Kpodonu, Jacques

Abstract Background Artificial intelligence (AI) has emerged as a tool to potentially increase the efficiency and efficacy of cardiovascular care and improve clinical outcomes. This study aims to provide an overview of applications of AI in cardiac surgery. Methods A systematic literature search on AI applications in cardiac surgery from inception to February 2024 was conducted. Articles were then filtered based on the inclusion and exclusion criteria and the risk of bias was assessed. Key findings were then summarized. Results A total of 81 studies were found that reported on AI applications in cardiac surgery. There is a rapid rise in studies since 2020. The most popular machine learning technique was random forest ( n = 48), followed by support vector machine ( n = 33), logistic regression ( n = 32), and eXtreme Gradient Boosting ( n = 31). Most of the studies were on adult patients, conducted in China, and involved procedures such as valvular surgery (24.7%), heart transplant (9.4%), coronary revascularization (11.8%), congenital heart disease surgery (3.5%), and aortic dissection repair (2.4%). Regarding evaluation outcomes, 35 studies examined the performance, 26 studies examined clinician outcomes, and 20 studies examined patient outcomes. Conclusion AI was mainly used to predict complications following cardiac surgeries and improve clinicians' decision‐making by providing better preoperative risk assessment, stratification, and prognostication. While the application of AI in cardiac surgery has greatly progressed in the last decade, further studies need to be conducted to verify accuracy and ensure safety before use in clinical practice.

The global burden of paediatric and congenital heart disease (PCHD) is substantial. We propose a novel public health framework with recommendations for developing effective and safe PCHD services in low-income and middle-income countries (LMICs). This framework was created by the Global Initiative for Children’s Surgery Cardiac Surgery working group in collaboration with a group of international rexperts in providing paediatric and congenital cardiac care to patients with CHD and rheumatic heart disease (RHD) in LMICs. Effective and safe PCHD care is inaccessible to many, and there is no consensus on the best approaches to provide meaningful access in resource-limited settings, where it is often needed the most. Considering the high inequity in access to care for CHD and RHD, we aimed to create an actionable framework for health practitioners, policy makers and patients that supports treatment and prevention. It was formulated based on rigorous evaluation of available guidelines and standards of care and builds on a consensus process about the competencies needed at each step of the care continuum. We recommend a tier-based framework for PCHD care integrated within existing health systems. Each level of care is expected to meet minimum benchmarks and ensure high-quality and family centred care. We propose that cardiac surgery capabilities should only be developed at the more advanced levels on hospitals that have an established foundation of cardiology and cardiac surgery services, including screening, diagnostics, inpatient and outpatient care, postoperative care and cardiac catheterisation. This approach requires a quality control system and close collaboration between the different levels of care to facilitate the journey and care of every child with heart disease. This effort was designed to guide readers and leaders in taking action, strengthening capacity, evaluating impact, advancing policy and engaging in partnerships to guide facilities providing PCHD care in LMICs.