ArticleScientific reports2023
Development of a nomogram for predicting 90-day mortality in patients with sepsis-associated liver injury.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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23 citing papers in PubMed, 37 citations in OpenAlex.
- Development and external validation of the HCH and HPMS prognostic indices for sepsis: a retrospective model development study using a Multi-Objective Non-Newtonian Fluid optimization algorithm.BMC medical informatics and decision making · 2026Article
- Association Between Systemic Immune-Inflammation Index and Sepsis-Induced Liver Injury in Adult Patients With Sepsis: A Retrospective Cohort Study.Immunity, inflammation and disease · 2026Article
- The alkylation of AIM2 by itaconate mediates macrophage PANoptosis during sepsis.Cellular & molecular immunology · 2026Article
- Association of the Albumin-Bilirubin score with 7-day incident delirium risk following bloodstream infection in critically ill adults: evidence from a propensity-weighted cohort.BMC infectious diseases · 2026Article
- Maresin-1 Alleviates Sepsis-Induced Liver Injury by Regulating Apoptosis and Autophagy via Activation of the PI3K/Akt Signaling Pathway in Mice.Current issues in molecular biology · 2026Article
- Prognostic value of easy Albumin-Bilirubin score in liver cirrhosis: a comparison with established scoring systems.European journal of gastroenterology & hepatology · 2026Article
- Aminotransferase-to-platelet Ratio Index for Sepsis-associated Liver Dysfunction: Promising Triage Signal but Phenotype Confounding and Implementation Calibration must be Intensive Care Unit Ready.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2026Article
- NHWD-870, a Potent BET Inhibitor, Ameliorated Endotoxemia-Induced Hepatic Inflammation via Suppression of BRD4-STAT1 Signaling and Macrophage M1 Polarization.Journal of inflammation research · 2026Article
- Early risk stratification of sepsis-related liver injury via machine learning: a multicohort study.Frontiers in medicine · 2026Article
- Identification and experimental validation of CD74, PGLYRP1, and TXN as potential biomarkers in rheumatoid arthritis: an integrative bulk and ScRNA-seq study.Frontiers in immunology · 2026Article
- Association between albumin-corrected anion gap and 60-day all-cause mortality in critically ill shock patients.European journal of medical research · 2025Article
- Mitochondrial dysfunction in sepsis-induced liver injury: from pathophysiology to preclinical therapeutic targets.Journal of translational medicine · 2025Review
- Iron metabolism and sepsis-associated liver injury: Methodological considerations and clinical perspectives.World journal of hepatology · 2025Article
- Prognostic value of albumin-corrected anion gap in critically ill patients with sepsis-associated liver injury: a retrospective study.BMC infectious diseases · 2025Article
- Multiple organ scoring systems for predicting in-hospital mortality of sepsis patients in the intensive care unit.Open medicine (Warsaw, Poland) · 2025Article
- Establishment and Validation of a Risk Prediction Model for Sepsis-Associated Liver Injury in ICU Patients: A Retrospective Cohort Study.Infection and drug resistance · 2025Article
- Aspirin is associated with improved 30-day mortality in patients with sepsis-associated liver injury: a retrospective cohort study based on MIMIC IV database.Frontiers in pharmacology · 2025Article
- Association between lactate-to-albumin ratio and 28-days all-cause mortality in patients with sepsis-associated liver injury: a retrospective cohort study.BMC infectious diseases · 2024Article
- An interpretable machine learning model for predicting 28-day mortality in patients with sepsis-associated liver injury.PloS one · 2024Article
- Analysis of risk factors for sepsis-related liver injury and construction of a prediction model.Frontiers in public health · 2024Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The high mortality rate in sepsis patients is related to sepsis-associated liver injury (SALI). We sought to develop an accurate forecasting nomogram to estimate individual 90-day mortality in SALI patients. Data from 34,329 patients were extracted from the public Medical Information Mart for Intensive Care (MIMIC-IV) database. SALI was defined by total bilirubin (TBIL) > 2 mg/dL and the occurrence of an international normalized ratio (INR) > 1.5 in the presence of sepsis. Logistic regression analysis was performed to establish a prediction model called the nomogram based on the training set (n = 727), which was subsequently subjected to internal validation. Multivariate logistic regression analysis showed that SALI was an independent risk factor for mortality in patients with sepsis. The Kaplan‒Meier curves for 90-day survival were different between the SALI and non-SALI groups after propensity score matching (PSM) (log rank: P < 0.001 versus P = 0.038), regardless of PSM balance. The nomogram demonstrated better discrimination than the sequential organ failure assessment (SOFA) score, logistic organ dysfunction system (LODS) score, simplified acute physiology II (SAPS II) score, and Albumin-Bilirubin (ALBI) score in the training and validation sets, with areas under the receiver operating characteristic curve (AUROC) of 0.778 (95% CI 0.730-0.799, P < 0.001) and 0.804 (95% CI 0.713-0.820, P < 0.001), respectively. The calibration plot showed that the nomogram was sufficiently successful to predict the probability of 90-day mortality in both groups. The DCA of the nomogram demonstrated a higher net benefit regarding clinical usefulness than SOFA, LODS, SAPSII, and ALBI scores in the two groups. The nomogram performs exceptionally well in predicting the 90-day mortality rate in SALI patients, which can be used to assess the prognosis of patients with SALI and may assist in guiding clinical practice to enhance patient outcomes.
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