A novel prognostic model to predict mortality in patients with acute-on-chronic liver failure in intensive care unit.

Acute-on-chronic liver failure (ACLF) implies high short-term mortality rates and usually requires intensive care unit (ICU) admission. Proper prognosis for these patients is crucial for early referral for liver transplantation. The superiority of CLIF-C ACLF score in Asian patients with ACLF admitted to an ICU remains inconclusive when compared to other scoring systems. The purpose of the study is (i) to compare the predictive performance of original MELD, MELD-Lactate, CLIF-C ACLF, CLIF-C ACLF-Lactate, and APACHE-II scores for short-term mortality assessment. (ii) to build and validate a novel scoring system and to compare its predictive performance to that of the original five scores. Two hundred sixty-five consecutive cirrhotic patients with ACLF who were admitted to our ICU were enrolled. The prognostic values for mortality were assessed by ROC analysis. A novel model was developed and internally validated using fivefold cross-validation. Alcohol abuse was identified as the primary etiology of cirrhosis. The AUROC of the five prognostic scores were not significantly superior to each other in predicting 1-month and 3-month mortality. The newly developed prognostic model, incorporating age, alveolar-arterial gradient (A-a gradient), BUN, total bilirubin level, INR, and HE grades, exhibited significantly improved performance in predicting 1-month and 3-month mortality with AUROC of 0.863 and 0.829, respectively, as compared to the original five prognostic scores. The novel ACLF model seems to be superior to the original five scores in predicting short-term mortality in ACLF patients admitted to an ICU. Further rigorous validation is required.

Adding nutritional status to the original BCLC stage improves mortality prediction for hepatocellular carcinoma patients in HBV-endemic regions.

Hepatocellular carcinoma (HCC) is associated with high mortality, especially in Asian populations where chronic HBV infection is a major cause. Accurate prediction of mortality can assist clinical decision-making. We aim to (i) compare the predicting ability of Barcelona Clinic Liver Cancer classification (BCLC) stage, neutrophil-to-lymphocyte ratio (NLR), and Albumin-Bilirubin (ALBI) score in predicting short-term mortality (one- and two-year) and (ii) develop a novel model with improved accuracy compared to the conventional models. This study enrolled 298 consecutive HCC patients from our hepatology department. The prognostic values for mortality were assessed by area under the receiver operating characteristic curve (AUROC) analysis. A novel model was established and internally validated using 5-fold cross-validation, followed by external validation in a cohort of 100 patients. The primary etiology of cirrhosis was hepatitis B virus (HBV), with 81.2% of HCC patients having preserved liver function. Significant differences were observed in hemoglobin (Hb) and serum albumin levels, which reflect patients' nutrition status, between patients who survived for one year and those who died. BCLC exhibited superior predictive accuracy compared to NLR but had borderline superiority to the ALBI score. Therefore, a novel model incorporating BCLC, Hb, and serum albumin was developed, internally and externally validated, as well as subgroup sensitivity analysis. The model exhibited significantly higher predictive accuracy for one- and two-year mortality than conventional prognostic predictors, with AUROC values of 0.841 and 0.805, respectively. The novel "BCLC-Nutrition Model", which incorporates BCLC, Hb, and serum albumin, may provide improved predictive accuracy for short-term mortality in HCC patients compared to commonly used prognostic scores. This emphasizes the importance of nutrition in the management of HCC patients.

A Validated Composite Score Demonstrates Potential Superiority to MELD-Based Systems in Predicting Short-Term Survival in Patients with Liver Cirrhosis and Spontaneous Bacterial Peritonitis-A Preliminary Study.

BACKGROUND: Spontaneous bacterial peritonitis (SBP) is a severe complication in cirrhosis patients with ascites, leading to high mortality rates if not promptly treated. However, specific prediction models for SBP are lacking. AIMS: This study aimed to compare commonly used cirrhotic prediction models (CTP score, MELD, MELD-Na, iMELD, and MELD 3.0) for short-term mortality prediction and develop a novel model to improve mortality prediction. METHODS: Patients with the first episode of SBP were included. Prognostic values for mortality were assessed using AUROC analysis. A novel prediction model was developed and validated. RESULTS: In total, 327 SBP patients were analyzed, with HBV infection as the main etiologies. MELD 3.0 demonstrated the highest AUROC among the traditional models. The novel model, incorporating HRS, exhibited superior predictive accuracy for in-hospital in all patients and 3-month mortality in HBV-cirrhosis, with AUROC values of 0.827 and 0.813 respectively, surpassing 0.8. CONCLUSIONS: MELD 3.0 score outperformed the CTP score and showed a non-significant improvement compared to other MELD-based scores, while the novel SBP model demonstrated impressive accuracy. Internal validation and an HBV-related cirrhosis subgroup sensitivity analysis supported these findings, highlighting the need for a specific prognostic model for SBP and the importance of preventing HRS development to improve SBP prognosis.