The cardiovascular medical profession is undeniably marked by constant evolutions and breakthroughs. One such paradigm-shifting development we’re observing is in a necessary domain of surgical patient care: Red Blood Cell (RBC) transfusion.
Today, we’re looking at a landscape where blood donations and supplies are dwindling, pressing us to accurately predict transfusion likelihood. Our traditional go-to, Maximum Surgical Blood Order Schedules (MSBOS), does not account for individualized factors such as preoperative hemoglobin level, total body blood volume, comedications, and patient-specific risk factors.
Enter the new frontier: AI and machine learning technologies. These tools offer a refined lens through which we can assess transfusion probability, incorporating individualized elements like comorbidities, lab parameters, use of oral anticoagulation, ASA score, surgeon’s ID, and implemented blood-saving measures.
Imagine our profession moving towards a framework where predictive models enable us to deliver truly personalized medicine. In the realm of perfusion, this isn’t merely an intellectual curiosity but a potential game-changer. These models can significantly contribute to enhanced quality assurance, marked reduction of blood loss, considerable cost reduction, and improved patient safety.
Moreover, predictive models aren’t just about the ‘during’ and ‘after’ of surgical procedures. These models empower us with the capability to form robust blood management strategies well before the patient is on the table. Much like having detailed navigation on a challenging journey, these tools aid us in minimizing unexpected surprises.
As we move further into an era where personalized medicine is becoming the norm rather than the exception, the integration of AI and machine learning for predicting RBC transfusions could be a game-changer. Think of it as a fusion of our clinical expertise with smart technologies, enabling us to offer well-crafted, personalized, and efficient perfusion care.
The future points us to a world where blood transfusions aren’t just a crucial medical intervention but a calculated, personalized approach, honed by AI and predictive analytics. As we continually strive for better patient outcomes and streamlined practices, the intersection of AI and perfusion science offers us an exciting trajectory. The road ahead promises not just evolution but a revolution in our profession.
Reference link: https://doi.org/10.1016/j.tracli.2022.09.063
- A. Greinacher
- R. Goudie
- A.A. Klein
- A.J. London