Background and Objectives: Spontaneous bacterial peritonitis (SBP) is both a prevalent and severe complication among individuals with cirrhosis. This systematic review and meta-analysis was designed to evaluate the diagnostic accuracy of procalcitonin (PCT) and compare it to C-reactive protein (CRP) in cirrhotic patients with suspected SBP. Materials and Methods: We performed an extensive literature review utilizing databases including MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials. Original investigations reporting PCT diagnostic accuracy for SBP in cirrhotic populations were included. We computed pooled measures of sensitivity, specificity, positive and negative likelihood ratios, diagnostic odds ratio, and SROC curve area under the curve, with corresponding 95% confidence intervals (CIs). Results: Meta-analytical synthesis encompassed twenty eligible studies. Diagnostic accuracy analysis revealed PCT sensitivity of 0.73 (95% CI, 0.61–0.83) and specificity of 0.88 (95% CI, 0.83–0.91). Likelihood ratio yielded positive values of 6.0 (95% CI, 4.1–8.8) and negative values of 0.30 (95% CI, 0.20–0.47). Overall discriminative ability, quantified through SROC curve analysis, demonstrated an AUC of 0.90 (95% CI, 0.87–0.92). Head-to-head comparisons between PCT and CRP were available from ten studies, demonstrating PCT’s superior diagnostic accuracy over CRP, with significantly higher AUC values (PCT: 0.89, 95% CI 0.86–0.91; CRP: 0.74, 95% CI 0.70–0.78, p < 0.01). Conclusions: Although PCT demonstrates higher diagnostic accuracy than CRP, it does not appear to provide sufficient accuracy to support treatment decisions for SBP. We recommend not relying solely on the PCT test and advise that it be interpreted in conjunction with clinical findings.

Background: Acute-on-chronic-liver failure (ACLF) demonstrates high short-term mortality rates and usually requires intensive care unit (ICU) admission. Accurate prognostication of these patients is pivotal for timely referral for liver transplantation. The superiority of CLIF-C ACLF, CLIF-C ACLF lactate, and NACSELD-ACLF scores in Asian patients with ACLF admitted to an ICU remains inconclusive. Aims: To compare the predictive performance of CLIF-C ACLF, CLIF-C ACLF lactate, and NACSELD-ACLF scores for one-month mortality. Methods: 276 consecutive cirrhotic patients with ACLF admitted to ICU were enrolled. The prognostic values for one-month mortality were assessed by AUROC analysis. Results: The primary cause of cirrhosis in this cohort was alcohol abuse (56.5%). AUROC analysis (95% confidence intervals) demonstrated that CLIF-C ACLF lactate [0.802 (0.747–0.856)] outperformed both CLIF-C ACLF [0.791 (0.733–0.848)] and NACSELD-ACLF [0.673 (0.606–0.740)] in predicting one-month mortality. However, no statistically significant difference was observed between the predictive abilities of CLIF-C ACLF and CLIF-C ACLF lactate. Conclusions: In critically ill cirrhotic patients with ACLF admitted to the hepatology ICU, CLIF ACLF-lactate outperformed CLIF-C ACLF and NACSELD-ACLF in predicting one-month mortality. Nevertheless, no statistically significant difference was observed between CLIF-C ACLF and CLIF-C ACLF lactate. Larger-scale multi-center prospective studies are warranted to validate these results.

Purpose: To develop and internally validate a novel prediction score to predict the occurrence of arterial–esophageal fistula (AEF) in esophageal cancer bleeding. Methods: This retrospective cohort study enrolled patients with esophageal cancer bleeding in the emergency department. The primary outcome was the diagnosis of AEF. The patients were randomly divided into a derivation group and a validation group. In the derivation stage, a predictive model was developed using logistic regression analysis. Subsequently, internal validation of the model was conducted in the validation cohort during the validation stage to assess its discrimination ability. Results: A total of 257 patients were enrolled in this study. All participants were randomized to a derivation cohort (n = 155) and a validation cohort (n = 102). AEF occurred in 22 patients (14.2%) in the derivation group and 14 patients (13.7%) in the validation group. A predictive model (HEARTS-Score) comprising five variables (hematemesis, active bleeding, serum creatinine level >1.2 mg/dL, prothrombin time >13 s, and previous stent implantation) was established. The HEARTS-Score demonstrated a high discriminative ability in both the derivation and validation cohorts, with c-statistics of 0.90 (95% CI 0.82–0.98) and 0.82 (95% CI 0.72–0.92), respectively. Conclusions: By employing this novel prediction score, clinicians can make more objective risk assessments, optimizing diagnostic strategies and tailoring treatment approaches.