ACLF is a serious condition associated with a high mortality rate which is 15 times higher as compared to patients with acute decompensation without ACLF [1].
Therefore, it is critical to stratify patients according to prognosis in order to monitor treatment responsiveness, determine emergency for transplantation, and decide allocation in the ICU.
In the present study, we have compared the performance of the conventional liver-specific scores (Child-Pugh and MELD) to the widely used international prognostic scores (CLIF-C OF, CLIF-C ACLF, CLIF-SOFA, and CLIF-C AD) in the prediction of in-hospital mortality of patients with ACLF.
Baseline characteristics of the studied patients
The age and gender of the studied patients were comparable to that of the CANONIC study, mean age of 53.9 ± 12.8 vs. 56.0 ± 11.0 years, and 71.1% males vs. 64.4%, respectively [1]. Meanwhile, our studied patients were older than those in the study by Dihman et al., who reported a mean age of 46.0 ± 13.0 years [22].
In our study, HCV was the most common cause of chronic liver disease (57.8%). This is consistent with the fact that Egypt has the highest HCV prevalence in the world, which represents the main etiology of chronic liver disease among the Egyptian population [23]. This figure is higher than that reported by Moreau et al. (13% for HCV and 9% for HCV and alcohol) [1] and Dihman et al. (10% for HCV with alcohol) [22]. In both studies, alcohol was the main etiology of chronic liver disease (60.3% and 58%, respectively). Other identifiable etiologies of the pre-existing liver disease in our study came with variable degrees of agreement with others reported in the literature. Hepatitis B was similar (5.2%) to the Dihman et al. study (6%). Autoimmune hepatitis was higher in the Dihman et al. study (6%) compared to ours (3.6%). The etiology could not be identified in 32.1% patients in our study compared to 14% in the study by Dihman et al. However, cryptogenic cirrhosis is the second most common etiology in both studies. We believe that the high rate of unidentifiable etiology of the pre-existing cirrhosis in our study could be referred considerably to nonalcoholic fatty liver disease, an important condition for which we could not stand on a confirmed diagnosis at such a late stage of cirrhosis. Conclusively, these differences in the etiologic profile of cirrhosis in ACLF reflect the etiology of cirrhosis in the respective countries. Alcoholic cirrhosis constitutes 50–70% of all the underlying liver diseases of ACLF in the western countries, whereas viral hepatitis-related cirrhosis constitutes about 10–15% of all the cases [24,25,26]. However, in most of the Asian countries, HBV constitutes 70% and alcohol only about 15% of all the etiologies [27]. In contrast, HCV-related cirrhosis constitutes the majority in Egyptian patients [23].
In the same stream, the acute insult precipitating ACLF was variable among different studies. In our cohort, sepsis represented the most common precipitating factor (49.8%). We have no definite explanation for such a high rate. However, this might be attributed to the immune derangement commonly found in patients with advanced stages of cirrhosis, which makes them more prone to bacterial infections. Similarly, Dhiman et al. reported that bacterial infections represented 66% of the ACLF precipitating factors [22]. The CANONIC study reported a lower rate of bacterial infections (32.6%) [1]. It is to be noted that the APASL definition does not include infection/sepsis as the acute precipitating event of ACLF [28].
Acute GI bleeding represented the second most common precipitating factor in our study (9.2%). Negligence, missing variceal screening programs, and/or non-adherence to portal pressure decompressing medications represented the main factors associated with acute variceal hemorrhage in this group of patients. Moreau et al. reported a comparable rate of variceal hemorrhage (13.2%) [1]. Meanwhile, Dhiman et al. reported a lower rate of 4% [22]. It is noteworthy that both studies reported a high proportion of active alcoholism (40% and 24.5%, respectively), which was not encountered in any of our studied patients. Dihman et al. also reported a higher incidence of autoimmune hepatitis flares (8%) compared to our rate of exacerbation (3.2%) and a higher rate of HEV (2%) compared to ours (0.4%) [22]. No precipitating factor could be identified in 30.9% of the patients in our study, which is lower than the figure reported by Moreau et al. (43.6%) [1].
Risk factors for mortality
The 28-day mortality in ACLF ranged between 30 and 40% [6]. The estimated global 90-day mortality was 58%, with some relative regional variations. South America had the highest rate (73%), followed by South Asia (68%) [29]. The reported mortality rate in our study was 74.3%. These variations might be attributed to the variance in the definition of ACLF and guidelines used in these different areas, the heterogeneity of patients’ characteristics and ethnicities, and the relative variation in the reversibility of the acute precipitating insult besides the ACLF grade. Another important point that could influence the mortality rate is the availability of salvage liver transplantation for patients who develop progressive irreversible deterioration. The candidacy for liver transplantation becomes more sophisticated and perplexing when patients develop intractable sepsis, a relatively common condition that could contraindicate liver transplantation. In addition, liver transplantation would be declined for patients who develop kidney failure, the most common organ failure in ACLF, unless a combined liver-kidney transplant is available. Adding to that, most patients with advanced ACLF grade are not sufficiently stable to undergo liver transplantation. Indeed, all these factors collectively could influence the mortality rates among different studies and regions. Unfortunately, many of these factors have been reported in many of our patients, including intractable sepsis, advanced ACLF grade, donor unavailability, and improper conditions for receiving liver transplants. This could explain the higher mortality rate disclosed in our cohort.
In univariate analysis, the Child-Pugh score and class, CLIF-AD grades, and the MELD, CLIF-C AD, CLIF-C OF, CLIF-SOFA, and CLIF-ACLF scores were significantly worse in patients who were deceased at discharge.
Age significantly predicted mortality in our study as well as in five previous studies [30,31,32,33,34]. Albumin was significantly lower in the deceased group (2.3 vs. 2.7, P<0.0001). This is similar to the finding by Sun et al. (2.8 vs. 3.1 P<0.001) [34]. In our study, the white blood cell count was significantly higher in the deceased group (11.3 vs. 15.2, P<0.0001). The same was reported in the study by Sun et al.; survivors had a significantly lower WBCs count (6.7 vs. 8.1, P=0.036) [34]. We noted that platelets were significantly higher in the group of survivors. This finding was reported in four previous studies [34,35,36,37]. In the current study, INR was significantly lower in the group of survivors. This was also reported in four previous studies [34, 37,38,39]. It is noteworthy that although bilirubin is an important component of these scores, it did not show statistical significance between both groups. This finding was replicated in six previous studies [34,35,36,37,38, 40].
It is also to be noted that the total stay in ICU was significantly shorter in the deceased group (6.8 vs. 10.8, P<0.0001) and the total hospital stay was not statistically significant regarding mortality.
Multivariate analysis, using Cox regression, revealed that Child-Pugh (class C vs. B) and CLIF-C ACLF scores significantly and independently predict mortality. In the study by Jalan et al., CLIF-C ACLF was superior to MELD and Child-Pugh scores in predicting mortality in patients with ACLF in the validation database, with a higher c-statistics (0.744 vs. 0.645 vs. 0.653, respectively) [20]. We also found that the AUROC for the CLIF-C ACLF was larger than that of Child-Pugh and MELD scores (0.870 vs. 0.850 vs. 0.861, respectively). The Child-Pugh class had a smaller AUROC (0.611). When using Cox regression and including time to mortality, which adds to the accuracy of testing the discriminating ability, the CLIF-C ACLF had a higher odds ratio as compared to the Child-Pugh class C vs. B (3.25 vs. 1.04).
The limitations of the current study include that it was a single-center study. The high proportion of patients with HCV-related liver cirrhosis could hinder the generalization of the results. However, it adds to the spectrum of ACLF studies with other etiologies of chronic liver disease and strengthens the concept that cirrhosis is one of the baseline hallmarks of ACLF regardless of its etiology. In addition, the large sample size represents an important strength point.