Home
JournalsCollections
For Authors For Reviewers For Editorial Board Members
Article Processing Charges Open Access
Ethics Advertising Policy
Editorial Policy Resource Center
Company Information Contact Us
OPEN ACCESS

The Development and Appraisal of MELD 3.0 in Liver Diseases: Good Things Never Come Easy

  • Gaoyue Guo1,2,#,
  • Wanting Yang1,2,#,
  • Jia Li1,2,
  • Ziyi Yang1,2,
  • Jing Liang3,*  and
  • Chao Sun1,2,* 
Journal of Clinical and Translational Hepatology   2024

doi: 10.14218/JCTH.2024.00303

Received:

Revised:

Accepted:

Published online:

 Author information

Citation: Guo G, Yang W, Li J, Yang Z, Liang J, Sun C. The Development and Appraisal of MELD 3.0 in Liver Diseases: Good Things Never Come Easy. J Clin Transl Hepatol. Published online: Nov 12, 2024. doi: 10.14218/JCTH.2024.00303.

Abstract

Since its proposal, the Model for End-Stage Liver Disease (MELD) score has been employed to predict short-term mortality among patients with chronic liver disease and those awaiting liver transplantation, serving as the primary criterion for organ allocation. However, as the demographic and epidemiological characteristics of chronic liver disease and liver transplantation have evolved, a range of MELD-related scores has emerged, including MELD-Na, iMELD, delta MELD, MELD XI, MELD-LA, and pediatric end-stage liver disease, culminating in the recently proposed MELD 3.0, which builds upon MELD-Na. This study aimed to comprehensively review and summarize relevant studies on MELD 3.0 in various scenarios, assessing its effectiveness in organ allocation, post-transplantation outcomes, and mortality prediction for patients with end-stage liver disease. Our preliminary findings indicate superior predictive performance of MELD 3.0, warranting further in-depth investigations to broaden its clinical implications.

Graphical Abstract

Keywords

MELD 3.0, Liver cirrhosis, Liver transplantation, Organ allocation, Prognostication, Advanced liver disease, MELD-Na

Introduction

Developed by Kamath et al. in 2000, the original MELD score served as a prognostic model incorporating three objective laboratory measures [(creatinine, total bilirubin, and international normalized ratio (INR)], with etiology as the sole subjective indicator. Initially, it aimed to predict short-term prognosis for patients with portal hypertension undergoing transjugular intrahepatic portosystemic shunt (TIPS). Subsequently, it has been broadly applied to evaluate the severity of various pathological conditions in patients with end-stage liver disease and to determine the urgency and prioritization for liver transplantation (LT).1

Although the MELD score has significantly improved health outcomes since its implementation in clinical practice, some inherent limitations should be acknowledged and addressed. These concerns regarding the MELD score are depicted as follows: (1) Serum bilirubin, creatinine, and INR are influenced by the underlying disease status, such as infections, vitamin K deficiency, and the administration of diuretic medications. Therefore, Kamath et al. suggested that to avoid extrahepatic impacts, the MELD score should be utilized under conditions of hemodynamic stabilization and adequate rehydration.2 (2) Using serum creatinine clearance rather than serum creatinine could more accurately reflect biochemical changes related to liver dysfunction. It is highlighted that the average muscle mass is lower in females than in males, indicating more advanced renal dysfunction in females at equivalent creatinine levels.3 (3) Given the effective spread of anti-hepatitis C drugs, the incidence of liver transplants for hepatitis C has dropped dramatically, while the proportion of patients waiting for transplants due to alcohol-associated liver disease (ALD) and metabolic dysfunction-associated steatohepatitis as major etiologies has risen substantially, altering the demographic characteristics of chronic liver disease and the indications for LT.4 (4) The MELD score cannot promptly capture pathophysiological perturbations in patients with complications such as refractory ascites (RA), hepatic encephalopathy, hepatocellular carcinoma, and acute-on-chronic liver failure (ACLF), thus limiting its performance for long-term prognostication. (5) While the MELD score remains a reliable predictor of preoperative mortality in transplant candidates, it has limited utility in predicting post-transplant mortality.5

Collectively, the magnitude of liver disease severity and the allocation of liver transplant resources require more precise, comprehensive, and accurate evaluation to meet escalating healthcare demands and provide tailored treatments for improved prognoses. In this regard, a spectrum of iterative MELD scores has been constructed and is discussed in the following statements.

MELD-related score

Over the past two decades, the MELD score has been continuously modified and developed to generate versatile, relevant models. The generated MELD-related scores are summarized in Table 1.

Table 1

Formula for MELD-related scores

ScoreComponents
MELD9.57*Ln(creatinine) + 3.78*Ln(bilirubin) + 11.20*Ln(INR) + 6.43 (etiology: 0 if cholestatic or alcoholic, 1 otherwise)
MELD-NaMELD +1.32 *(137 − Na) − 0.033 *MELD*(137 − Na)
Delta MELDDifference in MELD scores between last and first admission within 30 days
MELD-XI5.11*Ln(bilirubin) + 11.76*Ln(creatinine) + 9.44
iMELDMELD + 0.3*age − 0.7*Na + 100
MELD-LA5.68*Ln (LA) + 0.64*(MELD) + 2.68
PELD0.480 *Ln (bilirubin) + 1.857*Ln (INR) − 0.687*Ln (albumin) + 0.436 (if the patient is less than one year old), 0.480*Ln (bilirubin) + 1.857*Ln (INR) − 0.687*Ln (albumin) + 0.667 (if the patient has growth failure)
MELD 3.01.33 (if female) + 4.56*Ln(bilirubin) + 0.82*(137 − Na) − 0.24 *(137 - Na) *Ln(bilirubin) + 9.09*Ln(INR) + 11.14*Ln(creatinine) + 1.85*(3.5 − albumin) − 1.83*(3.5 − albumin) *Ln(creatinine) + 6

MELD-Na score

In 2006, Biggins et al.6 proposed the MELD-Na score, an adaptation of the original MELD score that includes serum sodium (Table 2). The Organ Procurement and Transplantation Network (OPTN) formally implemented the MELD-Na score as the standard for liver transplant allocation in 2016, resulting in a notable reduction in mortality rates among patients awaiting LT.7 Subsequent research, including a study by Cristal Brown et al., utilized the largest database of decompensated cirrhotic patients in the U.S., indicating that MELD-Na has a strong predictive value concerning six-month mortality with a C-statistic of 0.83, comparable to its predictive accuracy for 90-day morbidity and mortality.8 An assessment of three-month outcomes for 5,223 patients on the European transplant waiting list indicated that the MELD-Na score demonstrated superior prognostic accuracy.9 The MELD-Na score was also closely linked to post-LT complications, particularly early acute kidney injury,10 and to Accordion Severity Grades, as a MELD-Na score ≥ 25 independently predicted postoperative severe grade complications11 and post-liver transplant mortality. Notably, the majority of studies have shown that MELD-Na significantly enhances predictive performance in patients with lower MELD scores.12 Although the MELD-Na score surpassed the original MELD score in predicting overall mortality in cirrhosis, it was less effective in predicting short-term mortality after TIPS.13,14

Table 2

Characteristics of original MELD, MELD-Na, and MELD 3.0

MELDMELD-NaMELD 3.0
VariablesINR: Total bilirubin; Serum creatinineINR: Total bilirubin; Serum creatinine; Serum sodiumINR: Total bilirubin; Serum creatinine; Serum sodium; Albumin; Sex
Value Range
INRLower limit 1.0Lower limit 1.0Lower limit 1.0
BilirubinLower limit 1.0Lower limit 1.0Lower limit 1.0
CreatinineUpper limit 4.0 mg/dLUpper limit 4.0 mg/dLUpper limit 3.0 mg/dL
Sodium/Upper limit 125 meq/L, Lower limit 137 meq/LUpper limit 125 meq/L, Lower limit 137 meq/L
Albumin//Upper limit 1.5 mg/dL, Lower limit 3.5 mg/dL
Score range6–406–406–40
AdvantagesObjective, continuous scores, inclusion of etiologic and renal function indicatorsRefining the assessment of liver disease severity adding serum sodium levelsAdd albumin and gender to the equation, and address sex-based disparity
DisadvantagesSusceptible to interference from laboratory testing and lack comprehensive evaluation indicators for complicationsThe same as MELDShort application time and further confirmation is needed

Delta MELD score

Merion et al.15 proposed the delta MELD (ΔMELD) score, which indicates temporal changes in the MELD score over a 30-day interval and demonstrated that ΔMELD accurately predicts mortality in patients with end-stage liver disease compared to the original MELD score.16 Furthermore, ΔMELD more accurately predicted survival status in patients awaiting LT, indicating that a ΔMELD increase of >10 correlates with a 1.6-fold increase in mortality risk.17 Another study implied that ΔMELD scores were significantly higher in patients whose cirrhosis was due to alcohol consumption.18

MELD-XI score

The MELD-XI score, adapted for patients on anticoagulant therapy, adjusts for the effects of anticoagulation on INR values19 and provides a more accurate assessment of patients with heart failure.20 This score has shown prognostic relevance in patients undergoing ventricular assist device implantation21,22 and has been validated as a predictor of early mortality following heart transplantation. Patients with elevated MELD-XI scores often present with multi-organ dysfunction, thereby exhibiting a notable correlation with increased long-term and short-term mortality in ICU settings. Moreover, the MELD-XI score is extensively utilized in patients with Fontan-associated liver disease.23 The MELD-XI score also predicts outcomes in post-Fontan surgery patients, helping to determine the need for isolated heart transplantation or combined heart-liver transplantation. Among 596 pediatric Fontan patients undergoing isolated heart transplantation,24 those with elevated MELD-XI scores at heart transplantation showed lower post-transplant mortality, highlighting the score’s implications regarding compromised circulatory function, increased risk of liver disease, and poor outcomes.

iMELD score

Taking into account serum sodium level and age, the iMELD score was formulated.25 Saldaña et al. assessed various prognostic models in 818 LT candidates regarding 90-day survival and demonstrated that the iMELD score represented greater reliability and feasibility.26 In comparisons of three-month, six-month, and one-year mortality rates in patients with cirrhosis, iMELD outperformed both MELD and MELD-Na scores.27,28 Additionally, in evaluations of three-month and six-month prognosis in HBV-ACLF patients, iMELD showed better predictive value compared to MELD and MELD-Na; similarly, a prospective cohort study involving Chinese HBV-ACLF patients demonstrated that iMELD displayed the highest area under the curve (AUC) for predicting mortality at both three months and five years.29 In cases of ACLF resulting from intensive hepatic injury, iMELD proved to be the best indicator concerning 28-day mortality with the highest AUC (0.787), although Chronic Liver Failure Consortium (CLIF-C)-ACLF may be more appropriate for ACLF triggered by extrahepatic factors.30

MELD-LA score

A positive correlation between serum lactate levels and MELD scores led to the development of the MELD-LA score,31 which demonstrated good predictive performance regarding short-term prognosis following LT. Meanwhile, a large-scale study indicated that MELD-LA was better at predicting mortality and sepsis in the context of CLD32 and demonstrated strong predictive ability for variceal bleeding in cirrhosis compared to MELD.33 The MELD-LA effectively predicted short-term prognosis in critically ill patients with cirrhosis, with an AUC of 0.808 for 15-day mortality.34 Stratification by cirrhosis etiologies, such as alcohol and viral hepatitis (B and C), improved the score’s prognostic accuracy.

Pediatric end-stage liver disease (PELD) score

The PELD score applies to children under 12, estimating the severity and prognosis of chronic liver disease in this age group. It incorporates five objective indicators: age, serum albumin, INR, bilirubin levels, and growth status.35 The PELD score not only serves as a primary standard for organ allocation in pediatric liver transplantation but also predicts mortality among infants with end-stage liver disease awaiting LT.36,37 However, it is unsuitable for children receiving specific treatments like artificial liver therapy, which can significantly alter serum bilirubin/albumin levels and INR. An elevated PELD score increases the risk of post-transplant mortality, and children with biliary atresia exhibit a higher mortality risk than those with other chronic liver diseases.38 Additionally, a high PELD score is associated with increased postoperative AKI mortality in pediatric patients.39

MELD 3.0 score

Recently, Stanford University School of Medicine and Mayo Clinic refined the MELD 3.0 score to better reflect new clinical characteristics of liver transplant candidates added to the OPTN list.40 This score extends the MELD-Na by incorporating gender and albumin as additional variables. Considering the disadvantaged position of women under the current system, an additional 1.33 points were compensated for female candidates. The administration of albumin therapy in clinical practice may potentially lower the MELD score. Consequently, a sensitivity analysis was conducted to establish a MELD 3.0 model without serum albumin. This analysis showed that the MELD 3.0, including albumin, demonstrated superior mortality prediction and better discriminative accuracy than MELD-Na. The upper limit of creatinine was adjusted to 3.0 mg/dL to mitigate the influence of muscle mass and relevant comorbidities. Each variable in the MELD 3.0 was an independent predictor of mortality, but interactions between creatinine-albumin and sodium-bilirubin required adding corresponding interaction terms to the model. A temporal validation analysis of transplant candidates from 2019 demonstrated that MELD 3.0 reclassified a net 8.8% of deceased individuals on the waiting list into higher MELD categories, with a majority being female, suggesting that MELD 3.0 effectively reduces mortality on liver transplant waiting lists in the U.S. and partially eliminates existing gender disparities.

Next, we will elaborate on the clinical implementation of MELD 3.0 in the context of specific liver disease.

MELD 3.0 in liver transplantation

The purpose of organ allocation systems is to maximize the use of transplantable organs and minimize deaths on the waiting list. Organ allocation involves a delicate balance of three core principles: urgency, utility, and transplant benefit. Urgency prioritizes organs for patients with the shortest expected survival without a transplant, while utility focuses on those likely to have the longest post-transplant survival. Transplant benefit evaluates disparities in average survival rates before and after transplantation. The liver allocation has primarily emphasized urgency, with the MELD score serving as a biological predictor of mortality to help prioritize surgical intervention.41 In 2023, the United Network for Organ Sharing approved MELD 3.0, which is set to replace MELD-Na in prioritizing donor selection for liver disease patients awaiting LT.

A gender adjustment within the MELD score was also deemed necessary to address the disadvantages faced by females in accessing liver transplants.42 Since the implementation of MELD 3.0, an increase in transplantation likelihood has been observed for women compared to those evaluated with MELD-Na or the original MELD.43

Furthermore, the prognostic benefits of MELD 3.0 varied among different liver disease etiologies.44 In certain cases, there were differences in the prognostic benefits of MELD 3.0. For male patients with alcohol-associated hepatitis (AH) or non-hepatitis ALD, as well as those with metabolic dysfunction-associated steatotic liver disease (MASLD), MELD 3.0 offered slight improvements in calibration compared to the MELD-Na score. However, MELD 3.0 showed lower discrimination for AH, with C-index values of 0.75, 0.86, and 0.84 for AH, non-hepatitis ALD, and MASLD, respectively. In this cohort, the most significant increase in waitlist scores under MELD 3.0 was observed among male patients with AH and female patients with either AH or MASLD. Given the rising issues related to ethanol abuse, further investigation into the application of MELD 3.0 in AH is required.

In an Asian cohort, MELD 3.0 reclassified 22.6% of patients from the original MELD to a higher grade.45 The predictive ability of MELD 3.0 with albumin was lower than that observed in Western countries (C-index: U.S. = 0.869, Korea = 0.780), though it remained superior to other scores in predicting short-term prognosis on the LT waiting list, albeit not statistically significant overall.45 This discrepancy may be attributed to racial differences, variations in liver disease etiologies across countries, and disparities in LT practices, such as the prevalence of living donor LT in East Asia. The effectiveness of MELD 3.0 in reducing waitlist mortality among women and patients with severe ascites was limited in regions with organ shortages.46 However, in another Asian cohort, MELD 3.0 with albumin best stratified prognosis in relation to three-month survival, three-month transplant-free survival, overall survival, and total transplant-free survival. The MELD-Na-kidney dysfunction type derivation, which incorporates renal dysfunction type into MELD-Na, was comparable to MELD 3.0. When stratified by gender, MELD 3.0 demonstrated similar discriminative ability to MELD in males; but in the female cohort, it showed a significant prognostic impact on survival. This suggests that laboratory values related to hepatic and renal dysfunction may be more informative than renal dysfunction type in assessing short-term outcomes for hepatorenal syndrome in liver transplant candidates.47

The OPTN recommends the use of MELD 3.0 over MELD-Na for adolescents awaiting LT. Although initially developed and validated in adults, MELD 3.0 demonstrated moderate predictive performance regarding 90-day mortality in adolescents aged 12–17 on the waiting list,48 with a C-statistic of 0.893 outperforming MELD-Na and PELD, which had C-statistics of 0.871 and 0.852, respectively. Another study indicated that incorporating weight z-scores enhanced risk stratification for LT compared to MELD 3.0 and PELD, which includes sodium and creatinine.49 Notably, eliminating the upper limit of MELD 3.0 could improve risk stratification for mortality and potentially result in greater survival benefits from LT for critically ill patients, such as those with ACLF.50

MELD 3.0 in chronic liver disease

The MELD 3.0 score has been utilized as a predictor of mortality in patients with cirrhosis and other advanced liver diseases. In the context of liver cirrhosis, MELD 3.0 was significantly superior to MELD-Na for predicting both three-month and six-month mortality.51

In patients with hepatocellular carcinoma (HCC) categorized as Child-Turcotte-Pugh (CTP)-B, MELD 3.0 provided the most accurate mortality predictions compared to the albumin-bilirubin score.52 The MELD 3.0 score also demonstrated improved accuracy in predicting 90-day survival for HCC patients, particularly those with scores between 21–30 and 31–37, with 90-day survival rates of 72.5% and 24.3%, respectively. These rates were lower than those of non-HCC patients, which were 82.0% and 72.3%.53 However, MELD 3.0 performed poorly in HCC patients with renal insufficiency, where the albumin-bilirubin score was more effective, as indicated by the lowest corrected Akaike information criterion and highest homogeneity value.54

The prognostic value of MELD 3.0 in predicting one-year mortality in patients with ALD appears limited, showing poor performance compared to MELD-Na, with similar findings in AH.55 Nonetheless, in AH patients, MELD 3.0 performed better for predicting 30-day and 90-day mortality and was the best predictor of the need for renal replacement therapy compared to MELD-Na.56 Enhanced predictions for one-month and one-year mortality were also observed in patients with severe AH.57 MELD 3.0 demonstrated a significant advantage in predicting three-month mortality among patients undergoing TIPS compared to MELD and MELD-Na58 and accurately predicted six-week mortality risk for hospitalized patients with acute variceal bleeding.59

Refractory hepatic hydrothorax (RH), a serious complication of cirrhosis, was not included in the MELD model due to insufficient evidence of increased mortality. In a study by Allison Chin et al., RH was associated with a higher risk of liver-related death than RA at the same MELD-Na level. Although no significant differences in baseline MELD 3.0 levels were observed between patients with RH and RA, MELD 3.0 was found to provide enhanced prognostic capability for liver-related death associated with RH.60 In 327 patients with spontaneous bacterial peritonitis, MELD 3.0 demonstrated the highest AUC for predicting in-hospital and three-month mortality, with C-indexes of 0.786 and 0.760, respectively, outperforming iMELD, MELD, CTP, and MELD-Na. However, iMELD showed the best performance in predicting six-month mortality, with an AUC of 0.752.61 The MELD score has also been used to assess surgical risk in HCC and predict postoperative survival in patients with liver cirrhosis undergoing surgery other than LT.62 However, this application has yet to be verified for MELD 3.0.

Given the rapidly changing nature and prognostic fluctuations in patients with ACLF, MELD-related scores have often demonstrated limited efficacy in this vulnerable population. In this regard, Hernaez et al. proposed the CLIF-C ACLF model for this specific scenario.63 In terms of predicting short-term mortality, the AUC of the CLIF-C ACLF score was 0.80, surpassing those of MELD, MELD-Na, and CTP scores. However, this score was less sensitive for early diagnosis of ACLF in patients with alcoholic and hepatitis B virus-related cirrhosis. In a 2021 study by Li et al.,64 a new simplified score, COSSH-ACLF II, was developed, including INR, hepatic encephalopathy, neutrophils, total bilirubin levels, serum urea, and age. This scoring system demonstrated significantly higher C-indexes for 28-day and 90-day mortality (0.826 and 0.809, respectively) compared to CLIF-C ACLF, MELD, and MELD-Na. Data on the role of MELD 3.0 in the ACLF population remain limited, and its impact is unclear, necessitating further studies to determine the optimal time point concerning predictive efficacy.65

Following extensive research, MELD-related scores have been effectively employed in clinical practice to guide the rational allocation of liver donations, significantly contributing to the preservation of numerous lives of patients with acute or end-stage liver diseases. However, due to variations in etiology, precipitating factors, and ethnicity, it remains uncertain whether MELD 3.0 is universally applicable across all categories of liver disease. In summary, further investigation into MELD 3.0 is anticipated to confirm its effects in future studies.

In 2023, the Gender Equity Model for Liver Allocation Sodium was developed in the UK and underwent external validation in an Australian cohort, where it demonstrated superior performance in predicting 90-day mortality upon waitlist inclusion compared to MELD-Na.66 However, no significant differences were found between the Gender Equity Model for Liver Allocation Sodium, MELD-Na, and MELD 3.0 in an Italian cohort, indicating the need for further validation from other regions to clarify the discriminatory ability of these models.67

The original MELD score encompassed three quantitative values: serum bilirubin, INR, and creatinine, later revised into the MELD-Na score with the addition of serum sodium. Numerous variations of the original MELD score have since been proposed. ΔMELD was derived by calculating the difference in MELD scores within 30 days, MELD-LA incorporated serum lactate, and iMELD added age and sodium. Removing INR resulted in MELD XI, while excluding creatinine and including albumin yielded PELD. The latest iteration, MELD 3.0, further incorporates serum sodium, albumin, and gender, and adjusts the upper limit of serum creatinine to 3.0 mg/dL, enhancing accuracy in estimating disease severity in patients with liver diseases. MELD 3.0, which fully accounts for gender differences and optimizes organ allocation systems for liver transplantation,43 has been adopted as a new standard in the U.S. Nevertheless, MELD 3.0 may not be as precise as other scoring systems for predicting prognosis in specific liver disease etiologies (such as AH)44 and ACLF.65 Additionally, its predictive capacity could be influenced by ethnic disparities, differences concerning liver disease etiology across countries, and variations in the liver transplant practice. Eliminating the upper limit of MELD 3.0, currently set at 40 points, could increase survival benefits for candidates but might also lead to overestimation of severely ill patients, affecting the fairness of organ allocation.50 Therefore, further research is needed to verify the validity and reliability of the MELD 3.0 score.

Future prospects

With advancements in technology, novel strategies and approaches are emerging that surpass conventional MELD scoring methods. The establishment and refinement of electronic health record systems68 can facilitate access to precise, real-time shared data, providing a solid foundation for developing and evaluating comprehensive prediction models pertinent to mortality risk associated with LT. It is anticipated that artificial intelligence, natural language processing,69 and clinical decision support2 will leverage robust algorithmic models, potentially enhancing predictive capabilities for prognosis.

Conclusions

In conclusion, our findings indicate superior predictive performance of MELD 3.0, warranting further in-depth investigations to broaden its clinical implications.

Declarations

Funding

None to declare.

Conflict of interest

CS has been an Editorial Board Member of Journal of Clinical and Translational Hepatology since 2020. The other authors have no conflict of interests related to this publication.

Authors’ contributions

Writing - original draft (GG), literature search (WY), visualization and data analysis (JL), visualization (ZY), writing - review and editing (JL), design and supervision (CS). All authors were involved in the writing and revision of the manuscript. All authors have made significant contributions to this study and have approved the final version and publication of the manuscript.

References

  1. Wiesner R, Edwards E, Freeman R, Harper A, Kim R, Kamath P, et al. Model for end-stage liver disease (MELD) and allocation of donor livers. Gastroenterology 2003;124(1):91-96 View Article PubMed/NCBI
  2. Ge J, Kim WR, Lai JC, Kwong AJ. “Beyond MELD” - Emerging strategies and technologies for improving mortality prediction, organ allocation and outcomes in liver transplantation. J Hepatol 2022;76(6):1318-1329 View Article PubMed/NCBI
  3. Allen AM, Heimbach JK, Larson JJ, Mara KC, Kim WR, Kamath PS, et al. Reduced Access to Liver Transplantation in Women: Role of Height, MELD Exception Scores, and Renal Function Underestimation. Transplantation 2018;102(10):1710-1716 View Article PubMed/NCBI
  4. Younossi ZM, Stepanova M, Younossi Y, Golabi P, Mishra A, Rafiq N, et al. Epidemiology of chronic liver diseases in the USA in the past three decades. Gut 2020;69(3):564-568 View Article PubMed/NCBI
  5. Quante M, Benckert C, Thelen A, Jonas S. Experience Since MELD Implementation: How Does the New System Deliver?. Int J Hepatol 2012;2012:264015 View Article PubMed/NCBI
  6. Biggins SW, Kim WR, Terrault NA, Saab S, Balan V, Schiano T, et al. Evidence-based incorporation of serum sodium concentration into MELD. Gastroenterology 2006;130(6):1652-1660 View Article PubMed/NCBI
  7. Nagai S, Chau LC, Schilke RE, Safwan M, Rizzari M, Collins K, et al. Effects of Allocating Livers for Transplantation Based on Model for End-Stage Liver Disease-Sodium Scores on Patient Outcomes. Gastroenterology 2018;155(5):1451-1462.e3 View Article PubMed/NCBI
  8. Brown C, Aksan N, Muir AJ. MELD-Na Accurately Predicts 6-Month Mortality in Patients With Decompensated Cirrhosis: Potential Trigger for Hospice Referral. J Clin Gastroenterol 2022;56(10):902-907 View Article PubMed/NCBI
  9. Goudsmit BFJ, Putter H, Tushuizen ME, de Boer J, Vogelaar S, Alwayn IPJ, et al. Validation of the Model for End-stage Liver Disease sodium (MELD-Na) score in the Eurotransplant region. Am J Transplant 2021;21(1):229-240 View Article PubMed/NCBI
  10. Cheng Y, Wei GQ, Cai QC, Jiang Y, Wu AP. Prognostic Value of Model for End-Stage Liver Disease Incorporating with Serum Sodium Score for Development of Acute Kidney Injury after Liver Transplantation. Chin Med J (Engl) 2018;131(11):1314-1320 View Article PubMed/NCBI
  11. Zhang QK, Wang ML. Value of Model for End-Stage Liver Disease-Serum Sodium Scores in Predicting Complication Severity Grades After Liver Transplantation for Acute-on-chronic Liver Failure. Transplant Proc 2019;51(3):833-841 View Article PubMed/NCBI
  12. Ruf AE, Kremers WK, Chavez LL, Descalzi VI, Podesta LG, Villamil FG. Addition of serum sodium into the MELD score predicts waiting list mortality better than MELD alone. Liver Transpl 2005;11(3):336-343 View Article PubMed/NCBI
  13. Krishnan A, Woreta TA, Vaidya D, Liu Y, Hamilton JP, Hong K, et al. MELD or MELD-Na as a Predictive Model for Mortality Following Transjugular Intrahepatic Portosystemic Shunt Placement. J Clin Transl Hepatol 2023;11(1):38-44 View Article PubMed/NCBI
  14. Zhao Y, Wang Y, Xu J. Predictive Accuracy Comparison of Prognostic Scoring Systems for Survival in Patients Undergoing TIPS Placement: A Systematic Review and Meta-analysis. Acad Radiol 2024;31(9):3688-3710 View Article PubMed/NCBI
  15. Merion RM, Wolfe RA, Dykstra DM, Leichtman AB, Gillespie B, Held PJ. Longitudinal assessment of mortality risk among candidates for liver transplantation. Liver Transpl 2003;9(1):12-18 View Article PubMed/NCBI
  16. Kim HJ, Lee HW. Important predictor of mortality in patients with end-stage liver disease. Clin Mol Hepatol 2013;19(2):105-115 View Article PubMed/NCBI
  17. Colmenero J, Navasa M. Delta-MELD and survival after liver transplantation: the slope matters. Liver Int 2016;36(7):949-951 View Article PubMed/NCBI
  18. Acar Ş, Akyıldız M, Gürakar A, Tokat Y, Dayangaç M. Delta MELD as a predictor of early outcome in adult-to-adult living donor liver transplantation. Turk J Gastroenterol 2020;31(11):782-789 View Article PubMed/NCBI
  19. Heuman DM, Mihas AA, Habib A, Gilles HS, Stravitz RT, Sanyal AJ, et al. MELD-XI: a rational approach to “sickest first” liver transplantation in cirrhotic patients requiring anticoagulant therapy. Liver Transpl 2007;13(1):30-37 View Article PubMed/NCBI
  20. Inohara T, Kohsaka S, Shiraishi Y, Goda A, Sawano M, Yagawa M, et al. Prognostic impact of renal and hepatic dysfunction based on the MELD-XI score in patients with acute heart failure. Int J Cardiol 2014;176(3):571-573 View Article PubMed/NCBI
  21. Yang JA, Kato TS, Shulman BP, Takayama H, Farr M, Jorde UP, et al. Liver dysfunction as a predictor of outcomes in patients with advanced heart failure requiring ventricular assist device support: Use of the Model of End-stage Liver Disease (MELD) and MELD eXcluding INR (MELD-XI) scoring system. J Heart Lung Transplant 2012;31(6):601-610 View Article PubMed/NCBI
  22. Critsinelis A, Kurihara C, Volkovicher N, Kawabori M, Sugiura T, Manon M, et al. Model of End-Stage Liver Disease-eXcluding International Normalized Ratio (MELD-XI) Scoring System to Predict Outcomes in Patients Who Undergo Left Ventricular Assist Device Implantation. Ann Thorac Surg 2018;106(2):513-519 View Article PubMed/NCBI
  23. Byrne RD, Weingarten AJ, Clark DE, Huang S, Perri RE, Scanga AE, et al. More than the heart: Hepatic, renal, and cardiac dysfunction in adult Fontan patients. Congenit Heart Dis 2019;14(5):765-771 View Article PubMed/NCBI
  24. Amdani S, Simpson KE, Thrush P, Shih R, Simmonds J, Knecht K, et al. Hepatorenal dysfunction assessment with the Model for End-Stage Liver Disease Excluding INR score predicts worse survival after heart transplant in pediatric Fontan patients. J Thorac Cardiovasc Surg 2022;163(4):1462-1473.e12 View Article PubMed/NCBI
  25. Luca A, Angermayr B, Bertolini G, Koenig F, Vizzini G, Ploner M, et al. An integrated MELD model including serum sodium and age improves the prediction of early mortality in patients with cirrhosis. Liver Transpl 2007;13(8):1174-1180 View Article PubMed/NCBI
  26. Saldaña RS, Schrem H, Barthold M, Kaltenborn A. Prognostic Abilities and Quality Assessment of Models for the Prediction of 90-Day Mortality in Liver Transplant Waiting List Patients. PLoS One 2017;12(1):e0170499 View Article PubMed/NCBI
  27. Huo TI, Lin HC, Huo SC, Lee PC, Wu JC, Lee FY, et al. Comparison of four model for end-stage liver disease-based prognostic systems for cirrhosis. Liver Transpl 2008;14(6):837-844 View Article PubMed/NCBI
  28. Jiang M, Liu F, Xiong WJ, Zhong L, Chen XM. Comparison of four models for end-stage liver disease in evaluating the prognosis of cirrhosis. World J Gastroenterol 2008;14(42):6546-6550 View Article PubMed/NCBI
  29. Chen PC, Chen BH, Huang CH, Jeng WJ, Hsieh YC, Teng W, et al. Integrated model for end-stage liver disease maybe superior to some other model for end-stage liver disease-based systems in addition to Child-Turcotte-Pugh and albumin-bilirubin scores in patients with hepatitis B virus-related liver cirrhosis and spontaneous bacterial peritonitis. Eur J Gastroenterol Hepatol 2019;31(10):1256-1263 View Article PubMed/NCBI
  30. Shi Y, Yang Y, Hu Y, Wu W, Yang Q, Zheng M, et al. Acute-on-chronic liver failure precipitated by hepatic injury is distinct from that precipitated by extrahepatic insults. Hepatology 2015;62(1):232-242 View Article PubMed/NCBI
  31. Cardoso NM, Silva T, Basile-Filho A, Mente ED, Castro-e-Silva O. A new formula as a predictive score of post-liver transplantation outcome: postoperative MELD-lactate. Transplant Proc 2014;46(5):1407-1412 View Article PubMed/NCBI
  32. Sarmast N, Ogola GO, Kouznetsova M, Leise MD, Bahirwani R, Maiwall R, et al. Model for End-Stage Liver Disease-Lactate and Prediction of Inpatient Mortality in Patients With Chronic Liver Disease. Hepatology 2020;72(5):1747-1757 View Article PubMed/NCBI
  33. Horvatits T, Mahmud N, Serper M, Seiz O, Reher D, Drolz A, et al. MELD-Lactate Predicts Poor Outcome in Variceal Bleeding in Cirrhosis. Dig Dis Sci 2023;68(3):1042-1050 View Article PubMed/NCBI
  34. Chen XF. Prognostic Role of MELD-Lactate in Cirrhotic Patients’ Short- and Long-Term Prognosis, Stratified by Causes of Cirrhosis. Can J Gastroenterol Hepatol 2022;2022:8449579 View Article PubMed/NCBI
  35. Davies DB. The impact of PELD on OPTN liver allocation: preliminary results. Clin Transpl 2003:13-20 View Article PubMed/NCBI
  36. Rajanayagam J, Coman D, Cartwright D, Lewindon PJ. Pediatric acute liver failure: etiology, outcomes, and the role of serial pediatric end-stage liver disease scores. Pediatr Transplant 2013;17(4):362-368 View Article PubMed/NCBI
  37. Kaplan J, Han L, Halgrimson W, Wang E, Fryer J. The impact of MELD/PELD revisions on the mortality of liver-intestine transplantation candidates. Am J Transplant 2011;11(9):1896-1904 View Article PubMed/NCBI
  38. Malenicka S, Ericzon BG, Jørgensen MH, Isoniemi H, Karlsen TH, Krantz M, et al. Impaired intention-to-treat survival after listing for liver transplantation in children with biliary atresia compared to other chronic liver diseases: 20 years’ experience from the Nordic countries. Pediatr Transplant 2017;21(2):e12851 View Article PubMed/NCBI
  39. Wang Y, Liu P, Duan M. Prevalence, Risk Factors and Clinical Outcomes of Acute Kidney Injury after Paediatric Liver Transplantation. Arch Esp Urol 2023;76(8):548-554 View Article PubMed/NCBI
  40. Kim WR, Mannalithara A, Heimbach JK, Kamath PS, Asrani SK, Biggins SW, et al. MELD 3.0: The Model for End-Stage Liver Disease Updated for the Modern Era. Gastroenterology 2021;161(6):1887-1895.e4 View Article PubMed/NCBI
  41. Snyder JJ, Salkowski N, Wey A, Pyke J, Israni AK, Kasiske BL. Organ distribution without geographic boundaries: A possible framework for organ allocation. Am J Transplant 2018;18(11):2635-2640 View Article PubMed/NCBI
  42. Sealock JM, Ziogas IA, Zhao Z, Ye F, Alexopoulos SP, Matsuoka L, et al. Proposing a Sex-Adjusted Sodium-Adjusted MELD Score for Liver Transplant Allocation. JAMA Surg 2022;157(7):618-626 View Article PubMed/NCBI
  43. Walter Costa MB, Gärtner C, Schmidt M, Berg T, Seehofer D, Kaiser T. Revising the MELD Score to Address Sex-Bias in Liver Transplant Prioritization for a German Cohort. J Pers Med 2023;13(6):963 View Article PubMed/NCBI
  44. Bittermann T, Mahmud N, Weinberg EM, Reddy KR. MELD 3.0 leads to heterogeneous prioritization of men and women on the liver transplant waiting list. Liver Transpl 2023;29(6):655-657 View Article PubMed/NCBI
  45. Yoo JJ, Chang JI, Moon JE, Sinn DH, Kim SG, Kim YS. Validation of MELD 3.0 scoring system in East Asian patients with cirrhosis awaiting liver transplantation. Liver Transpl 2023;29(10):1029-1040 View Article PubMed/NCBI
  46. Kim DG, Yim SH, Min EK, Choi MC, Lee JG, Kim MS, et al. Predicted Impact of the Model for End-Stage Liver Disease 3.0 in a Region Suffering Severe Organ Shortage. J Korean Med Sci 2023;38(35):e274 View Article PubMed/NCBI
  47. Yeom KM, Chang JI, Yoo JJ, Moon JE, Sinn DH, Kim YS, et al. Addition of Kidney Dysfunction Type to MELD-Na for the Prediction of Survival in Cirrhotic Patients Awaiting Liver Transplantation in Comparison with MELD 3.0 with Albumin. Diagnostics (Basel) 2023;14(1):39 View Article PubMed/NCBI
  48. Kwong AJ, Zhang KY, Ebel N, Mannalithara A, Kim WR. MELD 3.0 for adolescent liver transplant candidates. Hepatology 2023;78(2):540-546 View Article PubMed/NCBI
  49. Shaheen AA, Martin SR, Khorsheed S, Abraldes JG. A model including standardized weight improved predicting waiting list mortality in adolescent liver transplant candidates: A US national study. Liver Transpl 2024;30(3):269-276 View Article PubMed/NCBI
  50. Kim WR, Mannalithara A, Kwo PY, Bonham CA, Kwong A. Mortality in patients with end-stage liver disease above model for end-stage liver disease 3.0 of 40. Hepatology 2023;77(3):851-861 View Article PubMed/NCBI
  51. Kim JH, Cho YJ, Choe WH, Kwon SY, Yoo BC. Model for end-stage liver disease-3.0 vs. model for end-stage liver disease-sodium: mortality prediction in Korea. Korean J Intern Med 2024;39(2):248-260 View Article PubMed/NCBI
  52. Fu CC, Chen YJ, Su CW, Wei CY, Chu CJ, Lee PC, et al. The outcomes and prognostic factors of patients with hepatocellular carcinoma and Child-Turcotte-Pugh class B. J Chin Med Assoc 2023;86(10):876-884 View Article PubMed/NCBI
  53. Kim K, Kim DG, Lee JG, Joo DJ, Lee HW. The Effect of Model for End-Stage Liver Disease 3.0 on Disparities between Patients with and without Hepatocellular Carcinoma in Korea. Yonsei Med J 2023;64(11):647-657 View Article PubMed/NCBI
  54. Ho SY, Liu PH, Hsu CY, Tseng HT, Huang YH, Su CW, et al. Albumin-Based Liver Reserve Models vs. MELD 3.0 in Prognostic Prediction for Hepatocellular Carcinoma Patients with Renal Insufficiency. Int J Mol Sci 2023;24(23):16987 View Article PubMed/NCBI
  55. Duan F, Liu C, Zhai H, Quan M, Cheng J, Yang S. The Model for End-stage Liver Disease 3.0 is not superior to the Model for End-stage Liver Disease-Na in predicting survival: A retrospective cohort study. Hepatol Commun 2023;7(10):e0250 View Article PubMed/NCBI
  56. Díaz LA, Fuentes-López E, Ayares G, Idalsoaga F, Arnold J, Valverde MA, et al. MELD 3.0 adequately predicts mortality and renal replacement therapy requirements in patients with alcohol-associated hepatitis. JHEP Rep 2023;5(8):100727 View Article PubMed/NCBI
  57. Singeap AM, Minea H, Petrea O, Robea MA, Balmuș IM, Duta R, et al. Real-World Utilization of Corticosteroids in Severe Alcoholic Hepatitis: Eligibility, Response, and Outcomes. Medicina (Kaunas) 2024;60(2):311 View Article PubMed/NCBI
  58. Song J, Wang X, Yan Y, Xiang T, Luo X. MELD 3.0 Score for Predicting Survival in Patients with Cirrhosis After Transjugular Intrahepatic Portosystemic Shunt Creation. Dig Dis Sci 2023;68(7):3185-3192 View Article PubMed/NCBI
  59. Buckholz A, Wong R, Curry MP, Baffy G, Chak E, Rustagi T, et al. MELD, MELD 3.0, versus Child score to predict mortality after acute variceal hemorrhage: A multicenter US cohort. Hepatol Commun 2023;7(10):e0258 View Article PubMed/NCBI
  60. Chin A, Bastaich DR, Dahman B, Kaplan DE, Taddei TH, John BV. Refractory hepatic hydrothorax is associated with increased mortality with death occurring at lower MELD-Na compared to cirrhosis and refractory ascites. Hepatology 2024;79(4):844-856 View Article PubMed/NCBI
  61. Lin YT, Chen WT, Wu TH, Liu Y, Liu LT, Teng W, et al. A Validated Composite Score Demonstrates Potential Superiority to MELD-Based Systems in Predicting Short-Term Survival in Patients with Liver Cirrhosis and Spontaneous Bacterial Peritonitis-A Preliminary Study. Diagnostics (Basel) 2023;13(15):2578 View Article PubMed/NCBI
  62. Teh SH, Nagorney DM, Stevens SR, Offord KP, Therneau TM, Plevak DJ, et al. Risk factors for mortality after surgery in patients with cirrhosis. Gastroenterology 2007;132(4):1261-1269 View Article PubMed/NCBI
  63. Jalan R, Saliba F, Pavesi M, Amoros A, Moreau R, Ginès P, et al. Development and validation of a prognostic score to predict mortality in patients with acute-on-chronic liver failure. J Hepatol 2014;61(5):1038-1047 View Article PubMed/NCBI
  64. Li J, Liang X, You S, Feng T, Zhou X, Zhu B, et al. Development and validation of a new prognostic score for hepatitis B virus-related acute-on-chronic liver failure. J Hepatol 2021;75(5):1104-1115 View Article PubMed/NCBI
  65. Hernaez R, Solà E, Moreau R, Ginès P. Acute-on-chronic liver failure: an update. Gut 2017;66(3):541-553 View Article PubMed/NCBI
  66. Rodríguez-Perálvarez ML, Gómez-Orellana AM, Majumdar A, Bailey M, McCaughan GW, Gow P, et al. Development and validation of the Gender-Equity Model for Liver Allocation (GEMA) to prioritise candidates for liver transplantation: a cohort study. Lancet Gastroenterol Hepatol 2023;8(3):242-252 View Article PubMed/NCBI
  67. Marrone G, Giannelli V, Agnes S, Avolio AW, Baiocchi L, Berardi G, et al. Superiority of the new sex-adjusted models to remove the female disadvantage restoring equity in liver transplant allocation. Liver Int 2024;44(1):103-112 View Article PubMed/NCBI
  68. Kawamoto K, Kukhareva P, Shakib JH, Kramer H, Rodriguez S, Warner PB, et al. Association of an Electronic Health Record Add-on App for Neonatal Bilirubin Management With Physician Efficiency and Care Quality. JAMA Netw Open 2019;2(11):e1915343 View Article PubMed/NCBI
  69. Van Vleck TT, Chan L, Coca SG, Craven CK, Do R, Ellis SB, et al. Augmented intelligence with natural language processing applied to electronic health records for identifying patients with non-alcoholic fatty liver disease at risk for disease progression. Int J Med Inform 2019;129:334-341 View Article PubMed/NCBI