From Child-Pugh to MELD score and beyond: Taking a walk down memory lane

Applicability of Child-Turcotte-Pugh Score in Anticipating Post-ERCP Adverse Events in Patients With Cirrhosis: A Systematic Review and Meta-analysis

Limited objective data exist on the comparison of post-endoscopic retrograde cholangiopancreatography (ERCP) complications in patients with cirrhosis based on the severity of the disease. We evaluated the effectiveness of the Child-Turcotte-Pugh (CTP) score system in anticipating the risk of post-ERCP complications in patients with cirrhosis. The PubMed, Scopus, Embase, and Cochrane databases were searched from inception through September 2022 to identify studies comparing post-ERCP complications in patients with cirrhosis based on CTP score. Odds ratios (ORs) and their associated 95% CIs were pooled using a random-effect model to calculate effect size. The reference group for analysis was the CTP class C patient group. Seven studies comprising 821 patients who underwent 1068 ERCP procedures were included. The CTP class C patient population exhibited a higher risk of overall post-ERCP adverse events compared with those with class A or B (OR: 2.87, 95% CI: 1.77-4.65, P = 0.00 and OR: 2.02, 95% CI: 1.17-3.51, P = 0.01, respectively). Moreover, CTP class B patients had a significantly higher complication rate than CTP class A patients (OR: 1.62, 95% CI: 1.04-2.53, P = 0.03). However, no statistically significant differences were found in the occurrence of specific types of complications, including bleeding, pancreatitis, cholangitis, perforation, or mortality across the three CTP groups. We demonstrated that the CTP classification system is a reliable predictor of ERCP complications in patients with cirrhosis. Consequently, caution should be exercised when performing ERCP in patients classified as CTP class C.

Pre-hospital symptom clusters and symptom network analysis in decompensated cirrhotic patients: A cross-sectional study

AIMS

To generate pre-hospital symptom networks, explore core, bridge and sentinel symptoms, identify pre-hospital symptom clusters and analyse relationship between influencing factors and symptom clusters in decompensated cirrhosis patients.

DESIGN

A cross-sectional study design using the Strengthening the Reporting of Observational Studies in Epidemiology checklist.

METHODS

Demographical, physiological, psychological and sociological characteristics and the pre-hospital symptoms of 292 decompensated cirrhotic patients were collected from October 2021 to March 2023 in China. Frequencies, percentages, means, standard deviations, independent samples t-tests, one-way analysis of variance, exploratory factor analysis, multiple stepwise regression analysis and network analysis were used for data analysis.

RESULTS

'I don't look like myself' and itching were core and bridge symptoms, while bloating and lack of energy were sentinel symptoms in decompensated cirrhotic patients. Monthly family income, anxiety, depression, social support and disease duration influenced the neuropsychological symptom cluster, with worrying as the strongest predictor symptom. Influential factors for cirrhosis-specific symptom cluster included Child-Pugh class, monthly family income, disease duration, anxiety and depression, with itching being the strongest predictor symptom. Monthly family income, disease duration and depression were influential factors for gastrointestinal symptom cluster, with loss of appetite as the strongest predictor symptom.

CONCLUSIONS

Neuropsychological, cirrhosis-specific and gastrointestinal symptom clusters were formed in decompensated cirrhotic patients. Through network analysis, direct connections between symptoms, symptom clusters and their influencing factors were revealed, thereby offering clinicians a foundation for effectively managing patients' pre-hospital symptoms.

IMPACT

Decompensated cirrhosis patients commonly have multiple symptoms, while the management of pre-hospital symptoms is often suboptimal. This study identified neuropsychological, cirrhosis-specific, gastrointestinal symptom clusters and recognized core, bridge and sentinel symptoms in these patients. It also revealed the most prominent symptoms within each cluster. This provides insight into the hierarchy of symptoms, improving symptom management in decompensated cirrhosis.

PATIENT AND PUBLIC INVOLVEMENT

There was no patient or public involvement.

LINAS-Score: prognostic model for mortality assessment in patients with cirrhotic liver and infected ascites

BACKGROUND AND AIM

Patients with liver cirrhosis often face a grave threat from infected ascites (IA). However, a well-established prognostic model for this complication has not been established in routine clinical practice. Therefore, we aimed to assess mortality risk in patients with liver cirrhosis and IA.

METHODS

We conducted a retrospective study across three tertiary hospitals, enrolling 534 adult patients with cirrhotic liver and IA, comprising 465 with spontaneous bacterial peritonitis (SBP), 34 with bacterascites (BA), and 35 with secondary peritonitis (SP). To determine the attributable mortality risk linked to IA, these patients were matched with 122 patients with hydropic decompensated liver cirrhosis but without IA. Clinical, laboratory, and microbiological parameters were assessed for their relation to mortality using univariable analyses and a multivariable random forest model (RFM). Least absolute shrinkage and selection operator (Lasso) regression model was used to establish an easy-to-use mortality prediction score.

RESULTS

The in-hospital mortality risk was highest for SP (39.0%), followed by SBP (26.0%) and BA (25.0%). Besides illness severity markers, microbiological parameters, such as Candida spp., were identified as the most significant indicators for mortality. The Lasso model determined 15 parameters with corresponding scores, yielding good discriminatory power (area under the receiver operating characteristics curve = 0.89). Counting from 0 to 83, scores of 20, 40, 60, and 80 corresponded to in-hospital mortalities of 3.3%, 30.8%, 85.2%, and 98.7%, respectively.

CONCLUSION

We developed a promising mortality prediction score for IA, highlighting the importance of microbiological parameters in conjunction with illness severity for assessing patient outcomes.

Tumor burden score as a prognostic factor in patients with intermediate and locally advanced hepatocellular carcinoma undergoing liver resection: an attempt to extend resectability criteria

BACKGROUND

Surgery is currently recommended as a curative treatment option for hepatocellular carcinomas (HCC) belonging to Barcelona Clinic Liver Cancer (BCLC) stage A only. This study aims to classify various BCLC groups as per Tumor Burden Score (TBS) in an attempt to identify patients who could benefit from resection.

MATERIALS AND METHODS

A retrospective analysis of a prospectively maintained database of all patients operated for HCC between January 2010 and July 2022 was performed. TBS was defined as, TBS2 = (maximum tumor diameter)2 + (number of tumors)2.

RESULTS

Two hundred and ninety-one patients who underwent resection were staged as per the latest BCLC (A = 219, B = 45, C = 27) staging. Patients were segregated into low (<7.3) and high (>7.3) TBS. With a median follow-up of 36.2 months, the median OS for stages, A and B in the low TBS group was 107.4 and 42.7 months respectively. Median OS was not reached for patients in the BCLC C stage. In patients with high TBS, the median OS for BCLC A, B and C was 42.3, 25.72, and 16.9 months respectively.

CONCLUSION

TBS is a significant factor influencing survival in patients of HCC. TBS can be used to stratify patients in BCLC B and C stages and help select patients who would benefit from surgical resection to achieve good long-term survival with acceptable morbidity.

Machine Learning for Short-Term Mortality in Acute Decompensation of Liver Cirrhosis: Better than MELD Score

Prediction of short-term mortality in patients with acute decompensation of liver cirrhosis could be improved. We aimed to develop and validate two machine learning (ML) models for predicting 28-day and 90-day mortality in patients hospitalized with acute decompensated liver cirrhosis. We trained two artificial neural network (ANN)-based ML models using a training sample of 165 out of 290 (56.9%) patients, and then tested their predictive performance against Model of End-stage Liver Disease-Sodium (MELD-Na) and MELD 3.0 scores using a different validation sample of 125 out of 290 (43.1%) patients. The area under the ROC curve (AUC) for predicting 28-day mortality for the ML model was 0.811 (95%CI: 0.714- 0.907; p < 0.001), while the AUC for the MELD-Na score was 0.577 (95%CI: 0.435-0.720; p = 0.226) and for MELD 3.0 was 0.600 (95%CI: 0.462-0.739; p = 0.117). The area under the ROC curve (AUC) for predicting 90-day mortality for the ML model was 0.839 (95%CI: 0.776- 0.884; p < 0.001), while the AUC for the MELD-Na score was 0.682 (95%CI: 0.575-0.790; p = 0.002) and for MELD 3.0 was 0.703 (95%CI: 0.590-0.816; p < 0.001). Our study demonstrates that ML-based models for predicting short-term mortality in patients with acute decompensation of liver cirrhosis perform significantly better than MELD-Na and MELD 3.0 scores in a validation cohort.

Clinical Outcomes and Their Determinants in Patients With Gastric Variceal Bleed Undergoing Endoscopic Cyanoacrylate Injection: An Observational Study

Background and aims

Gastric variceal bleeding (GVB), compared to esophageal varices, is rare but often massive and associated with high mortality. Endoscopic cyanoacrylate glue injection (ECGI) is the first-line treatment for GVB. Hence, we conducted this study to assess the clinical outcomes and the determinants of ECGI for gastric variceal bleeding.

Methods

This was a prospective observational study of patients with ECGI for GVB between June 2019 and February 2023. The demographic characteristics, etiology and severity of cirrhosis, size, type of gastric varices, volume of cyanoacrylate used, number of sessions required, technical success, rebleeding rate, and survival at three months were studied.

Results

A total of 135 patients underwent ECGI for GVB. Their mean (SD) age was 44.9 (13.6) years, with a male preponderance (n = 23, 68.1 %). Eighty-two patients (60.7 %) had cirrhosis. Their mean model for end-stage liver disease (MELD) score was 14.3 (7.3). Gastric varices were gastroesophageal varices (GOV)1 in 42 (31.1 %), GOV2 in 73 (54.1 %), and isolated gastric varices (IGV)1 in 20 (14.8 %) patients. Varices were large in 35 (25.9 %) and had F1 morphology in 89 (65.9 %) patients. The success rate of initial hemostasis was 98.5 %. The median sessions required were 1 (1-2), and the median volume of cyanoacrylate per session was 2 (1-2) ml. The procedure was associated with minor complications like transient abdominal pain in 11 (8.1 %) and fever in 2 (2.7 %) patients. Rebleeding was observed in 23 (17 %) patients. GOV2, F1 morphology, and a high MELD score were significantly associated with rebleeding. Five (3.7 %) patients died during the study; 2 (1.5 %) were due to failure to control bleeding.

Conclusion

In conclusion, our study demonstrated ECGI to be very safe and effective for GVB. The technical success was high and could be achieved in fewer sessions with a smaller volume of cyanoacrylate during each session.

Development and validation of a nomogram for predicting in-hospital mortality of intensive care unit patients with liver cirrhosis

BACKGROUND

Liver cirrhosis patients admitted to intensive care unit (ICU) have a high mortality rate.

AIM

To establish and validate a nomogram for predicting in-hospital mortality of ICU patients with liver cirrhosis.

METHODS

We extracted demographic, etiological, vital sign, laboratory test, comorbidity, complication, treatment, and severity score data of liver cirrhosis patients from the Medical Information Mart for Intensive Care IV (MIMIC-IV) and electronic ICU (eICU) collaborative research database (eICU-CRD). Predictor selection and model building were based on the MIMIC-IV dataset. The variables selected through least absolute shrinkage and selection operator analysis were further screened through multivariate regression analysis to obtain final predictors. The final predictors were included in the multivariate logistic regression model, which was used to construct a nomogram. Finally, we conducted external validation using the eICU-CRD. The area under the receiver operating characteristic curve (AUC), decision curve, and calibration curve were used to assess the efficacy of the models.

RESULTS

Risk factors, including the mean respiratory rate, mean systolic blood pressure, mean heart rate, white blood cells, international normalized ratio, total bilirubin, age, invasive ventilation, vasopressor use, maximum stage of acute kidney injury, and sequential organ failure assessment score, were included in the multivariate logistic regression. The model achieved AUCs of 0.864 and 0.808 in the MIMIC-IV and eICU-CRD databases, respectively. The calibration curve also confirmed the predictive ability of the model, while the decision curve confirmed its clinical value.

CONCLUSION

The nomogram has high accuracy in predicting in-hospital mortality. Improving the included predictors may help improve the prognosis of patients.

From liver to hormones: The endocrine consequences of cirrhosis

Hepatocrinology explores the intricate relationship between liver function and the endocrine system. Chronic liver diseases such as liver cirrhosis can cause endocrine disorders due to toxin accumulation and protein synthesis disruption. Despite its importance, assessing endocrine issues in cirrhotic patients is frequently neglected. This article provides a comprehensive review of the epidemiology, pathophysiology, diagnosis, and treatment of endocrine disturbances in liver cirrhosis. The review was conducted using the PubMed/Medline, EMBASE, and Scielo databases, encompassing 172 articles. Liver cirrhosis is associated with endocrine disturbances, including diabetes, hypoglycemia, sarcopenia, thyroid dysfunction, hypogonadotropic hypogonadism, bone disease, adrenal insufficiency, growth hormone dysfunction, and secondary hyperaldosteronism. The optimal tools for diagnosing diabetes and detecting hypoglycemia are the oral glucose tolerance test and continuous glucose monitoring system, respectively. Sarcopenia can be assessed through imaging and functional tests, while other endocrine disorders are evaluated using hormonal assays and imaging studies. Treatment options include metformin, glucagon-like peptide-1 analogs, sodium-glucose co-transporter-2 inhibitors, and insulin, which are effective and safe for diabetes control. Established standards are followed for managing hypoglycemia, and hormone replacement therapy is often necessary for other endocrine dysfunctions. Liver transplantation can address some of these problems.

Prognostic value of preoperative serum ferritin in hepatocellular carcinoma patients undergoing transarterial chemoembolization

The present study investigated the prognostic impact of preoperative serum ferritin (SF) levels on the survival of patients with hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE). Clinicopathological characteristics and laboratory biomarkers of 223 patients with HCC who underwent TACE were retrospectively reviewed. The Kaplan-Meier method was used to calculate the overall survival (OS), and the log-rank test was used to evaluate statistical significance. Univariate and multivariate analyses were performed using Cox proportional hazards regression to evaluate the prognostic impact of SF in these patients. The present findings identified extrahepatic metastases [hazard ratio (HR)=0.490,95%; confidence interval (CI)=0.282-0.843; P=0.010)] and vascular invasion (HR=0.373; 95% CI=0.225-0.619; P<0.0001) as independent prognostic factors for OS. However, preoperative SF levels could not independently predict OS when compared with other prognostic factors (HR=0.810; 95% CI=0.539-1.216; P=0.309). In conclusion, preoperative SF level is an unreliable biochemical predictor of survival in patients with HCC undergoing TACE.

Prognostic Factors for Mortality in Hepatocellular Carcinoma at Diagnosis: Development of a Predictive Model Using Artificial Intelligence

BACKGROUND

Hepatocellular carcinoma (HCC) accounts for 75% of primary liver tumors. Controlling risk factors associated with its development and implementing screenings in risk populations does not seem sufficient to improve the prognosis of these patients at diagnosis. The development of a predictive prognostic model for mortality at the diagnosis of HCC is proposed.

METHODS

In this retrospective multicenter study, the analysis of data from 191 HCC patients was conducted using machine learning (ML) techniques to analyze the prognostic factors of mortality that are significant at the time of diagnosis. Clinical and analytical data of interest in patients with HCC were gathered.

RESULTS

Meeting Milan criteria, Barcelona Clinic Liver Cancer (BCLC) classification and albumin levels were the variables with the greatest impact on the prognosis of HCC patients. The ML algorithm that achieved the best results was random forest (RF).

CONCLUSIONS

The development of a predictive prognostic model at the diagnosis is a valuable tool for patients with HCC and for application in clinical practice. RF is useful and reliable in the analysis of prognostic factors in the diagnosis of HCC. The search for new prognostic factors is still necessary in patients with HCC.

Prediction of acute kidney injury in patients with liver cirrhosis using machine learning models: evidence from the MIMIC-III and MIMIC-IV

PURPOSE

To develop and validate a machine learning (ML)-based prediction model for acute kidney injury (AKI) in patients with liver cirrhosis.

METHODS

Data on liver cirrhosis patients were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) and MIMIC-IV databases in this retrospective cohort study. ML algorithms, including random forest (RF), extreme gradient boosting (XGB), light gradient boosting machine (LGBM), and gradient boosting decision tree (GBDT) were applied to construct prediction models. Predictors were screened via univariate logistic regression, and then the models were developed with all data of the included patients. A bootstrap resampling method was adopted to validate the models. The predictive abilities of our final model were compared with those of the sequential organ failure assessment score (SOFA), simplified acute physiology score II (SAPS II), Model for End-stage Liver Disease (MELD), and MELD Na.

RESULTS

This study included 950 patients, of which 429 (45.16%) had AKI. Mechanical ventilation, vasopressor, international normalized ratio (INR), bilirubin, Charlson comorbidity index (CCI), prothrombin time (PT), estimated glomerular filtration rate (EGFR), partial thromboplastin time (PTT), and heart rate served as predictors. In the derivation set, the developed RF [area under curve (AUC) = 0.747], XGB (AUC = 0.832), LGBM (AUC = 0.785), and GBDT (AUC = 0.811) models exhibited significantly greater predictive performance than the logistic regression model (AUC = 0.699) (all P < 0.05). Among the ML-based models, the XGB model had the greatest AUC. In internal validation, the predictive capacity of the XGB model (AUC = 0.833) was significantly superior to that of the logistic regression model (AUC = 0.701) (P = 0.045). Hence, the XGB model was selected as the final model for AKI prediction. In contrast to the XGB model (AUC = 0.832), the SOFA (AUC = 0.609), MELD (AUC = 0.690), MELD Na (AUC = 0.690), and SAPS II (AUC = 0.641) had significantly lower predictive abilities in the derivation set (all P < 0.001). The XGB model was internally validated to have an AUC of 0.833, which was significantly higher than the SOFA (AUC = 0.609), MELD (AUC = 0.690), MELD Na (AUC = 0.688), and SAPS II (AUC = 0.641) (all P < 0.05).

CONCLUSION

The XGB model had a better performance than the logistic regression model, SOFA, MELD, MELD Na, and SAPS II in AKI prediction for cirrhosis patients, which may help identify patients at a risk of AKI, and then provide timely interventions.

Histologic scoring of liver biopsies for the prognosis of chronic liver disease at a tertiary care hospital in South India

OBJECTIVES

The study aimed to evaluate the role of histologic scoring of liver biopsies using Ishak-modified histological activity index (HAI) and Laennec's scoring system in predicting chronic liver disease (CLD) prognosis in South India.

METHODS

A retrospective analysis of liver biopsy samples was conducted at a tertiary care hospital. The samples were scored using the Ishak-modified HAI and Laennec's scoring system for staging and grading CLD. Patient clinical data were retrieved and assessed using the Child-Pugh scoring system. Chi-squared test was used to test the association between categorical variables and the association with multiple categories was reported using Cramer's V correlation coefficient. A p-value < 0.05 was considered significant.

RESULTS

Out of 43 samples included in the study, 65.12% were male patients, with a mean age of 43.3 ± 13.9 years. Cirrhotic cases accounted for the highest proportion (65.12%, n = 28), followed by hepatitis cases (30%, n = 13). The predominant etiology was alcohol-related (44.19%, n = 19). Percutaneous liver biopsies constituted most of the samples (48.84%, n = 21), followed by transjugular (37.21%, n = 16) and ultrasonography-guided (11.63%, n = 6) biopsies. The correlation between Ishak-modified HAI stages and Child-Pugh scores was weak and insignificant (p = 0.71), while Laennec's scores showed a moderate but insignificant correlation with Child-Pugh scores (p = 0.066).

CONCLUSION

Histologic scoring of liver biopsies using the Ishak-modified HAI and Laennec's scoring system can provide valuable prognostic information for CLD. However, further research is needed to establish stronger correlations with clinical outcomes.

The Effect of Model for End-Stage Liver Disease 3.0 on Disparities between Patients with and without Hepatocellular Carcinoma in Korea

PURPOSE

The model for end-stage liver disease (MELD) 3.0 has recently been suggested for determining liver allocation. We aimed to apply MELD 3.0 to a Korean population and to discover differences between patients with and without hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

This study is a retrospective study of 2203 patients diagnosed with liver cirrhosis at Severance Hospital between 2016-2022. Harrell's concordance index was used to validate the ability of MELD scores to predict 90-day survival.

RESULTS

During a mean follow-up of 12.9 months, 90-day survival was 61.9% in all patients, 50.4% in the HCC patients, and 74.8% in the non-HCC patients. Within the HCC patients, the concordance index for patients on the waitlist was 0.653 using MELD, which increased to 0.753 using MELD 3.0. Among waitlisted patients, the 90-day survival of HCC patients was worse than that of non-HCC patients with MELD scores of 31-37 only (69.7% vs. 30.0%, p=0.001). Applying MELD 3.0, the 90-day survival of HCC patients was worse than that of non-HCC patients across a wider range of MELD 3.0 scores, compared to MELD, with MELD 3.0 scores of 21-30 and 31-37 (82.0% vs. 72.5% and 72.3% vs. 24.3%, p=0.02 and p<0.001, respectively).

CONCLUSION

MELD 3.0 predicted 90-day survival of the HCC patients more accurately than original MELD score; however, the disparity between HCC and non-HCC patients increased, particularly in patients with MELD scores of 21-30. Therefore, a novel exception score is needed or the current exception score system should be modified.

Health status of patients with liver transplantation by alcohol-related disease vs another etiology: A cohort study

AIM

To study the health status of a group of patients with liver transplantation by alcohol-related disease vs another etiology before and after the transplantation.

METHOD

Longitudinal cohort study of liver transplant patients from November 2019 to July 2022. Adult patients attended in the unit of transplantation of a hospital for a first liver transplant, both elective and urgent, were included. Patients who already had a transplanted organ and those who required liver re-transplantation in the first month after the first transplant were excluded. Sociodemographic and clinical variables, MELDNa, liver frailty index, emotional-behavioral effects of transplantation, level of anxiety and depression were collected. Pearson's chi-square, Student's t, Mann-Whitney U, and Wilcoxon sign tests were used for statistical analysis.

RESULTS

The sample was n = 67 liver transplant patients with a mean age of 56.37 years, 67.2% being men and 39% due to alcohol-related liver disease. 9% of all included patients were urgent transplants. Alcohol consumption was associated with older age, a high rate of liver frailty, and a non-active work situation. Alcoholic etiology correlated with increased concern during the first six months after liver transplantation.

CONCLUSION

There are differences in the health status between liver transplant patients for alcohol-related liver disease vs other etiology. Nurses must consider the etiology of liver disease to guide care and interventions throughout the transplant process.

Prognostic assessment of liver cirrhosis and its complications: current concepts and future perspectives

Liver cirrhosis is an irreversible stage of chronic liver disease with varying clinical course. Acute decompensation of liver cirrhosis represents a watershed in prognosis and is characterized by the occurrence of clinical complications such as ascites, jaundice, hepatic encephalopathy, infections, or portal-hypertensive hemorrhages. Emergent data indicate that an acute decompensation can be subdivided into stable decompensated cirrhosis (SDC), unstable decompensated cirrhosis (UDC), pre-acute-on chronic liver failure (pre-ACLF) and acute-on chronic liver failure (ACLF), while the mortality risk varies greatly between the respective subgroups. ACLF is the most severe form of acutely decompensated cirrhosis and characterized by the development of organ failure(s) and a high short-term mortality. Due to the dynamic disease course of acute decompensation, it is paramount to detect patients at particular risk for severe complications those at high risk for developing ACLF as early as possible in order to initiate optimal management. This review describes new concepts and perspectives in the definition and classification of decompensated cirrhosis and provides on overview on emerging predictive scoring systems, non-invasive measurement methods and new biomarkers, which allow an early identification of patients with acute decompensation at risk.

Evaluation of the nutritional status of patients with liver cirrhosis

BACKGROUND

Progressive malnutrition coexists with liver diseases, particularly in patients with cirrhosis. Early diagnosis of malnutrition in patients with advanced stages of chronic liver disease and the implementation of appropriate nutritional treatment for malnourished patients should be an integral part of the therapeutic process.

AIM

To evaluate the nutritional status of patients with various severities of advanced liver fibrosis, using various nutritional status parameters.

METHODS

This study involved 118 patients with liver cirrhosis who were classified into three groups according to their Child-Pugh score. The nutritional status of the patients in each group was assessed using different methods. The average values obtained from the measurements were calculated for each research group. The influence of disease stage on the examined parameters of nutritional status was determined using one-way analysis of variance. To investigate the relationship between the parameters determining nutritional status and the stage of disease advancement, a correlation analysis was performed.

RESULTS

The Child-Pugh A group had the highest mean body weight (76.42 kg), highest mean body mass index (BMI) (26.72 kg/m²), and largest mean arm circumference (27.64 cm). In the Child-Pugh B group, the mean scores of all examined variables were lower than those of the Child-Pugh A group, whereas the mean body weight and BMI of the Child-Pugh C group were higher than those of the Child-Pugh B group. There was a very strong correlation between the Child-Pugh classification and subjective global assessment score; a very strong correlation between the Child-Pugh classification and arm circumference; a strong correlation between the Child-Pugh classification and body weight, albumin concentration, fat-free mass index, muscle mass index, phase angle, and BMI; and an average correlation between Child-Pugh classification and fat mass index. Notably, these indicators deteriorated with disease progression.

CONCLUSION

Advanced liver fibrosis leads to the deterioration of many nutritional status parameters. The extent of malnutrition increases with the progression of liver fibrosis. The Child-Pugh score reflects the nutritional status.

Differentiation of Spontaneous Bacterial Peritonitis from Secondary Peritonitis in Patients with Liver Cirrhosis: Retrospective Multicentre Study

Ascitic fluid infection is a serious complication of liver cirrhosis. The distinction between the more common spontaneous bacterial peritonitis (SBP) and the less common secondary peritonitis in patients with liver cirrhosis is crucial due to the varying treatment approaches. This retrospective multicentre study was conducted in three German hospitals and analysed 532 SBP episodes and 37 secondary peritonitis episodes. Overall, >30 clinical, microbiological, and laboratory parameters were evaluated to identify key differentiation criteria. Microbiological characteristics in ascites followed by severity of illness and clinicopathological parameters in ascites were the most important predictors identified by a random forest model to distinguish between SBP and secondary peritonitis. To establish a point-score model, a least absolute shrinkage and selection operator (LASSO) regression model selected the ten most promising discriminatory features. By aiming at a sensitivity of 95% either to rule out or rule in SBP episodes, two cut-off scores were defined, dividing patients with infected ascites into a low-risk (score ≥ 45) and high-risk group (score < 25) for secondary peritonitis. Overall, the discrimination of secondary peritonitis from SBP remains challenging. Our univariable analyses, random forest model, and LASSO point score may help clinicians with the crucial differentiation between SBP and secondary peritonitis.

Complement C3 Facilitates Stratification of Stages of Chronic Hepatitis B and Signifies Development of Acute-on-Chronic Liver Failure in Acute Decompensated Cirrhosis

INTRODUCTION

Patients with chronic hepatitis B (CHB) have a dynamic disease process and risk of end-stage liver disease. It is critical to unambiguously differentiate the stages of the disease and focus on therapy prior to onset of an irreversible clinical endpoint.

METHODS

We retrospectively analyzed a wide range of CHB patients at different stages. The predictive power of serum complement component 3 (C3) levels for the development of acute-on-chronic liver failure (ACLF) in patients with decompensated cirrhosis was established and validated.

RESULTS

The decrease in serum C3 levels paralleled the severity of diseases related to hepatitis B virus. Patients with decompensated cirrhosis who developed ACLF had significantly lower serum C3 levels than others on admission (0.50 vs. 0.80 g/L, P < 0.001). Data analysis also revealed that low serum C3 was a significant risk factor for developing ACLF (hazard ratio = 0.32, P < 0.01). The area under the receiver operating characteristic curve (auROC) for serum C3 levels that predicted the development of ACLF in patients with decompensated cirrhosis was 0.90, which had sensitivity and specificity of 88.2% and 88.7%, respectively. A similar result was observed in the validation set (auROC = 0.86 for predicting development of ACLF in patients with decompensated cirrhosis).

CONCLUSIONS

Serum C3 levels are valuable in assessing the severity of CHB-related stages. Low C3 levels signifies the development of ACLF in patients with decompensated cirrhosis.

Liver Function-How to Screen and to Diagnose: Insights from Personal Experiences, Controlled Clinical Studies and Future Perspectives

Acute and chronic liver disease is a relevant problem worldwide. Liver function plays a crucial role in the course of liver diseases not only in estimating prognosis but also with regard to therapeutic interventions. Within this review, we discuss and evaluate different tools from screening to diagnosis and give insights from personal experiences, controlled clinical studies and future perspectives. Finally, we offer our novel diagnostic algorithm to screen patients with presumptive acute or chronic liver disease in the daily clinical routine.

Albumin-bilirubin score is superior to platelet-albumin-bilirubin score and model for end-state liver disease sodium for predicting posthepatectomy liver failure

BACKGROUND

Risk stratification for patients undergoing hepatectomy can be attempted using established models. This study compares the platelet-albumin-bilirubin (PALBI) score with albumin-bilirubin (ALBI) and model for end-stage liver disease sodium (MELD-Na) for predicting posthepatectomy liver failure (PHLF) and 30-day mortality.

METHODS

The 2014-2018 NSQIP database was queried for patients who underwent elective hepatectomy. Multivariable logistic regressions assessed associations of posthepatectomy outcomes with patient and clinical characteristics. Predictive accuracy of the grading systems was evaluated using receiver operator characteristic (ROC) curves and calculating area under the curve (AUC).

RESULTS

Severe PHLF (Grade B/C) and mortality were present in 2.58% (N = 369) and 1.2% (N = 171) of patients who underwent hepatectomy (N = 13 925), respectively. ALBI Grade 2/3 had a stronger association with severe PHLF (odds ratio [OR] = 1.62, p < 0.01) and mortality (OR = 2.06, p < 0.005) than PALBI Grade 2/3 (OR = 1.14, p = 0.43 for PHLF and OR = 2.01, p < 0.005 for mortality) or MELD-Na ≥10 (OR = 1.29, p = 0.25 for PHLF and OR = 1.84, p < 0.03). ALBI had a higher AUC (0.671) than PALBI (0.625) and MELD-Na (0.627) for predicting severe PHLF. ALBI had a higher AUC (0.695) than PALBI (0.642) for predicting 30-day mortality.

CONCLUSIONS

ALBI was a more accurate predictor of severe PHLF and 30-day mortality than MELD-Na and PALBI for patients who underwent hepatectomy.

Urinary BA Indices as Prognostic Biomarkers for Complications Associated with Liver Diseases

Hepatobiliary diseases and their complications cause the accumulation of toxic bile acids (BA) in the liver, blood, and other tissues, which may exacerbate the underlying condition and lead to unfavorable prognosis. To develop and validate prognostic biomarkers for the prediction of complications of cholestatic liver disease based on urinary BA indices, liquid chromatography-tandem mass spectrometry was used to analyze urine samples from 257 patients with cholestatic liver diseases during a 7-year follow-up period. The urinary BA profile and non-BA parameters were monitored, and logistic regression models were used to predict the prognosis of hepatobiliary disease-related complications. Urinary BA indices were applied to quantify the composition, metabolism, hydrophilicity, and toxicity of the BA profile. We have developed and validated the bile-acid liver disease complication (BALDC) model based on BA indices using logistic regression model, to predict the prognosis of cholestatic liver disease complications including ascites. The mixed BA and non-BA model was the most accurate and provided higher area under the receiver operating characteristic (ROC) and smaller akaike information criterion (AIC) values compared to both non-BA and MELD (models for end stage liver disease) models. Therefore, the mixed BA and non-BA model could be used to predict the development of ascites in patients diagnosed with liver disease at early stages of intervention. This will help physicians to make a better decision when treating hepatobiliary disease-related ascites.