IJGII Inernational Journal of Gastrointestinal Intervention

pISSN 2636-0004 eISSN 2636-0012
ESCI
scopus

Article

Original Article

Int J Gastrointest Interv 2024; 13(3): 91-97

Published online July 31, 2024 https://doi.org/10.18528/ijgii240032

Copyright © International Journal of Gastrointestinal Intervention.

Prognostic indicators and risk factors for the in-hospital mortality rate of patients with cirrhosis

Zahra Shokati Eshkiki , Mobin Gholami , Ahmad Kadkhodaei , and Ali Akbar Shayesteh*

Alimentary Tract Research Center, Clinical Sciences Research Institute, Imam Khomeini Hospital, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran

Correspondence to:*Alimentary Tract Research Center, Clinical Sciences Research Institute, Imam Khomeini Hospital, Ahvaz Jundishapur University of Medical Sciences, Ahvaz 0098, Iran.
E-mail address: shayeste-a@ajums.ac.ir (A.A. Shayesteh).

Received: May 29, 2024; Revised: June 12, 2024; Accepted: July 5, 2024

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/4.0) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Background: Hepatic encephalopathy (HE) is an adverse prognostic indicator of liver cirrhosis, often triggered by various precipitating factors, with gastrointestinal bleeding being the most common. Comparing the Child–Pugh and Model for End-Stage Liver Disease (MELD) scores to predict the severity and outcome of complications in patients with cirrhosis could help establish an accurate prognosis.
Methods: We retrospectively reviewed the records of patients with cirrhosis aged 18 and older who were referred to the Gastroenterology Department at Imam Khomeini Hospital in Ahvaz from April to September 2023. A statistical analysis was conducted to compare MELD and Child-Pugh score (CPS) in 95 patients with cirrhosis.
Results: The in-hospital mortality rate was strongly correlated with certain complications of cirrhosis. Gastrointestinal bleeding and HE showed statistical significance (P < 0.05). Additionally, the co-occurrence of cirrhosis complications, particularly HE in conjunction with others, was associated with increased mortality rates. Abnormal levels of the international normalized ratio, prothrombin time, partial thromboplastin time, bilirubin, and liver enzymes (alanine aminotransferase, aspartate aminotransferase, and alkaline phosphatase) were also associated with mortality (P < 0.05). Specific laboratory factors in ascites fluid, namely total cell count and red blood count, were linked to the 6-month survival rate (P < 0.05). Furthermore, CPS was identified as a more specific and sensitive independent predictor of 6-month in-hospital survival than the MELD score (logistic regression: odds ratio, 2.3; standard error, 0.0189; P < 0.05).
Conclusion: We recommend continuing to use the CPS for predicting in-hospital mortality in patients with cirrhosis and for the individual evaluation of liver disease in daily clinical practice.

Keywords: Child–,Pugh score, Hepatic encephalopathy, Liver cirrhosis, MELD score, Upper gastrointestinal bleeding

Cirrhosis represents the final stage of chronic liver disease. As the disease progresses from the compensation phase to the decompensation phase, patients experience a range of complications that significantly worsen their life expectancy.1 Clinically, cirrhosis is categorized into two phases: the early or compensated phase, which is often asymptomatic, and the subsequent decompensated phase.2 Due to the poor survival rates among patients with decompensated cirrhosis and the worsening prognosis associated with complications such as hepatic encephalopathy (HE), gastrointestinal bleeding (GIB), spontaneous bacterial peritonitis (SBP), hepatorenal syndrome (HRS), and ascites, researchers are motivated to develop reliable tools for predicting outcomes in patients with chronic liver disease.35

The Child-Pugh score (CPS) and the Model for End-Stage Liver Disease (MELD) score are widely used disease severity scoring systems in patients with cirrhosis.6,7 Introduced in 1964, the CPS has become a reliable tool for the clinical evaluation of liver dysfunction.8 The MELD score, introduced in 2002 in the USA, initially included the etiology of liver cirrhosis in its calculations. However, the current version of the MELD score utilizes paraclinical parameters such as serum bilirubin, creatinine levels, and prothrombin time (PT) or international normalized ratio (INR).9,10 Originally developed to predict mortality in patients undergoing transjugular intrahepatic portosystemic shunt (TIPSS) procedures, the MELD score is now primarily used to prioritize organ allocation for liver transplantation candidates.11,12

Given the rising number of patients with cirrhosis experiencing poor survival rates during the decompensated phase, as well as increased hospital admissions due to overt HE and GIB, it is clear that these complications are common and associated with high resource use and significant mortality. Consequently, establishing an accurate prognosis for these patients continues to be a challenging issue.13,14 Therefore, we aimed to investigate this issue by comparing the accuracy of the CPS and the MELD scoring systems in predicting in-hospital mortality in patients with complications from liver cirrhosis.

After receiving approval from the Ethics Committee of Ahvaz Jundishapur University of Medical Sciences (Ethics Committee number: IR.AJUMS.REC.A/1402), 95 patients aged 18 years and older with liver cirrhosis were retrospectively included in this study. These patients were referred to the Gastroenterology Department of Imam Khomeini Hospital in Ahvaz between April and September 2023. Since the current investigation was a retrospective study, written informed consent to participate in this study was waived by the Ahvaz Jundishapur University of Medical Sciences ethics committee.

Each hospital record was meticulously reviewed to confirm the diagnosis of liver cirrhosis and to gather all pertinent data, which was derived from a well-established combination of laboratory, clinical, anatomopathological, and radiological features.

1. Standard parameters of liver and kidney function were evaluated.

2. The CP and MELD scores (the MELD score was calculated according to the standard formula) were assessed and compared.

Data collection

The etiology of liver disease varied, with cases attributed to cryptogenic factors, hepatitis C virus, hepatitis B virus, alcohol abuse, and potentially other reasons.

The data recorded at admission included demographic data (age, sex), the natural history of cirrhosis {etiology, the presence of ascites, upper GIB, hepatocellular carcinoma (HCC), SBP, HRS, and HE, the cause of admission and laboratory measurements (platelet and leukocyte count, bilirubin, hemoglobin, hematocrit, creatinine, albumin, and levels of liver enzymes; alanine aminotransferase [ALT], aspartate aminotransferase [AST], alkaline phosphatase [ALK-P], PT, and INR)}.

All biochemical evaluations were conducted by the same laboratory. Prothrombin activity was initially assessed by a single operator and expressed as a percentage. It was then converted to the PT and INR using the laboratory’s internal standards.

We also collected endoscopic findings from 61% of patients with cirrhosis, at the discretion of their physicians. The most frequently recorded endoscopic parameter was esophageal varices. Additionally, we documented in-hospital deaths and their causes. The endpoint of this 6-month study was either the discharge of the patient or death, which was used to predict in-hospital mortality among hospitalized patients with decompensated cirrhosis.

Calculation of the CPS and the MELD score

The severity of liver cirrhosis was assessed using both the CPS and the MELD scoring systems. The calculation of the CPS took into account the severity of ascites, HE, INR, total bilirubin, and albumin levels.15 The MELD score was calculated according to the following standard formula:

3.8 × loge [bilirubin (mg/dL)] + 11.2 × loge (INR) + 9.6 × loge [creatinine (mg/dL)] + 6.4 × (etiology: 0 if cholestatic or alcoholic, 1 otherwise).16

Both the MELD and CPS scores were calculated based on parameters obtained at the time of referral. The areas under the receiver operating characteristic (ROC) curves, along with 95% confidence intervals (CI), were reported for these two scoring systems.

Statistical analysis

Categorical variables were reported as frequency (percentage), and Fisher’s exact test or the chi-square test was used to compare these variables. Statistical differences and the analysis of quantitative data were determined using the independent-sample t-test or the Mann-Whitney U test. We evaluated the performance of the two scoring systems by employing binary logistic regression and calculating the odds ratio (OR). All statistical analyses were conducted using SPSS Statistics version 16 (SPSS Inc.). P-values less than 0.05 were considered statistically significant.

All patients with cirrhosis admitted to the Gastroenterology Department of Imam Hospital between April and September 2023 were enrolled in the study.

The mean age of the population was 56 years, with 62 individuals (65%) being male and 33 female (35%). The predominant etiology was cryptogenic, accounting for 48% of cases. The characteristics of the patients included in this study are summarized in Table 1.

Table 1 . Demographic and Baseline Characteristics of Hospitalized Patients with Cirrhosis.

VariableLiver cirrhosis (n = 95)
Age (yr)55.5 (23–88)
Sex
Male65.0
Female35.0
Cause of cirrhosis
Alcohol4.2
Hepatitis B20.0
Hepatitis C23.2
Cryptogenic48.4
Others4.2
HRS9.5
HE25.3
Ascites73.7
HCC4.2
GIB38.9
SBP57.9

Values are presented as median (range) or the frequency of individuals (percentage)..

HRS, hepatorenal syndrome; HE, hepatic encephalopathy; HCC, hepatocellular carcinoma; GIB, gastrointestinal bleeding; SBP, spontaneous bacterial peritonitis..



There was no correlation between demographic or etiological data and the in-hospital mortality rate among the study group (P > 0.05) (Table 2).

Table 2 . Characteristics and Prognosis of Hospitalized Patients.

VariableSurviving patientDeceased patientP-value
Age (yr)54.5 (23–86)57 (26–88)0.586
Sex
Male59.7078.600.78
Female40.3021.400.78
Cause of cirrhosis0.942
Alcohol4.503.60
Hepatitis B19.4021.40
Hepatitis C20.9028.60
Cryptogenic50.7042.90
Others4.503.60

Values are presented as median (range) or the frequency of individuals (percentage)..



Ninety-five individuals were diagnosed with cirrhosis. Following a six-month observation period, 18 of these patients died (18.9%). The occurrence of complications related to liver cirrhosis, particularly the co-occurrence of HE with other complications, was associated with the in-hospital mortality rate (Table 3).

Table 3 . Complications and Mortality in Hospitalized Patients.

Cirrhotic complicationFrequencyMortalityPercentage (%)
Co-occurrence of 3 complications7457
Ascites and GIB17529
Ascites and HE10660
Ascites and HRS4125
HE and GIB11100
HE and HRS11100
Ascites and HCC200

GIB, gastrointestinal bleeding; HE, hepatic encephalopathy; HRS, hepatorenal syndrome; HCC, hepatocellular carcinoma..



Our findings revealed a strong correlation between certain complications of cirrhosis, such as GIB and HE, and the in-hospital mortality rate. This suggests a significant association between the presence of these complications and life expectancy in patients with cirrhosis (P < 0.05, Table 4).

Table 4 . Correlation of Cirrhotic Complications and In-Hospital Mortality Rate.

Cirrhotic complicationsSurviving patientDeceased patientP-value
HRS7 (7.50)14 (14.30)0.442
HE17 (17.90)41 (42.90)0.011
Ascites68 (71.60)75 (78.60)0.484
HCC2 (3.00)7 (7.10)0.579
GIB30 (31.30)54 (57.10)0.019

Values are presented as number (%)..

HRS, hepatorenal syndrome; HE, hepatic encephalopathy; HCC, hepatocellular carcinoma; GIB, gastrointestinal bleeding..



The correlation between laboratory findings and the in-hospital mortality rate also showed significant associations between abnormal values of INR, PT, partial thromboplastin time (PTT), bilirubin, and liver enzymes (ALT, AST, and ALK-P) and the in-hospital mortality rate (P < 0.05, Table 5).

Table 5 . Comparison of Biochemical Characteristics of Hospitalized Patients’ Blood Samples.

Laboratory dataSurviving patientDeceased patientP-value
WBC (103/µL)8.45 ± 5.32 (1.60–36.00)8.98 ± 3.90 (2.20–17.20)0.640
Hemoglobin (g/dL)9.41 ± 2.08 (5.20–14.40)8.55 ± 2.59 (4.30–13.20)0.091
Hematocrit (%)29.20 ± 5.47 (17.80–41.50)25.55 ± 7.61 (14.20–41.00)0.058
Platelet (103/µL)105.16 ± 43.33 (13–231)112.50 ± 44.68 (30–227)0.458
BUN (mg/dL)38.17 ± 28.27 (7–140)44.96 ± 31.71 (7–126)0.306
Creatinine (mg/dL)1.48 ± 1.13 (0.40– 8.20)1.84 ± 1.69 (0.40–8.10)0.342
AST (U/L)76.37 ± 59.20 (13–373)155.17 ± 198.08 (20–998)0.048
ALT (U/L)72.61 ± 77.13 (12–561)122.25 ± 125 (12–504)0.059
ALK-P (U/L)332.50 ± 252.73 (3.60–2,009)674.46 ± 733.84 (107–2,981)0.023
Bilirubin (mg/dL)4.10 ± 4.46 (0.60–28.00)9.93 ± 7.91 (0.60–27.40)< 0.001
PT (s)15.29 ± 2.76 (12–29)18.34 ± 4.59 (12.33)0.002
PTT (s)42.23 ± 22.49 (28–120)54.28 ± 29.09 (28–120)0.001
INR1.57 ± 0.53 (1–4.38)2.16 ± 0.95 (1–5.70)0.002
Protein (g/dL)6.19 ± 0.97 (3.40–820)5.98 ± 0.91 (4.30–8.20)0.332
Albumin (g/dL)3.01 ± 0.57 (1.91–4.30)2.61 ± 0.46 (1.90–3.50)0.002

Values are presented as mean ± standard deviation (standard error of the mean)..

WBC, white blood cell; BUN, blood urea nitrogen; AST, aspartate aminotransferase; ALT, alanine aminotransferase; ALK-P, alkaline phosphatase; PT, prothrombin time; PTT, partial thromboplastin time; INR, international normalized ratio..



In addition, Table 6 compares the biochemical characteristics of ascites fluid in patients with cirrhosis who died with those who survived after six months of evaluation. The data demonstrated that factors in the ascites fluid associated with 6-month survival included total cell and red blood cell (RBC) counts (P < 0.05).

Table 6 . Comparison of Biochemical Characteristics of Hospitalized Patients’ Ascites Fluid.

Laboratory dataSurviving patientDeceased patientP-value
Albumin (g/dL)0.70 ± 0.59 (0.10–3.00)0.60 ± 0.36 (0.30–1.70)0.616
Protein (g/dL)1.40 ± 0.88 (0.30–3.80)1.40 ± 0.57 (0.80–2.70)0.952
LDH90 ± 107.10 (27–620)141 ± 156.18 (32–558)0.070
Glucose (mg/dL)134 ± 57.98 (71–351)119 ± 64.38 (26–283)0.080
Total cells2,170 ± 6,963 (10–32,500)700 ± 4,331 (80–17,000)0.015
WBCs (103/µL)400 ± 10,952 (25–70,000)400 ± 4,358 (10–16.80)0.748
RBCs (106/µL)1,600 ± 9,285 (0–44,000)200 ± 628 (20–2,560)< 0.001
Neutrophils (%)60 ± 28 (2–95)50 ± 24.90 (15–90)0.625
Lymphocytes (%)40 ± 27.98 (5–98)50 ± 24.90 (10–85)0.608

Values are presented as mean ± standard deviation (standard error of the mean)..

LDH, lactate dehydrogenase; WBCs, white blood cells; RBCs, red blood cells..



Among the 66 patients who underwent endoscopy, esophageal varices were the most frequently observed condition, accounting for 73.3% of cases. The incidences of high-grade and low-grade varices were roughly equal. Nevertheless, there was no evidence of a relation between endoscopic findings and the in-hospital mortality rate.

An analysis of the background of the 77 patients who survived and 18 who died reveals that smoking is a significant risk factor affecting the survival of patients with cirrhosis (P < 0.001).

Prediction of in-hospital mortality in patients with decompensated cirrhosis who were hospitalized for 6 months

According to Table 7, the current results demonstrate a strong correlation between CPS and MELD scores and the in-hospital mortality rate. The accuracy of CPS and MELD in predicting in-hospital mortality among hospitalized patients showed no statistically significant difference.

Table 7 . Comparison of CPS and MELD Scores of Hospitalized Patients.

Surviving patients rangeDeceased patients rangeP-value
Blood received25 (37.30)22 (78.60)< 0.001
Plasma received7 (10)14 (50)< 0.001
PCs received10 (14.90)21 (75)< 0.001
FFP received2 ± 1.18 (1–6)2 ± 3.54 (1–14)< 0.001
Need to be admitted2 ± 0.49 (1–2)2.50 ± 3.22 (2–11)< 0.001
Admitted to the ICU4.50 ± 3.56 (2–14)5 ± 3.61(1–15)< 0.001
Total admission time (mo)6 ± 3.21 (3–16)5.50 ± 4.56 (1–20)0.777
MELD score16 (4–43)24 (7–53)< 0.001
CPS8.44 ± 1.82 (5–12)11.71 ± 2.41 (6–15)< 0.001

Values are presented as number (%) or mean ± standard deviation (standard error of the mean)..

CPS, Child-Pugh score; MELD, Model for End-Stage Liver Disease; PCs, packed cells; FFP, frozen fresh plasma; ICU, intensive care unit..



Receiving blood, plasma, packed cells (PCs), and fresh frozen plasma (FFP), as well as requiring admission to the intensive care unit (ICU), all displayed correlations with the in-hospital mortality rate. However, the total duration of hospital admission did not influence the survival outcomes of patients with cirrhosis (P < 0.05).

In the ROC analysis, the CPS had a cut-off value 10.5, with a specificity of 71.1% and a sensitivity of 86.6% (Fig. 1A). The MELD score had a cut-off value of 22, with a specificity of 68% and a sensitivity of 79% (Fig. 1B).

Figure 1. Receiver operating characteristic (ROC) curve analysis for predicting in-hospital mortality in patients with liver cirrhosis: (A) Child-Pugh score, (B) Model for End-Stage Liver Disease (MELD) score.

CPS versus MELD score

Logistic regression analysis identified CPS as a single independent predictor of 6-month in-hospital survival, demonstrating greater specificity and sensitivity than the MELD score (Logistic regression: OR = 2.3, standard error = 0.0189; P < 0.001).

HE and GIB are among the most severe complications associated with liver cirrhosis, potentially leading to death if not properly managed.17,18

HE, a major complication of cirrhosis, can manifest in a range from subclinical alterations to coma. It is classified into three types: Type A results from acute liver failure; Type B is caused by portal-systemic shunting without intrinsic liver disease; and Type C occurs in patients with underlying cirrhosis.19,20

The development of a GIB episode significantly contributes to morbidity and mortality among patients with liver cirrhosis. This may be associated with various factors including the degree of liver dysfunction (as indicated by CPS and MELD scores), the bleeding source (such as esophageal or gastric varices, gastric or duodenal ulcers, hemorrhagic gastritis, esophagitis, or Mallory-Weiss syndrome), characteristics of the bleeding (including severity and presentation form), compensated status, concurrent HCC, and the presence of other underlying conditions.21,22

This study analyzed the complications most closely associated with mortality, including HE and GIB, in patients with liver cirrhosis. It focused on the relationship between these complications and the severity of liver dysfunction, as assessed by the CPS and MELD scoring systems.

This study included 95 patients with cirrhosis aged over 18 years; among them, 25.30% exhibited HE, and 38.90% experienced GIB. During the 6-month study period, 18 patients (19%) died. The most significant finding was the strong correlation between the in-hospital mortality rate and certain complications of cirrhosis, such as HE (42.90% mortality, P = 0.011) and GIB (57.10% mortality, P = 0.019). Thus, HE and GIB were identified as the most lethal complications among hospitalized patients with liver cirrhosis. These findings are consistent with previous reports.2325

The cause of death for all patients was linked to the occurrence of three simultaneous liver cirrhosis complications, resulting in a mortality rate of 100%. The concurrent presence of HE, GIB, and HRS in patients was notably infrequent, likely reflecting advancements in prevention and improved management of these complications.26 However, when these complications do co-occur, they can lead to catastrophic outcomes in patients with cirrhosis, with a mortality rate of 100%. The current study indicated that ascites (73.70%), SBP (57.9%), and GIB (38.90%) were the most prevalent complications observed in patients with cirrhosis. The co-occurrence of these complications with HE is particularly lethal, with a mortality rate of 100%. GIB creates an environment conducive to bacterial infections in ascitic fluid, thereby establishing a connection between GIB and SBP. SBP, an infection of the ascitic fluid, is now recognized as a severe bacterial infection that can lead to renal failure in patients with cirrhosis.27 Renal failure development is strongly associated with a very poor short-term prognosis.28 Factors independently predictive of renal failure include the severity of bleeding, as evidenced by hypovolemic shock and high blood transfusion requirements.27,29

Another important finding was the relationship between laboratory markers in ascitic fluid (total cell and RBC count) and the in-hospital mortality rate in patients with cirrhosis. Previous studies have indicated that a RBC count of 10,000 cells/mL or greater characterizes hemorrhagic ascites, which is associated with increased morbidity and mortality. In patients with liver cirrhosis, hemorrhagic ascites may result from acute or chronic hemorrhage due to ruptured lymphatics or varices, a ruptured HCC lesion, or leakage from the splanchnic vascular bed. Consequently, the occurrence of hemorrhagic ascites often necessitates extensive blood transfusions.30,31 Over time, these conditions can lead to patient death. Our findings concur with these observations and demonstrate that the volume of blood, plasma, PCs, and FFP received, along with the need for ICU admission, all correlated positively with the in-hospital mortality rate. It is likely that the need for blood is driven by severe complications such as renal failure or hemorrhagic ascites. Therefore, our results, although seemingly promising, actually reflect critical conditions and fatal outcomes in surviving patients with cirrhosis.

This study also demonstrated positive correlations between INR, PT, PTT, bilirubin, liver enzymes (ALT, AST, and ALK-P), and the in-hospital mortality rate. These findings are reasonable based on the definition of the MELD and CPS32,33 and the fact that these serum markers are considered to be criteria for assessing the severity of liver cirrhosis.34,35

A prognostic evaluation of patients with liver cirrhosis is crucial for the decision-making process in clinical settings, but it presents a significant challenge for clinicians. In this context, the CPS and the MELD offer tools to more accurately assess the severity of liver disease and identify patients with cirrhosis at risk of mortality.8,9 The CPS is a vital prognostic scoring system for patients with cirrhosis and plays a key role in the current organ allocation policy. However, the traditional model has several limitations, including the subjectivity of some parameters and its inadequate ability to discriminate in long-term prognosis.36 Subsequently, the MELD scoring system was developed to assess the prognosis of patients undergoing TIPSS procedures and was later extended to evaluate short-term survival in patients at various stages of liver cirrhosis.

Several studies have shown that the MELD score performs at least as well as the CPS in predicting patient outcomes.3739 However, other investigations have produced contrasting results. One prospective study enrolled 110 consecutive patients with decompensated cirrhosis of the liver, identified either clinically or radiologically. The hospital monitored these patients throughout their stay. Initially, patients were categorized into groups A, B, and C based on the CPS. The MELD score was also calculated for each patient. The study’s endpoints were the length of hospital stay and the rate of in-hospital mortality. The findings indicated that the MELD score did not surpass the CPS in predicting the short-term prognosis of patients with cirrhosis.40 Consistent with these findings, another prospective study assessed the CPS and recalibrated CPS, along with the MELD score at admission, to evaluate their effectiveness in distinguishing between rebleeding and death in the hospital. This study found that the recalibrated CPS, original CPS, and MELD score were effective indicators for predicting in-hospital mortality among patients with bleeding esophageal varices due to alcoholic cirrhosis.41 In a recent study conducted by a tertiary healthcare center in India, the CPS, MELD, and MELD-Na scores of 171 patients with end-stage liver disease were obtained upon admission. The C-statistics of the three scores for predicting 3-month mortality were evaluated and compared. The results demonstrated that the CPS, MELD, and MELD-Na scores all had excellent predictive power for mortality at 3 months. Among these, the CPS was found to be the most accurate in predicting 3-month mortality.42

In this study, we compared the prognostic abilities of the CPS and the MELD score in assessing the 6-month survival prognosis for patients with cirrhosis. The CPS demonstrated discriminative ability between patients who survived and those who died within the 6-month study period, exhibiting excellent diagnostic accuracy in predicting short-term survival. In contrast, some studies have suggested that the MELD scoring system has greater prognostic ability for the survival of patients with liver cirrhosis.43 The rationale for this claim is that the MELD model lacks many of the limitations of the CPS and is a well-recognized predictor of survival in patients with liver disease44 and outcomes post-liver transplantation.45 Additionally, it includes the serum creatinine level, which measures renal function in patients with liver disease.44 However, some researchers advocate for further improvements to the MELD model, such as the inclusion of sodium levels — termed “Sodium-MELD” or “MELD-Na” — which may provide a distinct advantage over the CPS.4648 Moreover, some studies question whether MELD is superior to CPS in predicting survival in patients with chronic liver disease. They propose that using both MELD and CPS as complementary tools could be beneficial in evaluating the progressive worsening of the clinical condition in patients with cirrhosis.38,43,49

In Conclusion, the MELD scoring system utilizes bilirubin, INR, and creatinine levels, whereas the CPS incorporates clinical complications such as HE and ascites, along with para-clinical findings. Indeed, both the CPS and MELD scores have their own significance. However, our results indicate that the CPS is a more accurate predictor of in-hospital mortality in patients with cirrhosis. The CPS also demonstrates greater effectiveness as a tool for assessing long-term prognosis, especially in a broad context. Therefore, we advocate for the continued use of the CPS in the routine clinical assessment of individual liver diseases. Furthermore, the predictive accuracy of both the CPS and the Meld score could be enhanced by including variables that reflect the circulatory dysfunction seen in cirrhotic liver disease. This could lead to the development of a new scoring system that offers a more precise and reliable method for evaluating the prognosis of patients with liver disease.

We thank Ahvaz Jundishapur University of Medical Sciences for the financial support.

This work was financially supported by Ahvaz Jundishapur University of Medical Sciences (GP94029).

No potential conflict of interest relevant to this article was reported.

  1. Yoshiji H, Nagoshi S, Akahane T, Asaoka Y, Ueno Y, Ogawa K, et al. Evidence-based clinical practice guidelines for Liver Cirrhosis 2020. J Gastroenterol. 2021;56:593-619.
    Pubmed KoreaMed CrossRef
  2. Reiberger T. The value of liver and spleen stiffness for evaluation of portal hypertension in compensated cirrhosis. Hepatol Commun. 2022;6:950-64.
    Pubmed KoreaMed CrossRef
  3. Nadim MK, Durand F, Kellum JA, Levitsky J, O'Leary JG, Karvellas CJ, et al. Management of the critically ill patient with cirrhosis: a multidisciplinary perspective. J Hepatol. 2016;64:717-35.
    Pubmed CrossRef
  4. Olson JC, Karvellas CJ. Critical care management of the patient with cirrhosis awaiting liver transplant in the intensive care unit. Liver Transpl. 2017;23:1465-76.
    Pubmed CrossRef
  5. Mahmud N, Sundaram V, Kaplan DE, Taddei TH, Goldberg DS. Grade 1 acute on chronic liver failure is a predictor for subsequent grade 3 failure. Hepatology. 2020;72:230-9.
    Pubmed KoreaMed CrossRef
  6. Wang Z, Wu YF, Yue ZD, Zhao HW, Wang L, Fan ZH, et al. Comparative study of indocyanine green-R15, Child-Pugh score, and model for end-stage liver disease score for prediction of hepatic encephalopathy after transjugular intrahepatic portosystemic shunt. World J Gastroenterol. 2021;27:416-27.
    Pubmed KoreaMed CrossRef
  7. Angermayr B, Cejna M, Karnel F, Gschwantler M, Koenig F, Pidlich J, et al. Child-Pugh versus MELD score in predicting survival in patients undergoing transjugular intrahepatic portosystemic shunt. Gut. 2003;52:879-85.
    Pubmed KoreaMed CrossRef
  8. Demirtas CO, D'Alessio A, Rimassa L, Sharma R, Pinato DJ. ALBI grade: evidence for an improved model for liver functional estimation in patients with hepatocellular carcinoma. JHEP Rep. 2021;3:100347.
    Pubmed KoreaMed CrossRef
  9. Kaur H, SinGla G, SinGla B. Comparison of homocysteine levels in various liver diseases. J Clin Diagn Res. 2019;13:BC01-3.
    CrossRef
  10. Nafeh HM, Abdelmoneim SS, Hassany SM, Swifee YM. Risk factors and outcome in ICU patients with end-stage liver disease. J Arab Soc Med Res. 2014;9:33-9.
    CrossRef
  11. Kamath PS, Kim WR; Advanced Liver Disease Study Group. The model for end-stage liver disease (MELD). Hepatology. 2007;45:797-805.
    Pubmed CrossRef
  12. Leise MD, Kim WR, Kremers WK, Larson JJ, Benson JT, Therneau TM. A revised model for end-stage liver disease optimizes prediction of mortality among patients awaiting liver transplantation. Gastroenterology. 2011;140:1952-60.
    Pubmed KoreaMed CrossRef
  13. Morando F, Maresio G, Piano S, Fasolato S, Cavallin M, Romano A, et al. How to improve care in outpatients with cirrhosis and ascites: a new model of care coordination by consultant hepatologists. J Hepatol. 2013;59:257-64.
    Pubmed CrossRef
  14. Simons-Linares CR, Romero-Marrero C, Jang S, Bhatt A, Lopez R, Vargo J, et al. Clinical outcomes of acute pancreatitis in patients with cirrhosis. Pancreatology. 2020;20:44-50.
    Pubmed CrossRef
  15. Papatheodoridis GV, Cholongitas E, Dimitriadou E, Touloumi G, Sevastianos V, Archimandritis AJ. MELD vs Child-Pugh and creatinine-modified Child-Pugh score for predicting survival in patients with decompensated cirrhosis. World J Gastroenterol. 2005;11:3099-104.
    Pubmed KoreaMed CrossRef
  16. Schepke M, Roth F, Fimmers R, Brensing KA, Sudhop T, Schild HH, et al. Comparison of MELD, Child-Pugh, and Emory model for the prediction of survival in patients undergoing transjugular intrahepatic portosystemic shunting. Am J Gastroenterol. 2003;98:1167-74.
    Pubmed CrossRef
  17. Poordad FF. Presentation and complications associated with cirrhosis of the liver. Curr Med Res Opin. 2015;31:925-37.
    Pubmed CrossRef
  18. Fouad TR, Abdelsameea E, Abdel-Razek W, Attia A, Mohamed A, Metwally K, et al. Upper gastrointestinal bleeding in Egyptian patients with cirrhosis: post-therapeutic outcome and prognostic indicators. J Gastroenterol Hepatol. 2019;34:1604-10.
    Pubmed CrossRef
  19. Lima LCD, Miranda AS, Ferreira RN, Rachid MA, Simões E Silva AC. Hepatic encephalopathy: lessons from preclinical studies. World J Hepatol. 2019;11:173-85.
    Pubmed KoreaMed CrossRef
  20. Sundaram V, Shaikh OS. Hepatic encephalopathy: pathophysiology and emerging therapies. Med Clin North Am. 2009;93:819-36; , vii.
    Pubmed CrossRef
  21. Cheng R, Tan N, Kang Q, Luo H, Chen H, Pan J, et al. High-density lipoprotein cholesterol is a predictor of survival in cirrhotic patients with acute gastrointestinal bleeding: a retrospective study. BMC Gastroenterol. 2020;20:381.
    Pubmed KoreaMed CrossRef
  22. Zhao Y, Ren M, Lu G, Lu X, Yin Y, Zhang D, et al. The prognosis analysis of liver cirrhosis with acute variceal bleeding and validation of current prognostic models: a large scale retrospective cohort study. Biomed Res Int. 2020;2020:7372868.
    Pubmed KoreaMed CrossRef
  23. del Olmo JA, Peña A, Serra MA, Wassel AH, Benages A, Rodrigo JM. Predictors of morbidity and mortality after the first episode of upper gastrointestinal bleeding in liver cirrhosis. J Hepatol. 2000;32:19-24.
    Pubmed CrossRef
  24. Hung TH, Lee HF, Tseng CW, Tsai CC, Tsai CC. Effect of proton pump inhibitors in hospitalization on mortality of patients with hepatic encephalopathy and cirrhosis but no active gastrointestinal bleeding. Clin Res Hepatol Gastroenterol. 2018;42:353-9.
    Pubmed CrossRef
  25. Aires FT, Ramos PT, Bernardo WM. Efficacy of lactulose in the prophylaxis of hepatic encephalopathy in cirrhotic patients presenting gastrointestinal bleeding. Rev Assoc Med Bras (1992). 2016;62:243-7.
    Pubmed CrossRef
  26. Sharma P, Agrawal A, Sharma BC, Sarin SK. Prophylaxis of hepatic encephalopathy in acute variceal bleed: a randomized controlled trial of lactulose versus no lactulose. J Gastroenterol Hepatol. 2011;26:996-1003.
    Pubmed CrossRef
  27. Rimola A, García-Tsao G, Navasa M, Piddock LJ, Planas R, Bernard B, et al. Diagnosis, treatment and prophylaxis of spontaneous bacterial peritonitis: a consensus document. International Ascites Club. J Hepatol. 2000;32:142-53.
    Pubmed CrossRef
  28. Cárdenas A, Ginès P, Uriz J, Bessa X, Salmerón JM, Mas A, et al. Renal failure after upper gastrointestinal bleeding in cirrhosis: incidence, clinical course, predictive factors, and short-term prognosis. Hepatology. 2001;34:671-6.
    Pubmed CrossRef
  29. Boustany A, Rahhal R, Onwuzo S, Almomani A, Boustany T, Kumar P, et al. Cirrhotic patients on proton pump inhibitors are at a twofold risk of spontaneous bacterial peritonitis independently of gastrointestinal bleeding: a population-based retrospective study. Ann Gastroenterol. 2023;36:327-32.
    Pubmed KoreaMed CrossRef
  30. Falleti E, Cmet S, Cussigh AR, Salvador E, Bitetto D, Fornasiere E, et al. Recurrent and treatment-unresponsive spontaneous bacterial peritonitis worsens survival in decompensated liver cirrhosis. J Clin Exp Hepatol. 2021;11:334-42.
    Pubmed KoreaMed CrossRef
  31. Urrunaga NH, Singal AG, Cuthbert JA, Rockey DC. Hemorrhagic ascites. Clinical presentation and outcomes in patients with cirrhosis. J Hepatol. 2013;58:1113-8.
    Pubmed KoreaMed CrossRef
  32. Durand F, Valla D. Assessment of the prognosis of cirrhosis: Child-Pugh versus MELD. J Hepatol. 2005;42 Suppl(1):S100-7.
    Pubmed CrossRef
  33. European Association for the Study of the Liver. EASL clinical practice guidelines on the management of ascites, spontaneous bacterial peritonitis, and hepatorenal syndrome in cirrhosis. J Hepatol. 2010;53:397-417.
    Pubmed CrossRef
  34. Liu W, Zheng J, Xing R. Clinical significance of a scoring formula of liver injury for the preoperative evaluation of patients with liver cirrhosis. Eur J Gastroenterol Hepatol. 2014;26:95-100.
    Pubmed CrossRef
  35. Zou D, Qi X, Zhu C, Ning Z, Hou F, Zhao J, et al. Albumin-bilirubin score for predicting the in-hospital mortality of acute upper gastrointestinal bleeding in liver cirrhosis: a retrospective study. Turk J Gastroenterol. 2016;27:180-6.
    Pubmed CrossRef
  36. Adler M, Verset D, Bouhdid H, Bourgeois N, Gulbis B, Le Moine O, et al. Prognostic evaluation of patients with parenchymal cirrhosis. Proposal of a new simple score. J Hepatol. 1997;26:642-9.
    Pubmed CrossRef
  37. Forman LM, Lucey MR. Predicting the prognosis of chronic liver disease: an evolution from child to MELD. Mayo End-stage Liver Disease. Hepatology. 2001;33:473-5.
    Pubmed CrossRef
  38. Mylavarapu M, Kalpeshbhai PN, Hien VTT, Patel P, Kahlon P, Minhas A, et al. Comparison of the prognostic value of the Child Pugh and MELD scoring systems in cirrhosis -a systematic review. J Critical Care & Emerg Med. 2022;1:1-7.
    CrossRef
  39. Peng Y, Qi X, Dai J, Li H, Guo X. Child-Pugh versus MELD score for predicting the in-hospital mortality of acute upper gastrointestinal bleeding in liver cirrhosis. Int J Clin Exp Med. 2015;8:751-7.
  40. Shaikh S, Ghani H, Memon S, Baloch GH, Jaffery M, Shaikh K. MELD era: is this time to replace the original Child-Pugh score in patients with decompensated cirrhosis of liver. J Coll Physicians Surg Pak. 2010;20:432-5.
  41. Krige J, Spence RT, Jonas E, Hoogerboord M, Ellsmere J. A new recalibrated four-category Child-Pugh score performs better than the original Child-Pugh and MELD scores in predicting in-hospital mortality in decompensated alcoholic cirrhotic patients with acute variceal bleeding: a real-world cohort analysis. World J Surg. 2020;44:241-6.
    Pubmed CrossRef
  42. Acharya G, Kaushik RM, Gupta R, Kaushik R. Child-Turcotte-Pugh score, MELD score and MELD-Na score as predictors of short-term mortality among patients with end-stage liver disease in Northern India. Inflamm Intest Dis. 2020;5:1-10.
    Pubmed KoreaMed CrossRef
  43. Botta F, Giannini E, Romagnoli P, Fasoli A, Malfatti F, Chiarbonello B, et al. MELD scoring system is useful for predicting prognosis in patients with liver cirrhosis and is correlated with residual liver function: a European study. Gut. 2003;52:134-9.
    Pubmed KoreaMed CrossRef
  44. Arroyo V, Ginès P, Gerbes AL, Dudley FJ, Gentilini P, Laffi G, et al. Definition and diagnostic criteria of refractory ascites and hepatorenal syndrome in cirrhosis. International Ascites Club. Hepatology. 1996;23:164-76.
    Pubmed CrossRef
  45. González E, Rimola A, Navasa M, Andreu H, Grande L, García-Valdecasas JC, et al. Liver transplantation in patients with non-biliary cirrhosis: prognostic value of preoperative factors. J Hepatol. 1998;28:320-8.
    Pubmed CrossRef
  46. 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;11:336-43.
    Pubmed CrossRef
  47. Biggins SW, Rodriguez HJ, Bacchetti P, Bass NM, Roberts JP, Terrault NA. Serum sodium predicts mortality in patients listed for liver transplantation. Hepatology. 2005;41:32-9.
    Pubmed CrossRef
  48. Peng Y, Qi X, Guo X. Child-Pugh versus MELD score for the assessment of prognosis in liver cirrhosis: a systematic review and meta-analysis of observational studies. Medicine (Baltimore). 2016;95:e2877.
    Pubmed KoreaMed CrossRef
  49. Cholongitas E, Papatheodoridis GV, Vangeli M, Terreni N, Patch D, Burroughs AK. Systematic review: the model for end-stage liver disease--should it replace Child-Pugh's classification for assessing prognosis in cirrhosis? Aliment Pharmacol Ther. 2005;22:1079-89.
    Pubmed CrossRef