Austin J Gastroenterol. 2019; 6(2): 1105.
1Physician, Internal Medicine, Hospital Virvi Ramos,Residency in Oncology, Hospital Geral, Caxias do Sul(RS), Brazil
3Medical student, Universidade de Caxias do Sul (UCS),Caxias do Sul (RS), Brazil
4Physician, Titular Professor of Gastroenterology andHepatology, Universidade de Caxias do Sul (UCS), Caxiasdo Sul (RS). Doctorate in Gastroenterology, Departmentof Gastroenterology, Universidade de Sao Paulo (USP),Sao Paulo (SP), Brazil
5Physician, Titular Professor of Gastroenterology andHepatology, Universidade de Caxias do Sul (UCS), Caxiasdo Sul (RS). Doctorate in Gastroenterology, Departmentof Gastroenterology, Universidade de São Paulo (USP),São Paulo (SP), Brazil
6Associate Professor of Gastroenterology and Hepatology,Universidade de Caxias do Sul (UCS), Caxias do Sul(RS). Master’s in Medicine: Hepatology, Department ofHepatology, Universidade Federal de Ciências da Saúdede Porto Alegre (UFCSPA), Porto Alegre (RS), Brazil
*Corresponding author: Jonathan Soldera, AssociateProfessor of Gastroenterology and Hepatology,Universidade de Caxias do Sul (UCS), Caxias do Sul(RS). Master’s in Medicine: Hepatology, Department ofHepatology, Universidade Federal de Ciências da Saúdede Porto Alegre (UFCSPA), Porto Alegre (RS), Brazil
Received: October 31, 2019; Accepted: December 03, 2019; Published: December 10, 2019
Abstract
Background: A particular clinical entity, acute-on-chronic liver failure(ACLF), defined as organ failures associated with decompensated cirrhosiscarries a higher risk of death in the short term. Liver-specific scores have beendeveloped to predict mortality in such population in previous studies.
Design and Setting: Historical cohort study conducted in a mixed publicand private tertiary care teaching hospital.
Methods: Data from medical records from January 2013 to December2014 were obtained by searching the hospital electronic database for codesassociated to liver disease. Paper medical charts were hand-analyzed. Liverspecificscores were calculated and ROC-curves pairwise comparisons wereperformed using DeLong test.
Results: CLIF-SOFA was able to predict mortality in 28, 90 and 365-day,with AUROC of 0.71, 0.75 and 0.66, respectively. CLIF-SOFA was superior toCLIF-C AD/ACLF, MELD and MELD-Na in prediction of 90-day mortality (p ‹0,05). Values of CLIF-SOFA above 11 was able to predict higher mortality for allpatients, with sensitivity of 64%, 50% and 47% and specificity of 72%, 89% and82% for 28, 90 and 365-day mortality, respectively (p ‹ 0,05).
Conclusion: CLIF-SOFA score was superior to other liver-specific scoresfor predicting mortality in a cohort of a mixed public and private teaching hospitalin Brazil, especially in values above 11.
Keywords: Liver cirrhosis; End stage liver disease; Organ dysfunctionscores; Prognosis; Cohort studies
Introduction
Chronic liver injury leads to fibrosis and nodular regeneration,which culminates into cirrhosis, a mostly irreversible condition [1].Such injuries might be caused by several conditions, as viral hepatitis,alcoholic liver disease and non-alcoholic fatty liver disease. Thenatural history of cirrhosis, after it is established, is marked by theprogression from compensated cirrhosis to decompensated cirrhosis(DC). Cirrhosis is the 9th leading cause of death in the West in 2015,according to World Health Organization [2].
DC is the principal cause of hospital admittance in cirrhoticpatients [3-7]. Nevertheless, in the last decade, it has been observedthat the association of organ failures to DC might increase mortalityindependently [8-12]. Therefore, a particular clinical entity, acute-onchronicliver failure (ACLF), has been suggested as the responsiblefor such increase in mortality [10-13]. Score systems were neededto differentiate between DC and ACLF, defining and staging it.The importance of such resides in the fact that while DC translates into progression of the disease, ACLF is an acute event, potentiallyreversible, with a high mortality [14,15].
Organ failure-associated scores, initially developed for intensivecare, have been shown to be better predictors of ACLF-relatedmortality than classic liver-specific scores. Mortality for cirrhoticpatients admitted in the intensive care unit (ICU) with three or moreorgan failures has been shown to be as high as 70% in the first day ofadmission, increasing to around 89% by the third day [15,16]. Thisperception of ACLF has been profoundly shifted by the publication ofthe CANONIC study, a prospective cohort study published in 2013,which translated a score commonly used in the ICU to the ACLFsetting, creating the CLIF-SOFA (Chronic Liver Failure SequentialOrgan Failure Assessment) and dividing ACLF into three categorieswith distinct mortality [17]. Therefore, understanding ACLF hasbecome paramount in order to better understand the gap betweenDC and death.
The purpose of this paper is to analyze the accuracy of CLIF SOFA to predict mortality and compare it to other liver-specificscores in the CD and ACLF setting, in a mixed public and privatetertiary care teaching hospital in Brazil.
Methods
Study population
The study was approved by the research ethics committeeof the hospital on October 20, 2014, under protocol no.35359813.4.0000.5523. A historical cohort study was conducted,analyzing data from hospital charts from January 2013 to December2014. Patients were found by searching through a mixed publicand private teaching hospital electronic database for InternationalClassification of Diseases (ICD-10) codes F10, K70, K70.1, K70.2,K70.3, K71.7, K74, K74.2, K74.3, K74.6, K77. Paper medical chartswere hand-analyzed. Patients over 18 years old with laboratory andimaging data supporting the diagnosis of cirrhosis were included.Patients were excluded if they did not have a diagnosis of cirrhosiswhen the chart was reviewed or had incomplete charts. Dataregarding clinical and laboratory variables were gathered and liverspecificscores were calculated.
Variables
Clinical and laboratorial variables were gathered by analyzingpaper medical charts and electronic laboratory data. Laboratory datais expressed in units used in the hospital. Diagnosis of hepatocellularcarcinoma (HCC) was made using standardized imaging techniques[18]. Diagnosis of Hepatorenal Syndrome were made using thepreviously published criteria for diagnosis [19]. Diagnosis of infectionwas made through a positive culture or neutrophil count in ascitis [20].
MELD and MELD-Na
MELD (Model for End-Stage Liver Disease) [21] and MELD-Na(MELD-Sodium) [22] are scores used to predict 90-day mortalityand are currently used for organ allocation in liver transplantation.They were calculated using an online calculator (MELD: https://www.mdcalc.com/meld-score-model-end-stage-liver-disease-12-older)(MELD-Na: https://www.mdcalc.com/meldna-meld-na-score-livercirrhosis).
CLIF-SOFA
CLIF-SOFA is an adaptation of the SOFA score commonly usedin the intensive care setting, developed by the CANONIC group in2013 and further validated [17] It was calculated using an onlinecalculator developed by the CLIF Research Group (https://www.clifresearch.com/ToolsCalculators.aspx).
ACLF grade
The CLIF-SOFA score is also used to analyze organ failures anddefine the presence of ACLF and its grade [17]. It was calculated usingan online calculator developed by the CLIF Research Group (https://www.clifresearch.com/ToolsCalculators.aspx).
CLIF-C AD/ACLF
CLIF Consortium Acute Decompensation (CLIF-C AD) scoreand CLIF-C ACLF are scores also developed by the CANONIC groupthat predict expected mortality for 30-day, 90-day, 180-day and 365-day for DC and ACLF patients [23]. They were calculated using anonline calculator developed by the CLIF Research Group (https://www.clifresearch.com/ToolsCalculators.aspx). The online calculator,after the result of the presence of ACLF and the value of CLIF-SOFA,automatically analyzes if CLIF-C AD or ACLF applies in each caseand calculates accordingly.
Outcome
Outcome data regarding survival were gathered using hospitalcharts and searching through national death databases (https://www.falecidosnobrasil.org.br/). If the patient had more than one hospitaladmission, data regarding only the first were collected.
Statistical analysis
Statistical analysis was performed using Statistical Package forthe Social Sciences (SPSS) 15.0 and MedCalc. Categorical variablesare described using frequency and continuous variables by mean andstandard deviation. ROC-curves were generated to analyze sensitivityand specificity of the scores and pairwise comparisons were performedusing DeLong test in order to compare scores. Younden index wasused to generate ideal cut-off values, sensitivity and specificity.
Results
Electronic ICD search retrieved 190 hospital admissions. Ofthese, 131 admissions were excluded due to the other diagnosis foradmission than cirrhosis; and 8 admissions were excluded for beingfor the same patients. After chart analysis, 51 patients in their firsthospital admission in the analyzed period were included in the study.Demographic, clinical and laboratorial data are described in Table 1for the study population and for either DC or ACLF. DC was presentin 33 patients, while ACLF in 18 patients.
Table 1: Demographic, clinical and laboratory findings of the study populationand for each acute-on-chronic liver failure (ACLF) grade.
Variable
Study population
Decompensated Cirrhosis
Acute-on-chronic liver failure
(n = 51)
(n=33)
(n=18)
Age (years)*
53 (11)
54 (11)
51 (12)
Leukocytes (10³/mm³)*
8,8 (4,8)
8.1 (4.1)
10.3 (5.9)
Platelets (10³/mm³)*
134 (93)
155 (98)
97(71)
BMI (kg/m²)*
25 (3.6)
25 (3.9)
25 (2.9)
MBP (mmHg)*
75 (14)
75 (15)
75 (14)
Creatinine (mg/dL)*
1.59 (1.1)
0.97 (0.17)
2.7 (1.3)
Urea (mg/dL)*
48 (37)
35 (24)
72 (45)
Sodium (mmol/L)*
137 (5.2)
137 (5.2)
135 (5.2)
PaO2 (mmHg)*
85 (26)
84 (30)
85 (17.2)
AST (U/L)*
125 (157)
104 (103)
163 (223)
ALT (U/L)*
137 (303)
77 (110)
248 (477)
GGT (U/L)*
541 (729)
498 (582)
620 (956)
Alkaline phosphatase (U/L)*
220 (137)
243 (148)
177 (104)
Albumin (g/dL)*
2.0 (1.0)
1.9 (1.7)
2.1 (0.5)
INR*
1.5 (0.6)
1.3 (0.4)
1.8 (0.7)
Bilirubin (mg/dL)*
Total
2.4 (2.1)
2.1 (2.1)
2.9 (2.2)
Direct
1.3 (1.6)
1 (1.5)
1.7 (1.8)
Liver scores*
MELD
15.2 (9.7)
10.4 (5.6)
23.9 (9.6)
MELD-Na
16.6 (10.4)
11.9 (6.7)
25.3 (10.4)
CLIF-SOFA
10.9 (2.4)
10.3 (2.1)
11.9 (2.6)
CLIF-C AD/ACLF
54 (11.5)
49.7 (8.5)
63.1 (11.2)
Sex**
Male
42 (82)
25 (76)
17 (94)
Female
9 (18)
8 (24)
1 (6)
Health Service**
Public
46 (90)
30 (90)
16 (89)
Private
5 (10)
3 (10)
2 (11)
Etiology**
Alcohol
46 (90)
29 (88)
17 (94)
Other
5 (10)
4 (12)
1 (6)
Virus**
Hepatitis B
1 (2)
1 (3)
Hepatitis C
9 (18)
6 (18)
3 (17)
HIV
1 (2)
1 (6)
Hepatocellular carcinoma**
Yes
5 (10)
4 (12)
1 (6)
No
46 (90)
29 (88)
17 (94)
Hepatorenal syndrome**
Yes
6 (12)
1 (3)
5 (28)
No
45 (88)
32 (97)
13 (72)
Infection**
SBP
6 (12)
2 (6)
4 (22)
UTI
30 (59)
20 (61)
10 (56)
RTI
6 (12)
3 (9)
3 (16)
Other
3 (5)
2 (7)
1 (6)
None
6 (12)
6 (17)
Hepatic encephalopathy**
Absent
26 (51)
19 (58)
7 (40)
Present
25 (49)
14 (42)
11 (60)
Grade I
12 (23)
8 (24)
4 (22)
Grade II
4 (8)
2 (6)
2 (11)
Grade III
1 (2)
1 (5)
Grade IV
8 (16)
4 (12)
4 (22)
Survival**
28-day
37 (72)
26 (78)
11 (61)
90-day
29 (57)
23 (69)
6 (33)
365-day
16 (31)
13 (39)
3 (17)
BMI: Body Mass Index; MBP: Mean Blood Pressure; AST: Aspartate Transaminase; ALT: Alanine Transaminase; GGT: Gamma-Glutamyl Transferase; INR: International Normalized Ratio; MELD: Model For End-Stage Liver Disease; MELD-Na: Modified Model Including Sodium; CLIF-SOFA: Chronic Liver Failure Sequential Organ Failure Assessment; CLIF-C AD/ACLF: CLIF Consortium Acute Decompensation/Acute-On-Chronic Liver Failure; SBP: Spontaneous Bacterial Peritonitis; UTI: Urinary Tract Infection; RTI: Respiratory Tract Infection.
*Mean (standard deviation); **Frequency (%).
Table 1: Demographic, clinical and laboratory findings of the study populationand for each acute-on-chronic liver failure (ACLF) grade.
Analysis comparing the scores CLIF-C AD and CLIF-C ACLF,CLIF-SOFA, MELD and MELD-Na were made for 28, 90 and365-day survival. Table 2 presents the data regarding AUROCcomparisons for all patients, showing superiority for CLIF-SOFAscore over other scores (Figure 1). Table 3 presents the data regarding AUROC comparisons for DC patients (Figure 2) and Table 4 forACLF patients (Figures 3), showing discrete or absent superiority forCLIF-SOFA score over the other liver-specific scores when patientswere stratified to either DC or ACLF. CLIF-SOFA was able to predictmortality in 28, 90 and 365-day, with AUROC of 0.71, 0.75 and 0.66,respectively. CLIF-SOFA was superior to CLIF-C AD/ACLF, MELDand MELD-Na in prediction of 90-day mortality (p ‹ 0,05).
Table 2: AUROC for DC and ACLF patients.
Variable
AUROC (95% CI)
p value (vs. CLIF-SOFA)
28-day
90-day
365-day
CLIF-SOFA
0.71 (0.57-0.83)
0.75 (0.61-0.86)
0.66 (0.52-0.79)
CLIF-C AD/ACLF
0.52 (0.38-0.67)
0.51 (0.36-0.65)
0.56 (0.41-0.69)
p=0.11
p=0.01
p=0.36
MELD
0.54 (0.39-0.68)
0.50 (0.36-0.65)
0.52 (0.38-0.66)
p=0.11
p=0.05
p=0.21
MELD-Na
0.57 (0.41-0.71)
0.54 (0.40-0.68)
0.55 (0.40-0.69)
p=0.16
p=0.02
p=0.29
AUROC: Area under the Receiver Operator Curve; MELD: Model for End-Stage Liver Disease; MELD-Na: Modified Model Including Sodium; CLIF-SOFA: Chronic Liver Failure Sequential Organ Failure Assessment; CLIF-C AD/ACLF: CLIF Consortium Acute Decompensation/acute-on-chronic liver failure; DC: Decompensated cirrhosis.
Table 2: AUROC for DC and ACLF patients.
Table 3: AUROC for DC patients.
Variable
AUROC (95% CI)
p value (vs. CLIF-SOFA)
28-day
90-day
365-day
CLIF-SOFA
0.61 (0.43-0.88)
0.67 (0.49-0.83)
0.50 (0.32-0.68)
CLIF-C AD
0.53 (0.34-0.70)
0.59 (0.40-0.76)
0.50 (0.32-0.68)
p=0.66
p=0.59
p=0.96
MELD
0.56 (0.38-0.73)
0.70 (0.52-0.85)
0.60 (0.42-0.77)
p=0.78
p=0.87
p=0.43
MELD-Na
0.57 (0.38-0.74)
0.54 (0.36-0.72)
0.52 (0.34-0.70)
p=0.72
p=0.46
p=0.86
AUROC = Area under the Receiver Operator Curve; MELD = Model for End-Stage Liver Disease; MELD-Na =
Modified Model Including Sodium; CLIF-SOFA = Chronic Liver Failure Sequential Organ Failure Assessment; CLIF-C AD = CLIF Consortium Acute Decompensation; DC = Decompensated cirrhosis.
Table 3: AUROC for DC patients.
Table 4: AUROC for ACLF patients.
Variable
AUROC (95% CI)
p value (vs. CLIF-SOFA)
28-day
90-day
365-day
CLIF-SOFA
0.76 (0.81-0.92)
0.76 (0.50-0.92)
0.92 (0.69-0.99)
CLIF-C ACLF
0.60 (0.35-0.82)
0.69 (0.43-0.88)
0.57 (0.32-0.80)
p=0.41
p=0.48
p=0.26
MELD
0.53 (0.28-0.76)
0.61 (0.35-0.82)
0.53 (0.28-0.76)
p=0.22
p=0.48
p=0.07
MELD-Na
0.51 (0.27-0.75)
0.61 (0.35-0.82)
0.55 (0.30-0.78)
p=0.23
p=0.48
p=0.09
AUROC: Area under the Receiver Operator Curve; MELD: Model for End-Stage Liver Disease; MELD-Na: Modified Model Including Sodium; CLIF-SOFA: Chronic Liver Failure Sequential Organ Failure Assessment; LIF-C AD: CLIF Consortium acute-on-chronic liver failure; ACLF: acute-on-chronic liver failure.
Table 4: AUROC for ACLF patients.
Figure 1: ROC curves for 28, 90 and 365-day survival for all patients.
Figure 1: ROC curves for 28, 90 and 365-day survival for all patients.
Figure 2: ROC curves for 28, 90 and 365-day survival for DC patients.
Figure 2: ROC curves for 28, 90 and 365-day survival for DC patients.
Figure 3: ROC curves for 28, 90 and 365-day survival for ACLF patients.
Figure 3: ROC curves for 28, 90 and 365-day survival for ACLF patients.
Table 5 shows the ideal cut-off for predicting mortality using theROC curve for each score and time frame, for all patients, DC andACLF patients. Values of CLIF-SOFA above 11 was able to predicthigher mortality for all patients, with sensitivity of 64%, 50% and 47%and specificity of 72%, 89% and 82% for 28, 90 and 365-day mortality,respectively (p ‹ 0,05). CLIF-SOFA was able to predict mortality inevery time frame for all patients and ACLF patients. CLIF-SOFAvalues above 11 were associated to higher mortality.
Table 5: Ideal cut-offs for each score and time interval.
Variable
Survival - hazard ratio (95% CI)
28-day
90-day
365-day
CLIF-SOFA
All patients
> 11
> 12
> 11
Sn 64% Sp 72%
Sn 50% Sp 89%
Sn 47% Sp 82%
p < 0.01
p < 0.01
p = 0.03
ACLF patients
> 11
> 12
> 8
Sn 85% Sp 63%
Sn 58% Sp 83%
Sn 100% Sp 66%
p = 0.01
p = 0.02
p <0.01
DC patients
> 10
> 11
> 9
Sn 57% Sp 65%
Sn 50% Sp 82%
Sn 47% Sp 35%
p = 0.34
p = 0.1
p = 0.9
CLIF-C AD/ACLF
All patients
> 54
> 54
> 62
Sn 64% Sp 62%
Sn 54% Sp 62%
Sn 29% Sp 88%
p = 0.76
p = 0.89
p = 0.48
ACLF patients
> 61
> 56
> 56
Sn 57% Sp 72%
Sn 41% Sp 100%
Sn 33% Sp 100%
p = 0.51
p = 0.13
p = 0.73
DC patients
> 54
> 46
> 39
Sn 57% Sp 80%
Sn 60% Sp 73%
Sn 21% Sp 92%
p = 0.84
p = 0.45
p = 0.94
MELD
All patients
> 27
> 8
> 8
Sn 28% Sp 89%
Sn 40% Sp 82%
Sn 61% Sp 17%
p = 0.67
p = 0.91
p = 0.77
ACLF patients
> 27
> 21
> 21
Sn 57% Sp 63%
Sn 50% Sp 100%
Sn 40% Sp 100%
p = 0.84
p = 0.43
p = 0.82
DC patients
> 8
> 8
> 8
Sn 57% Sp 69%
Sn 70% Sp 78%
Sn 57% Sp 78%
p = 0.6
p = 0.06
p = 0.32
MELD-Na
All patients
> 8
> 27
> 26
Sn 85% Sp 35%
Sn 27% Sp 89%
Sn 26% Sp 88%
p = 0.41
p = 0.58
p = 0.55
ACLF patients
> 21
> 21
> 21
Sn 42% Sp 81%
Sn 41% Sp 100%
Sn 33% Sp 100%
p = 0.9
p = 0.42
p = 0.72
DC patients
> 8
> 15
> 10
Sn 85% Sp 46%
Sn 80% Sp 39%
Sn 57% Sp 57%
p = 0.54
p = 0.67
p = 0.8
MELD: Model for End-Stage Liver Disease; MELD-Na: Modified Model Including Sodium; CLIF-SOFA: Chronic Liver Failure Sequential Organ Failure Assessment; CLIF-C AD/ACLF: CLIF Consortium Acute Decompensation/acute-on-chronic liver failure; ACLF: Acute-on-chronic liver failure; DC: decompensated cirrhosis; Sn: Sensitivity; Sp: Specificity.
Table 5: Ideal cut-offs for each score and time interval.
Discussion
The definition of ACLF has been improved ever since the firstsupplement dedicated to this subject [9,24-29] integrating intensivecare and Hepatology. This was largely due to the publication ofCANONIC study, responsible for the current definition of this entityin the West [17]. A different set of criteria developed by the Asia-Pacific Association for the Study of the Liver has been described,but it appears to be inferior to the one developed by the EASL-CLIF[30,31].
In the past couple of decades, several studies have been publishedregarding the clinical nature of ACLF, but they have been underminedbecause of the lack of a consensual definition of ACLF. In this study,we analyzed the role of the definitions and scores proposed by theEASL-CLIF (European Association for the Study of the Liver -Chronic Liver Failure) consortium, comparing their accuracy forsurvival [17].
In this study, the prevalence of ACLF was 35.3% (grade 1 in 13.7%,grade 2 in 19.6% and grade 3 in 2%). These results are not very closeto those obtained in the CANONIC study, with an ACLF prevalenceof 22.6% [17], or in a similar Brazilian study, with a prevalence of24% [32], or in a similar North-American study, with a prevalence of26.4% [33], where grade 1 was 11.0%, 17.7% and 12.8%, respectively.
The ACLF group showed a 28-day mortality of 39% (29, 40 and100% in ACLF grades 1, 2 and 3, respectively), compared to 22% innon-ACLF patients. In the CANONIC study, 28-day mortality was33.9%, significantly lower than that reported here [17], whereas theBrazilian study showed very similar mortality rates of 39% [32].
The superiority of CLIF-SOFA has been demonstrated for shorttermfor alcoholic cirrhosis in a previous study, in comparisonto other liver-specific scores [33]. It has been demonstrated to besuperior to CLIF-C AD/ACLF, MELD and MELD-Na in otherprevious study, even for extra-hepatic insults [34]. It has been studiedeven in alcoholic hepatitis, showing superiority to even scores that are applied specifically for this condition [35,36].
A major drawback of our study was the small sample size, whichwas probably due to the fact that the hospital is not a referral centerfor liver diseases. Nonetheless, the complete data gathered allowedfor an in-depth study of the population and provided more dataregarding the prognosis and treatment of cirrhosis in Brazil.
Conclusion
In conclusion, CLIF-SOFA score was superior to other liverspecificscores for predicting mortality in a cohort of a mixed publicand private teaching hospital in Brazil, especially in values above 11.An increase in the use of these evidence-based scores may help defineoptimal diagnostic and therapeutic strategies for ACLF.
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Citation: Grochot RM, Luz LB, Garcia R, Balbinot RA, Balbinot SS and Soldera J. Clif-Sofa is Superior to OtherLiver-Specific Scores for Predicting Mortality in Acute-on-Chronic Liver Failure and Decompensated Cirrhosis.Austin J Gastroenterol. 2019; 6(2): 1105.
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