under-resourced settings.

Objective: To describe the process of implementing a congenital heart surgery database at the National Cardiovascular Institute (INCOR) in Peru, adapted to the standardized nomenclature of the Society of Thoracic Surgeons, and to present clinical-surgical outcomes in terms of morbidity and mortality within the framework of comprehensive multidisciplinary care.

Materials and methods: A prospective observational study was conducted in three phases: feasibility, database construction, and prospective data collection. Variables were adapted to the institutional context, and the process included a pilot test, strategic planning, multidisciplinary training, role assignment, monitoring, and periodic statistical analysis.

Results: A total of 500 consecutive patients were registered between May 2022 and July 2023. Septal defects were the most common surgical indication. The most frequent complications included cardiac dysfunction and arrhythmias. In-hospital mortality was 7.6%. The database incorporated preoperative nutritional and dental assessments. Although 27.2% of the forms were fully completed, the remainder showed limitations such as missing data and the need for additional verification of information across modules.

Conclusion: The implementation of a congenital heart surgery registry in Peru is feasible even in a resource-limited setting. This system allows the identification of critical areas for improving care and optimizing clinical outcomes, establishing a foundation for future quality improvement initiatives.

Objectives: To describe the frequency of postoperative acute kidney injury (AKI) following cardiac surgery and to analyse risk factors for its development.

Materials and methods: We conducted an observational analytical cohort study using prospective data from adult patients who underwent cardiac surgery between 2003 and 2023 at a high-complexity centre in Argentina. AKI was defined according to KDIGO criteria. Risk factors were assessed using logistic regression.

Results: A total of 13,215 patients were analysed, with a mean age of 64 years; most were men (75.7%). The frequency of AKI was 7.3%, with an in-hospital mortality of 4.7%. Independent risk factors included advanced age (OR: 1.05, p<0.001), urgent surgery (OR: 2.87, p<0.001), cardiopulmonary bypass (OR: 1.41, p<0.001), and comorbidities such as chronic obstructive pulmonary disease and preoperative anaemia. Asymptomatic status prior to surgery was identified as a protective factor.

Conclusions: The frequency of postoperative AKI is comparable to international registries. The main predictors of risk were age, surgical urgency, and use of cardiopulmonary bypass. Identifying risk factors can improve perioperative prevention and management in cardiac surgery.

Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy by significantly improving long-term outcomes across multiple malignancies. Despite their benefits, ICIs can lead to immune-related adverse events, including rare but severe cardiovascular toxicity such as myocarditis, which can be life-threatening. This comprehensive review aims to explore and discuss the mechanisms, clinical presentation, diagnostic challenges, and management strategies of ICI-induced myocarditis, emphasizing the need for early detection and timely intervention. As the use of ICIs continues to expand, further research is essential to fully elucidate the underlying mechanisms and optimize therapeutic strategies to mitigate this potentially fatal complication while maintaining the efficacy of cancer therapy.

Aortic valve disease is a highly prevalent and clinically significant condition in the general population. Cardiac computed tomography (CT) has emerged as a widely available imaging modality that provides high-resolution static and dynamic information, enabling comprehensive evaluation of valve anatomy and function. This technique complements echocardiography and other imaging tools, adding incremental value to clinical decision-making. Its principal applications include identifying the etiology of valvular disease, grading severity, and assessing adjacent structures, all of which are critical for therapeutic planning. This non-systematic review synthesizes the evidence on the role of CT in the assessment of the aortic valve, focusing on aortic stenosis, aortic regurgitation, infective endocarditis, and postoperative evaluation. The current body of evidence underscores the expanding role of CT in the integrated diagnosis and longitudinal management of aortic valve disease.