1. Presented by Grace Diehl & JJ Trout February 25, 2013 Mathur, A.K., Heimbach, J., Steffick, D.E., Sonnenday, C.J., Goodrich, N.P. & Merion, R.M. (2010). Donation after cardiac death liver transplantation: Predictors of outcome. American Journal of Transplantation, 10, 2512-2519. doi: 10.1111/j.1600-6143.2010.03292.x Donation after Cardiac Death Liver Transplantation: Predictors of Outcome http://www.guardian.co.uk/science/2011/oct/12/skin-liver-cells-inherited-disease

2. Presentation Outline Background Information Purpose & Goals of the Study Materials and Methods Results Conclusions Significance and Future Directions of the Research

3. Background Information Scientific Registry of Transplant Recipients (1987) (SRTR) National database of transplant statistics Evaluation/Research/Policy of solid organ transplants Collect: OPTN (Organ Procurement and Transplantation Network) & OPOs (Organ Procurement Organizations) 2011 Report: 5,805 adult liver transplants (OPTN/SRTR) 5,531 brain dead; 266 DCD; 188 live Waitlist: ~14,000 Disease: Cholestatic (bile cannot flow) Metabolic/Malignancy…

4. Background Information Continued Surgical Plan (University Health Network, 2012) The liver would be transected with a plane that divides the intrahepatic left hepatic vein. Parenchymal transection would be performed until the intrahepatic left hepatic vein is reached. A standard IV tubing would be inserted into the main portal vein, and the hepatic artery and portal vein would be clamped. The vena cava would then be cross-clamped above and below the liver. While the left hepatic vein is divided, ice cold HTK solution would be perfused through the IV tubing. Sterile ice would also be placed around the liver remnant. The confluence of the middle/left hepatic vein would be divided at the cava, and then anastomosed to the divided left hepatic vein. A Roux-en-Y hepatico-jejunostomy will be performed to reconstruct the biliary circulation. http://pie.med.utoronto.ca/TVASurg/TVASurg_content/surg/TL_coldPerfusion.html

5. Background Information Continued Terms: Ischemic cholangiopathy/ischemic biliary strictures Damage to bile ducts caused by inadequate blood flow, specific narrowing Cold Ischemia Time (CIT) Time from devascularization in donor to repurfusion in recipient (Furukawa et al., 1991). Donor Warm Ischemia Time (DWIT): Time of cross clamping until cold perfusion is started (Halazun, Al-Mukhtar, Aldouri, Willis, & Ahmad, 2007). Model for End-Stage Liver Disease (MELD): Predictor of death & used for waitlist priority Based on INR (international normalized ratio for prothrombin time, bilirubin, creatinine (Weisner et. al, 2003). 40 or more — 71.3% mortality 30–39 — 52.6% mortality 20–29 — 19.6% mortality 10–19 — 6.0% mortality <9 — 1.9% mortality Known factors of Ischemic cholangiopathy and graft failure from single center studies: Donor weight Donor age Cold Ischemia time (CIT) 6

6. Purpose and Goals of the Study Investigating: Donors after Cardiac Death (DCD) Liver Transplantation Using the Scientific Registry of Transplant Recipients (SRTR) determine risk factors in: Donor Recipient Transplant Better understand post-transplant outcomes including: Graft Failure Re-transplantation Patient Mortality Rates Hypothesis: Factors demonstrated in prior single-center studies associated with ischemic cholangiopathy including donor weight, donor age, and cold ischemia time (CIT) would also be associated with graft failure and posttransplant mortality. ** Cannot calculate ischemic cholangiopathy due to definition/time of onset not uniformly reported

7. Materials and Methods Used SRTR to construct retrospective cohort to determine risk of failure DCD liver transplant recipients Liver-only grafts September 1, 2001 to April 30, 2009 (~7.5 years) 80% greater than 1 year follow up: minimum 182 days Data from Organ Procurement and Transplantation Network (OPTN) Cross reference for validation with the Social Security Death Master File and other data sources for donor and recipient mortality Cross validation is good – increased strength of the study Data on: candidate, recipient, donor demographics, comorbidities, disease progression, clinical risk factors, post- transplant outcomes with graft failure and recipient death

8. Materials and Methods Continued Cumulative Incidence: measure of disease frequency during a period of time Find the competing risk rate of post-DCD transplant outcomes over time Multivariable Cox proportional hazard models Estimate the treatment effect on survival time of an individual after an adjustment for explanatory variables (XLSTAT, 2013) Good model for the study: accounts for death which is heavily censored Determine donor, recipient, transplant predictors of inferior DCD outcomes Separate models for graft failure and posttransplant mortality (1) Graft failure: re-transplantation event or death (the earlier) (2) Mortality: live or die Time-varying covariate: allow for flexibility in the model when re- transplant occurs Time? Was re-transplant necessary because of the graft or something else ? Combined individual covariate effects that had the most clinical impact were tested in both models to create interaction terms All patients had 6 months of follow up: don’t want to include those who died right away, indicator of comorbidity

9. Materials and Methods Continued Donor Variables Age Race BMI Weight Cause of Death Recipient Characteristics Age Race Sex Medical Condition Prior liver transplant Diagnosis Pre-existing malignancy Diabetes Prior Abdominal Surgery Portal Vein Thrombosis Transplant Characteristics Local vs. Shared Donor Partial or Split Liver ABO compatibility DWIT* CIT* *: each form determined by lowess plots of marginale residuals and statistical significance of the covariates in the failure model Fewer than 10% of total data across all variables were missing and indicators were used for missing data

10. Results: Table 1 Demographic & Clinical Characteristics of DCD Transplant Recipient Data of Note: 5% previous liver transplant 20% hospitalized at time of transplant 5% Status 1

11. Results: Table 1 Demographic & Clinical Characteristics of DCD Transplant Donor Data of Note: Average age 35.2 years 2/3 male Average weight 77.3 Kg Traumatic Injury = Cause of Death 2.5% Uncontrolled Transplant Data of Note: Mean CIT 7.5 hours Mean DWIT 16 minutes 60% local

12. Results: Figure 1 Cumulative Incidence of Post-DCD Liver Transplant Outcomes Highest rate of death is during the first year Relisting occurred in 19.9%, median of 73.5 days following transplantation MELD at relisting was 21 (16-29) Majority of retransplants occurred in the first few months following DCD transplantation

13. Results: Table 2 Predictors of Graft Failure Following DCD Liver Transplant Recipient Data of Note: AGE: Recipients >55 26% higher failure than 18-55; <18 = lower graft failure GENDER: Female protective RACE: African Am 38% higher failure vs white DISEASE: Metabolic 2x higher failure than noncholestatic Recipient Data of Note: PRIOR TRANSPLANT: 45% higher failure MELD: MELD > 35 46% higher failure than MELD 15-25 HOSPITALIZATION & LIFE SUPPORT also signficiant indicators Not Status 1

14. Results: Table 2 Predictors of Graft Failure Following DCD Liver Transplant Donor Data of Note: AGE: >50 39-88% higher risk vs 18-50 WEIGHT: >100 56% higher risk than <100 Cause of Death NOT associated Transplant Data of Note: DWIT & CIT independently significant Continuously: each hour = 6% increase fail Categorically: even 6-10h had 64% higher fail vs 10h; 4x risk at 13h. Missing = proxy for longer

15. Results: Figure 2 DWIT Distribution Among 1567 DCD Liver Transplant Recipients 3.8% grafts implanted with warm ischemia times >35 minutes DWIT “threshold effect” at 35 minutes: significantly increased graft failure rates

16. Results: Figure 3 Effect of DWIT on Graft Failure Following DCD Liver Transplant Data of Note: Multivariate COX Regression approach DWIT has significant effect on graft failure (retransplant or death). DWIT of 35 minutes or greater = threshold; 1.8 times higher graft loss vs less than 15 min No sig difference <15 vs 15- 35

17. Results: Table 3 Predictors of Mortality Following DCD Liver Transplantation Older Recipient age (>55): 60% higher mortality rate Retransplantation: 2.4 times higher mortality rate than those with functional grafts Hospitalization: 48% higher risk of dying vs. ambulatory recipients Higher MELD scores not associated with post-transplant mortality Status 1 Medical Emergency not predictive of post-transplant mortality

18. Conclusions Hypothesis was partially supported: predictive indicators of ischemic cholangiopathy on longer term graft failure/mortality in comprehensive study: Donor age, weight, and CIT significant for failure Donor age and CIT significant for mortality (not weight) But no significant interactions Further Conclusions: >1/3 DCD transplants die, or require another transplant 3 years after MELD >35 significant for failure; not mortality Retransplants had higher mortality rate Recipient Race/Disease/Gender/Hospitalization/Age/Life Support/MELD all significant indicators

19. Significance of the Research Possible improved informed consent process of risks associated with specific DCD transplants Transplant surgeons can create better DCD acceptance protocols Provided framework to judge clinical risk of DCD transplants Assist providers in recommendations of DCD transplants to patients based on their individual characteristics, needs and organ availability Selective utilization of DCD liver transplants: grafts from older, heavier donors with long CIT to be used with caution Study is limited: depth and quality of SRTR (OPTN) data Confounding factor – inability to account for variations from DCD liver procurement practices, reducing applicability

20. Future Directions Collection of additional data serial hemodynamic measurements other physiological parameters Identify clinical tools to decrease risk of biliary injury in DCD grafts Modify allocation rules to increase access to retransplantation after failed DCD liver transplants Refine understanding of risk factors of DCD liver transplants http://thinkingfutures.net/wp-content/uploads/2010/10/ future -direction-sign.jpg

21. References Furukawa, H., Todo, S., Imventarza, O., Wu, Y.M., Scotti, C., Day, R., & Starzl, T.E. (1991). Cold ischemia time vs outcome of human liver transplantation using UW solution. Transplant Procedures, 23(1.2), 1550-1551. Halazun, K.J., Al-Mukhtar, A., Aldouri, A., Willis, S., & Ahmad, N. (2007). Warm ischemia in transplantation: search for a consensus definition. Transplant Procedures, 39(5), 1329-1331. OPTN/SRTR (n.d.). OPTN/SRTR 2011 annual data report: Liver. In U.S. Department of Health and Human Services. Retrieved February 20, 2013 from http://srtr.transplant.hrsa.gov/annual_reports/2011/pdf/03_%20liver_12.pdf http://srtr.transplant.hrsa.gov/annual_reports/2011/pdf/03_%20liver_12.pdf Sample, I. (2011, October 12). Skin transformed into liver cells to treat an inherited disease. The Guardian. Retrieved from http://www.guardian.co.uk/science/2011/oct/12/skin- liver-cells-inherited-diseasehttp://www.guardian.co.uk/science/2011/oct/12/skin- liver-cells-inherited-disease SRTR (n.d.). About the SRTR. In SRTR. Retrieved February 20, 2013 from http://www.srtr.org/who.aspx http://www.srtr.org/who.aspx University Health Network (n.d.). In-situ cold perfusion. In Toronto Video Atlas of Liver, Pancreas, and Transplant Surgery. Retrieved February 20, 2013 from http://pie.med.utoronto.ca/TVASurg/TVASurg_content/surg/TL_coldPerfusion.html http://pie.med.utoronto.ca/TVASurg/TVASurg_content/surg/TL_coldPerfusion.html Wiesner, R., Edwards, E., Freeman, R., Harper, A., Kim, R., Kamath, P., Kremers, W.,…Krom, R. (2003). Model for end-stage liver disease (MELD) and allocation of donor livers. Gastroenterology, 124(1), 91-96. XLSTAT (n.d.) Cox proportional hazards models. Retrieved February 11, 2013 from http://www.xlstat.com/en/products-solutions/feature/cox-proportional-hazards- models.html

22. Questions?