Dr Lim reviews key findings from abstracts at The Liver Meeting 2022 pertaining to liver transplantation.

Nicholas Lim, MD, is a transplant hepatologist and an assistant professor of Medicine with the Division of Gastroenterology Hepatology and Nutrition for the University of Minnesota Medical School.

TRANSCRIPT:

Hi there. My name is Nicholas Lim. I'm a transplant hepatologist at the University of Minnesota. I was at The Liver Meeting in Washington, DC and just got a few, I guess take-home points to talk about what I learned there.

So I think, number one, it was great to be back in person. I think it was a lot better for learning, definitely better for networking and socializing as well.

There are 4 abstracts that I thought were definitely notable from in the liver transplantation field. From the liver transplant plenary session there was “not all MELD scores are created equal.” MELD driven by creatinine has a lower intention to treat survival compared to MELD driven by total bilirubin and/or INR.

This was presented by Craig Rosenstengle who's a GI Fellow with Baylor in Dallas. Basically, as you guys know, the MELD score is something that we use to determine the severity of liver disease and to help us place patients on the liver transplant waiting list. It's made up of 4 lab values—total bilirubin, INR, and creatinine, as well as sodium. The question posed in this study was whether one of these lab values was more important than the other when it came to predicting death.

Baylor used the SRTR database and they use a machine learning technique called K-means clustering to create 3 groups—one where their MELD score's predominantly made up of serum creatinine, one with INR, and one with bilirubin. And what they found was that 1-year survival was actually worse in the MELD creatinine group compared to the other groups. And they also found that this was actually affecting female patients worse than it did male patients as well. So I think in these patients where MELD scores that are predominantly driven by serum creatinine, maybe we should be monitoring these patients a little bit more closely. And this actually, in fact, persisted even when these patients' serum creatinine improved as well.

The next abstract was called DYNAMELD: Accurate, Equitable Modeling of End-Stage Liver Disease. I actually really enjoyed this particular abstract. This was presented by a computer science student, a PhD student called Michael Cooper from the University of Toronto. Basically what they did here was they used machine-based deep learning techniques to create this nonlinear survival analysis model to help predict weightless mortality. They used 342 variables and what they found was that their model, I guess unsurprisingly, was better at predicting 90-day mortality than MELD-sodium and the upcoming MELD 3.0, which is what we're using at the moment to allocate livers. And these, interesting to note, are linear models that we're using when it comes to liver allocation.

They were able to validate their DYNAMELD model in 2 ways. The presentation was actually quite entertaining and it really showed off the potential of using AI in medicine or in hepatology and really showed us how we might be able to use this in the future to look at our patients better.

The next abstract was entitled Early Outcomes and Hospital Resource Utilization After Liver Transplantation: Impact of Normothermic Mechanical Perfusion in a High Volume US DCD Liver Transplant Center. This particular abstract was presented by Michelle Nguyen; she's a transplant surgeon at the Mayo Clinic in Arizona.

The background to this is that FDA approved this normothermic profusion device. What they wanted to do at the Mayo Clinic was to find out if this machine could help them utilize DCD livers better while maintaining good clinical outcomes. The Mayo Clinic in Arizona is actually one of the largest DCD centers in the United States, so this was a good place to actually do this study.

They looked back at the patients that they transplanted with both DBD— donation after brain death livers— as well as DCD livers, donation after cardiac livers, then compared the outcomes between the patients where they used the machine to the patients where they did not use this machine. The take-home was really that they actually got really good outcomes when they were using the machine. Specifically, they had lower rates of early allograft dysfunction, particularly in the DCD liver groups. This also led to less transfusions and shorter length of stay as well. That may actually speak to the type of patients they were using as opposed to the machine itself. The actual liver graft survival was also excellent in the short term.

They've been using technology like this in Europe for years with really, really good outcomes. But the big issue is that these machines are not cheap, especially in the United States. So we've got to figure out how the financial aspect of things is going to factor into things.

The final abstract was entitled Pretransplant Terlipressin Treatment for Hepatorenal Syndrome Decreases the Need For Renal Replacement Therapy For Both Pre- and Post-transplants. This was a 12-month follow-up analysis of the CONFIRM trial. This was presented by Ethan Weinberg, a hepatologist at the University of Pennsylvania. This study was like a follow-up analysis of data that was gathered from the CONFIRM study. The CONFIRM study itself was a landmark trial published in the New England Journal of Medicine last year, basically showing that terlipressin, again, a drug that's been used throughout the world for years for HRS, improved clinical outcomes in patients with HRS. And this study was actually instrumental in getting terlipressin approved in the United States.

What they found was that in patients who got terlipressin and then underwent a liver transplant were less likely to go on dialysis before their transplant and they're also less likely to be on dialysis about 12 months after their transplant as well. Why this is important is that basically we know that patients with acute kidney injury at the time of transplant don't do quite as well compared to people who don't have acute kidney injury. Using this medication around the time of transplant, it is going to lead to better outcomes for patients, we think. And also patients who end up on dialysis at the time of transplant don't really do as well at the time of transplant either.

I think the interesting thing here is that at 12 months there were also less patients on dialysis. This, I think, is really important because less people on dialysis at 12 months also potentially means a reduced need for kidney transplantation after liver, which again, also overall leads to increased costs and increased resource utilization in a very sick patient population. We can't draw too many conclusions because this was from data that was done from a different study, but at least from what we know, terlipressin could potentially be very good for our patients in the pre-and posttransplant setting.

Again, it was really good to be there in person and to be able to hear these things and ask questions in real time and hopefully we're going to be able to see more advances in the care of our patients from the lessons that we learned at this meeting.