A Serum DLL1 and CRP dual-marker model for bacterial infection detection in patients with decompensated cirrhosis: A dual-cohort diagnostic study

血清DLL1和CRP双标志物模型在失代偿期肝硬化患者细菌感染检测中的应用:一项双队列诊断研究

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Abstract

ObjectiveBacterial infections (BIs) in decompensated cirrhosis are associated with high morbidity and mortality but remain diagnostically challenging due to limited conventional biomarker accuracy. We aim to evaluate the utility of serum Delta-like ligand 1 (DLL1) for BI detection in patients with decompensated cirrhosis.MethodsIn this dual-cohort prospective study, 320 hospitalized patients with decompensated cirrhosis were consecutively enrolled and stratified into derivation (n = 224) and independent validation (n = 96) cohorts. Serum DLL1 levels were quantified at admission with an enzyme-linked immunosorbent assay. Diagnostic performance was assessed through receiver operating characteristic (ROC) curve analysis and multivariable logistic regression.ResultsCompared with their noninfected counterparts, patients with decompensated cirrhosis and BI had elevated serum DLL1 levels (P < 0.001). DLL1 was an independent predictor of BIs (adjusted odds ratio (OR) = 5.495, 95% confidence interval (CI): 3.022-9.992) in multivariate analysis. DLL1 demonstrated robust diagnostic performance (area under the curve (AUC) = 0.863, 95% CI: 0.814-0.911), which was further improved when combined with C-reactive protein (CRP) in a dual-marker model (AUC = 0.918, P < 0.001) and validated in an independent cohort (AUC = 0.925). Decision curve analysis confirmed the clinical utility of this combination across threshold probabilities of 10% to 80%. Notably, DLL1 levels were weakly correlated with total bilirubin levels (Spearman's ρ=0.24, P < 0.001), suggesting limited confounding effects from hepatic inflammation.ConclusionSerum DLL1 was a clinically viable diagnostic biomarker for BIs in patients with decompensated cirrhosis and demonstrated weak confounding effects from hepatic dysfunction. The CRP-DLL1 combined model achieved superior diagnostic accuracy with cross-cohort validation robustness.

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