1932

Abstract

The MELD (model for end-stage liver disease) 3.0 score was developed to replace the MELD-Na score that is currently used to prioritize liver allocation for cirrhotic patients awaiting liver transplantation in the United States. The MELD 3.0 calculator includes new inputs from patient sex and serum albumin levels and has new weights for serum sodium, bilirubin, international normalized ratio, and creatinine levels. It is expected that use of MELD 3.0 scores will reduce overall waitlist mortality modestly and improve access for female liver transplant candidates. The utility of MELD 3.0 and PELD (pediatric end-stage liver disease, creatinine) scores for risk stratification in cirrhotic patients undergoing major abdominal surgery, placement of a transjugular intrahepatic portosystemic shunt, and other interventions requires further study. This article reviews the background of the MELD score and the rationale to create MELD 3.0 as well as potential implications of using this newer risk stratification tool in clinical practice.

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2024-01-29
2024-04-30
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Literature Cited

  1. 1.
    Freeman RB, Edwards EB. 2000. Liver transplant waiting time does not correlate with waiting list mortality: implications for liver allocation policy. Liver Transplant. 6:554352
    [Google Scholar]
  2. 2.
    Child CG, Turcotte JG. 1964. Surgery and portal hypertension. Major Probl. Clin. Surg. 1:185
    [Google Scholar]
  3. 3.
    Inst. Med. Comm. Organ Procure. Transplant. Policy 1999. Analysis of waiting times. Organ Procurement and Transplantation: Assessing Current Policies and the Potential Impact of the DHHS Final Rule5778. Washington, DC: Natl. Acad. Press
    [Google Scholar]
  4. 4.
    Malinchoc M, Kamath PS, Gordon FD et al. 2000. A model to predict poor survival in patients undergoing transjugular intrahepatic portosystemic shunts. Hepatology 31:486471
    [Google Scholar]
  5. 5.
    Kamath P, Wiesner RH, Malinchoc M et al. 2001. A model to predict survival in patients with end-stage liver disease. Hepatology 33:246470
    [Google Scholar]
  6. 6.
    Wiesner R, Edwards E, Freeman R et al. 2003. Model for end-stage liver disease (MELD) and allocation of donor livers. Gastroenterology 124:19196
    [Google Scholar]
  7. 7.
    Heuman DM, Abou-Assi SG, Habib A et al. 2004. Persistent ascites and low serum sodium identify patients with cirrhosis and low MELD scores who are at high risk for early death. Hepatology 40:480210
    [Google Scholar]
  8. 8.
    Ray Kim W, Biggins SW, Kremers WK et al. 2008. Hyponatremia and mortality among patients on the liver-transplant waiting list. N. Engl. J. Med. 359:101826
    [Google Scholar]
  9. 9.
    Barches NR, Lee TC, Udell IW et al. 2006. The pediatric end-stage liver disease (PELD) model as a predictor of survival benefit and posttransplant survival in pediatric liver transplant recipients. Liver Transpl. 12:347580
    [Google Scholar]
  10. 10.
    Freeman RB, Wiesner RH, Edwards E et al. 2004. Results of the first year of the new liver allocation plan. Liver Transplant. 10:1715
    [Google Scholar]
  11. 11.
    Merion RM, Schaubel DE, Dykstra DM et al. 2005. The survival benefit of liver transplantation. Am. J. Transplant. 5:230713
    [Google Scholar]
  12. 12.
    Schaubel DE, Guidinger MK, Biggins SW et al. 2009. Survival benefit-based deceased-donor liver allocation. Am. J. Transplant. 9:4 Pt. 297081
    [Google Scholar]
  13. 13.
    Adler JT, Dong N, Markmann JF et al. 2015. Role of patient factors and practice patterns in determining access to liver waitlist. Am. J. Transplant. 15:7183642
    [Google Scholar]
  14. 14.
    Yeh H, Smoot E, Schoenfeld DA et al. 2011. Geographic inequity in access to livers for transplantation. Transplantation 91:447986
    [Google Scholar]
  15. 15.
    Massie AB, Chow EKH, Wickliffe CE et al. 2015. Early changes in liver distribution following implementation of Share 35. Am. J. Transplant. 15:365967
    [Google Scholar]
  16. 16.
    Sharma P, Schaubel DE, Goodrich NP et al. 2015. Serum sodium and survival benefit of liver transplantation. Liver Transplant. 21:3308
    [Google Scholar]
  17. 17.
    Nagai S, Chau LC, Schilke RE et al. 2018. Effects of allocating livers for transplantation based on model for end-stage liver disease-sodium scores on patient outcomes. Gastroenterology 155:5145162
    [Google Scholar]
  18. 18.
    Kim WR, Lake JR, Smith JM et al. 2019. OPTN/SRTR 2017 Annual data report: liver. Am. J. Transplant. 19:184283
    [Google Scholar]
  19. 19.
    Nagai S, Ivanics T, Kitajima T et al. 2022. Disparities in the effects of acuity circle-based liver allocation on waitlist and transplant practice between centers. Transplant. Direct 8:10e1356
    [Google Scholar]
  20. 20.
    Karp SJ. 2021. Acuity circles—higher cost for fewer transplants?. JAMA Surg. 156:111058
    [Google Scholar]
  21. 21.
    Asrani SK, Jennings LW, Kim W et al. 2019. MELD-GRAIL-Na: glomerular filtration rate and mortality on liver-transplant waiting list. Hepatology 71:5176674
    [Google Scholar]
  22. 22.
    Godfrey EL, Malik TH, Lai JC et al. 2019. The decreasing predictive power of MELD in an era of changing etiology of liver disease. Am. J. Transplant. 19:123299307
    [Google Scholar]
  23. 23.
    Locke JE, Shelton BA, Olthoff KM et al. 2020. Quantifying sex-based disparities in liver allocation. JAMA Surg. 155:7e201129
    [Google Scholar]
  24. 24.
    Allen AM, Heimbach JK, Larson JJ et al. 2018. Reduced access to liver transplantation in women: role of height, MELD exception scores, and renal function underestimation. Transplantation 102:10171016
    [Google Scholar]
  25. 25.
    Lai JC, Covinsky KE, Dodge JL et al. 2017. Development of a novel frailty index to predict mortality in patients with end-stage liver disease. Hepatology 66:256474
    [Google Scholar]
  26. 26.
    Kim WR, Mannalithara A, Heimbach JK et al. 2021. MELD 3.0: the model for end-stage liver disease updated for the modern era. Gastroenterology 161:618871895.e4
    [Google Scholar]
  27. 27.
    Levey AS, Stevens LA, Schmid CH et al. 2009. A new equation to estimate glomerular filtration rate. Ann. Intern. Med. 150:960412
    [Google Scholar]
  28. 28.
    Shaffi K, Uhlig K, Perrone RD et al. 2014. Performance of creatinine-based GFR estimating equations in solid-organ transplant recipients. Am. J. Kidney Dis. 63:6100718
    [Google Scholar]
  29. 29.
    Moylan CA, Brady CW, Johnson JL et al. 2008. Disparities in liver transplantation before and after introduction of the MELD score. JAMA 300:20237178
    [Google Scholar]
  30. 30.
    Mazumder NR, Simpson D, Atiemo K et al. 2021. Black patients with cirrhosis have higher mortality and lower transplant rates: results from a metropolitan cohort study. Hepatology 74:292636
    [Google Scholar]
  31. 31.
    Gutiérrez OM, Sang Y, Grams ME et al. 2022. Association of estimated GFR calculated using race-free equations with kidney failure and mortality by black versus non-black race. JAMA 327:23230616
    [Google Scholar]
  32. 32.
    Cullaro G, Sarkar M, Lai JC et al. 2018. Sex-based disparities in delisting for being “too sick” for liver transplantation. Am. J. Transplant. 18:121419
    [Google Scholar]
  33. 33.
    Lai JC, Terrault NA, Vittinghoff E et al. 2010. Height contributes to the gender difference in wait-list mortality under the MELD-based liver allocation system. Am. J. Transplant. 10:12265964
    [Google Scholar]
  34. 34.
    Mazumder NR, Celaj S, Atiemo K et al. 2020. Liver-related mortality is similar among men and women with cirrhosis. J. Hepatol. 73:5107281
    [Google Scholar]
  35. 35.
    Bernardi M, Angeli P, Claria J et al. 2020. Albumin in decompensated cirrhosis: new concepts and perspectives. Gut 69:6112738
    [Google Scholar]
  36. 36.
    Biggins SW, Angeli P, Garcia-Tsao G et al. 2021. Diagnosis, evaluation, and management of ascites, spontaneous bacterial peritonitis and hepatorenal syndrome: 2021 practice guidance by the American Association for the Study of Liver Diseases. Hepatology 74:2101448
    [Google Scholar]
  37. 37.
    Angeli P, Bernardi M, Villanueva C et al. 2018. EASL clinical practice guidelines for the management of patients with decompensated cirrhosis. J. Hepatol. 69:240660
    [Google Scholar]
  38. 38.
    Atiemo K, Skaro A, Maddur H et al. 2017. Mortality risk factors among patients with cirrhosis and a low model for end-stage liver disease sodium score (≤15): an analysis of liver transplant allocation policy using aggregated electronic health record data. Am. J. Transplant. 17:9241019
    [Google Scholar]
  39. 39.
    Myers RP, Tandon P, Ney M et al. 2014. Validation of the five-variable Model for End-stage Liver Disease (5vMELD) for prediction of mortality on the liver transplant waiting list. Liver Int. 34:8117683
    [Google Scholar]
  40. 40.
    Mulligan DC, Hirose R. 2014. OPTN/UNOS Liver and Intestinal Organ Transplantation Committee report to the Board of Directors Nov. 12–13 St. Louis, MO: https://optn.transplant.hrsa.gov/media/1301/liver_boardreport_20141120.pdf
  41. 42.
    Yang J, Park J-B, Shim JH et al. 2023. Validation of the Model for End-Stage Liver Disease 3.0 in Korean patients on the liver transplant waiting list. Clin. Gastroenterol. Hepatol. In press. https://doi.org/10.1016/j.cgh.2023.01.020
    [Google Scholar]
  42. 43.
    Tarlow BD, Kim WR, Mannalithara A et al. 2022. Mortality in patients with end-stage liver disease above model for end-stage liver disease 3.0 of 40. Hepatology 77:385161
    [Google Scholar]
  43. 44.
    Caraceni P, Riggio O, Angeli P et al. 2018. Long-term albumin administration in decompensated cirrhosis (ANSWER): an open-label randomised trial. Lancet 391:10138241729
    [Google Scholar]
  44. 45.
    China L, Freemantle N, Forrest E et al. 2021. A randomized trial of albumin infusions in hospitalized patients with cirrhosis. N. Engl. J. Med. 384:980817
    [Google Scholar]
  45. 46.
    Kwong AJ, Ebel NH, Kim WR et al. 2022. OPTN/SRTR 2020 annual data report: liver. Am. J. Transplant. 22:S2204309
    [Google Scholar]
  46. 47.
    Trotter JF, Osgood MJ. 2004. MELD scores of liver transplant recipients according to size of waiting list. JAMA 291:151871
    [Google Scholar]
  47. 48.
    Yi Z, Mayorga ME, Orman ES et al. 2017. Trends in characteristics of patients listed for liver transplantation will lead to higher rates of waitlist removal due to clinical deterioration. Transplantation 101:10236874
    [Google Scholar]
  48. 49.
    Kwong AJ, Zhang KY, Ebel N et al. 2022. MELD 3.0 predicts waitlist mortality risk in adolescent liver transplant registrants. Hepatology 76:S11718
    [Google Scholar]
  49. 50.
    Peng CY, Chien RN, Liaw YF. 2012. Hepatitis B virus-related decompensated liver cirrhosis: benefits of antiviral therapy. J. Hepatol. 57:244250
    [Google Scholar]
  50. 51.
    Liaw YF, Raptopoulou-Gigi M, Cheinquer H et al. 2011. Efficacy and safety of entecavir versus adefovir in chronic hepatitis B patients with hepatic decompensation: a randomized, open-label study. Hepatology 54:191100
    [Google Scholar]
  51. 52.
    Dunn W, Jamil LH, Brown LS et al. 2005. MELD accurately predicts mortality in patients with alcoholic hepatitis. Hepatology 41:235358
    [Google Scholar]
  52. 53.
    Jeong R, Lee YS, Sohn C et al. 2015. Model for end-stage liver disease score as a predictor of short-term outcome in patients with drug-induced liver injury. Scand. J. Gastroenterol. 50:443946
    [Google Scholar]
  53. 54.
    Parikh ND, Singal AG. 2016. Model for end-stage liver disease exception points for treatment-responsive hepatocellular carcinoma. Clin. Liver Dis. 7:597100
    [Google Scholar]
  54. 55.
    Cucchetti A, Ercolani G, Vivarelli M et al. 2006. Impact of model for end-stage liver disease (MELD) score on prognosis after hepatectomy for hepatocellular carcinoma on cirrhosis. Liver Transplant. 12:696671
    [Google Scholar]
  55. 56.
    Amitrano L, Guardascione MA, Bennato R et al. 2005. MELD score and hepatocellular carcinoma identify patients at different risk of short-term mortality among cirrhotics bleeding from esophageal varices. J. Hepatol. 42:682025
    [Google Scholar]
  56. 57.
    Ghabril M, Gu J, Yoder L et al. 2019. Development and validation of a model consisting of comorbidity burden to calculate risk of death within 6 months for patients with suspected drug-induced liver injury. Gastroenterology 157:5124552.e3
    [Google Scholar]
  57. 58.
    Hayashi PH, Rockey DC, Fontana RJ et al. 2017. Death and liver transplantation within 2 years of onset of drug-induced liver injury. Hepatology 66:4127585
    [Google Scholar]
  58. 59.
    Koch DG, Tillman H, Durkalski V et al. 2016. Development of a model to predict transplant-free survival of patients with acute liver failure. Clin. Gastroenterol. Hepatol. 14:81199206.e2
    [Google Scholar]
  59. 60.
    Sarmast N, Ogola GO, Kouznetsova M et al. 2020. Model for End-Stage Liver Disease–Lactate and prediction of inpatient mortality in patients with chronic liver disease. Hepatology 72:5174757
    [Google Scholar]
  60. 61.
    Mahmud N, Asrani SK, Kaplan DE et al. 2021. The predictive role of MELD-Lactate and lactate clearance for in-hospital mortality among a national cirrhosis cohort. Liver Transplant. 27:217789
    [Google Scholar]
  61. 62.
    Montano-Loza AJ, Duarte-Rojo A, Meza-Junco J et al. 2015. Inclusion of sarcopenia within MELD (MELD-Sarcopenia) and the prediction of mortality in patients with cirrhosis. Clin. Transl. Gastroenterol. 6:7e102
    [Google Scholar]
  62. 63.
    Zipprich A, Kuss O, Rogowski S et al. 2010. Incorporating indocyanin green clearance into the Model for End Stage Liver Disease (MELD-ICG) improves prognostic accuracy in intermediate to advanced cirrhosis. Gut 59:796368
    [Google Scholar]
  63. 64.
    Bambha K, Kim WR, Kremers WK et al. 2004. Predicting survival among patients listed for liver transplantation: an assessment of serial MELD measurements. Am. J. Transplant. 4:111798804
    [Google Scholar]
  64. 65.
    Cholankeril G, Li AA, Dennis BB et al. 2019. Pre-operative Delta-MELD is an independent predictor of higher mortality following liver transplantation. Sci. Rep. 9:18312
    [Google Scholar]
  65. 66.
    Bayona Molano MDP, Barrera Gutierrez JC, Landinez G et al. 2022. Updates on the model for end-stage liver disease score and impact on the liver transplant waiting list: a narrative review. J. Vasc. Interv. Radiol. 34:333743
    [Google Scholar]
  66. 67.
    Boike JR, Mazumder NR, Kolli KP et al. 2021. Outcomes after TIPS for ascites and variceal bleeding in a contemporary era—an ALTA group study. Am. J. Gastroenterol. 116:10207988
    [Google Scholar]
  67. 68.
    Bettinger D, Sturm L, Pfaff L et al. 2021. Refining prediction of survival after TIPS with the novel Freiburg index of post-TIPS survival. J. Hepatol. 74:6136272
    [Google Scholar]
  68. 69.
    Mahmud N, Fricker Z, Panchal S et al. 2021. External validation of the VOCAL-Penn cirrhosis surgical risk score in 2 large, independent health systems. Liver Transplant. 27:796170
    [Google Scholar]
  69. 70.
    Song J, Wang X, Yan Y et al. 2023. MELD 3.0 score for predicting survival in patients with cirrhosis after transjugular intrahepatic portosystemic shunt creation. Dig. Dis. Sci. 68:318592
    [Google Scholar]
  70. 71.
    Peng Y, Qi X, Guo X. 2016. Child-Pugh versus MELD score for the assessment of prognosis in liver cirrhosis. Medicine 95:8e2877
    [Google Scholar]
  71. 72.
    Ahn JC, Connell A, Simonetto DA et al. 2021. Application of artificial intelligence for the diagnosis and treatment of liver diseases. Hepatology 73:6254663
    [Google Scholar]
  72. 73.
    Ahn JC, Shah VH. 2020. Model to predict progression of liver disease in heavy drinkers is useful today and supports the future of deep learning. Clin. Gastroenterol. Hepatol. 18:10217678
    [Google Scholar]
  73. 74.
    Park SH, Mazumder NR, Mehrotra S et al. 2021. Artificial intelligence-related literature in transplantation: a practical guide. Transplantation 105:47048
    [Google Scholar]
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