Rethinking Cardiopulmonary Bypass Management in The Digital Health Era

Area of Science:

• Cardiovascular Surgery
• Medical Technology
• Digital Health

Background:

• Minimally invasive and robotic cardiac surgery aim to reduce trauma and improve recovery.
• These techniques often necessitate longer cardiopulmonary bypass (CPB) and aortic cross-clamp times compared to conventional sternotomy.
• Prolonged CPB duration is linked to increased postoperative morbidity and mortality, especially in vulnerable patients.

Purpose of the Study:

• To address the paradox of less invasive access versus prolonged extracorporeal support in cardiac surgery.
• To explore how digital health innovations can mitigate risks associated with extended CPB times.
• To propose a framework for precision perfusion management in cardiac surgery.

Main Methods:

• Review of contemporary evidence from randomized and observational studies on minimally invasive/robotic cardiac surgery outcomes.
• Analysis of advances in digital health for intraoperative perfusion management, including high-frequency data acquisition and AI predictive models.
• Conceptualization of integrating digital data streams and patient-specific digital twins for dynamic perfusion monitoring and control.

Main Results:

• Minimally invasive and robotic procedures show comparable or improved survival and functional recovery.
• Extended CPB and aortic clamp times are associated with higher risks of renal dysfunction, neurological events, and systemic inflammation.
• Digital health tools offer potential for early detection of perfusion imbalance and metabolic distress.

Conclusions:

• Precision perfusion, enabled by digital health and AI, can potentially reconcile the benefits of minimal invasiveness with physiological safety.
• Converting CPB duration into a digitally monitored, optimizable variable is a key future direction.
• Further multicenter validation and standardization of digital perfusion frameworks are necessary for real-world implementation.