AI Model for Liver Transplant Could Cut Costs and Boost Success Rates, Stanford Study Finds
Stanford study says AI Model for Liver Transplant that might cut costs and improve Liver Transplants!
There are more candidates on the waitlist for a liver transplant than there are available organs, yet about half the time a match is found with a donor who dies after cardiac arrest following the removal of life support, the transplant must be canceled. The time between the removal of life support and death shouldn’t exceed 30-45 minutes for these types of organ donations (donation after circulation death). The surgeons will often reject the liver because of the increased risk of complications to the receiver.
Recently, there was a new study led by the researchers of Stanford University which has shown that a machine learning model could make liver transplants more successful while also reducing costs and efforts.
To solve this problem, researchers developed a machine learning model that can predict how long it will take for a donor to pass away after life support is withdrawn. This helps doctors decide in advance whether the organ is likely to be usable.
The results are promising. The model was able to reduce “futile procurements” by about 60%. These are situations where doctors prepare for transplant surgery, but later have to cancel because the organ cannot be used.
Kazunari Sasaki, MD, Clinical Professor of abdominal transplantation and senior author on the study, said that, “By identifying when an organ is likely to be useful before any preparations for surgery have started, this model could make the transplant process more efficient”. She also mentioned, “It also has the potential to allow more candidates who need an organ transplant to receive one”.
Sasaki said “The number of liver transplants keeps going up because of donations after circulatory death, and the waitlist is getting smaller. In the future, it might be possible for everyone who needs a liver transplant to get one from a deceased donor”.
A third type of liver transplantation, living donation, involves removing part of a healthy person’s liver to transplant, which is possible because the liver can regenerate. While “it’s a beautiful story,” Sasaki said of living donation, “any major surgery is not without risk to the healthy donor”.
By avoiding such cases, hospitals can save time, reduce costs, and make better use of available organs. The model also performed better than surgeons in predicting whether the donor would pass away within the required time.
Experts say this technology could help more patients receive life-saving transplants. It may also reduce stress on medical teams and improve overall efficiency in transplant centers.
The study was published in The Lancet Digital Health. Researchers believe that in the future, similar models could also be used for other organ transplants like heart and lungs.
