Technology-Based Cardiac Rehabilitation and Exercise Capacity in Coronary Artery Disease: An Artificial Intelligence Analysis

I read with great interest the article by Saklica et al. entitled “The Impact of Technology-Based Cardiac Rehabilitation on Exercise Capacity and Adherence in Patients with Coronary Artery Disease: An Artificial Intelligence Analysis,” recently published in Arquivos Brasileiros de Cardiologia. The study addresses an important and timely topic by examining the potential role of technology-supported cardiac rehabilitation programs and exploring the integration of artificial intelligence (AI)–based analyses in the evaluation of rehabilitation outcomes. Considering the persistent global underutilization of cardiac rehabilitation programs, studies exploring innovative and accessible rehabilitation strategies are of clear clinical importance.

One methodological aspect that warrants further consideration is the assessment of exercise capacity. In the present study, functional improvement was evaluated using the incremental shuttle walk test (ISWT). Although the ISWT is a practical and validated field test frequently used in rehabilitation settings, it remains a submaximal and effort-dependent measure. In patients with coronary artery disease, cardiopulmonary exercise testing (CPET) is generally regarded as the reference standard for evaluating exercise capacity because it provides objective physiological parameters such as peak oxygen uptake and ventilatory thresholds. The inclusion of CPET-derived variables could therefore have offered a more comprehensive evaluation of cardiopulmonary adaptations and strengthened the interpretation of the observed improvements in functional capacity.

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