ArticleScientific reports2024
Development of a nomogram for predicting in-hospital mortality in patients with liver cirrhosis and sepsis.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed.
- Factors associated with mortality in older sepsis patients: a nationwide retrospective cohort study in Germany.Age and ageing · 2026Observational
- Albumin-corrected anion gap and 28-/90-day mortality in cirrhotic patients with invasive fungal infection: a retrospective cohort study.BMC infectious diseases · 2026Article
- Development and external validation of a predictive model for in-hospital mortality in patients with liver cirrhosis and sepsis.Scientific reports · 2026Article
- Article
- Prognostic significance of lymphocyte PD-1 expression in combination with clinical scoring systems in patients with liver cirrhosis complicated by sepsis.Frontiers in immunology · 2026Article
- Risk factors and prediction model for sarcopenia in patients with cirrhosis undergoing transjugular intrahepatic portosystemic shunt.Internal and emergency medicine · 2026Article
- Development and validation of a prediction model for in-hospital mortality in intensive care unit patients with cirrhosis and sepsis: a multicentre retrospective cohort study.Frontiers in medicine · 2026Article
- Machine learning-based nomogram for mortality risk stratification in cirrhotic patients with sepsis: a single-center predictive model.Frontiers in medicine · 2025Article
- The predictive value of SOFA and APSIII scores for 28-day mortality risk in SIMI: a cohort study based on the MIMIC-IV database.Frontiers in cellular and infection microbiology · 2025Article
- A Novel Scoring System for Assessing In-Hospital Mortality Risk in Patients With Liver Cirrhosis.Cureus · 2024Article
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6 authors.
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Abstract
In this study, we aimed to investigate the risk factors associated with in-hospital mortality in patients with cirrhosis and sepsis, establish and validate the nomogram. This retrospective study included patients diagnosed with liver cirrhosis and sepsis in the Medical Information Mart for Intensive Care IV (MIMIC-IV). Models were compared by the area under the curve (AUC), integrated discriminant improvement (IDI), net reclassification index (NRI) and decision curve analysis (DCA). A total of 1,696 patients with cirrhosis and sepsis were included in the final cohort. Our final model included the following 9 variables: age, heartrate, total bilirubin (TBIL), glucose, sodium, anion gap (AG), fungal infections, mechanical ventilation, and vasopressin. The nomogram were constructed based on these variables. The AUC values of the nomograms were 0.805 (95% CI 0.776-0.833), which provided significantly higher discrimination compared to that of SOFA score [0.684 (95% CI 0.647-0.720)], MELD-Na [0.672 (95% CI 0.636-0.709)] and ABIC [0.674(95% CI 0.638-0.710)]. We established the first nomogram for predicting in-hospital mortality in patients with liver cirrhosis and sepsis based on these factors. This nomogram can performs well and facilitates clinicians to identify people at high risk of in-hospital mortality.
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