Until now, surgeons have evaluated the likelihood of a successful heart transplant based on individual risk factors. Now, new research presented at ISHLT 2024 has revealed that artificial intelligence (AI) can help physicians better assess the complex factors impacting patient outcomes and have a significant impact on the heart transplantation process.

Surgeons at the Cleveland Clinic (Cleveland, OH, USA) are developing a decision-support tool for transplant surgeons using a modeling technique known as ‘digital twinning.’ This innovative approach involves creating a digital picture of each transplant recipient to assist physicians in predicting patient outcomes using specific data combinations. The surgical team has established a comprehensive database that incorporates clinical data and test results from all 600 heart recipients and donors since the start of their transplant program.

To further enhance this database, the team is currently sequencing the whole genomes of both the recipients and their donors. Plans are in place to continually update the database with new data gathered from ongoing monitoring of heart recipients, including metrics like heart rate, blood oxygen levels, and biopsy results. The integration of AI with this rich data pool is expected to refine organ allocation systems significantly, enabling more accurate predictions of patient outcomes throughout the transplantation process.

“I think our guidelines will change because we’ll be able to look at combinations of weighted risk factors and how they interplay,” said Eileen Hsich, medical director of the Heart Transplant Program at the Cleveland Clinic. “That work cannot be done manually. Machine learning can provide data we’ve never had before, and it will make a big difference.” 

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