ArticleFrontiers in medicine2025
Development of a nomogram to predict in-ICU mortality of elderly patients with sepsis-associated liver injury: an analysis of the MIMIC-IV database.
Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Research Topics and Trends in MIMIC-IV: A Large ICU Database Relevant for Critical Care Nursing.Nursing in critical care · 2026Review
- Diagnostic value of the combined detection of serum tumor necrosis factor-α and fecal calprotectin in early sepsis-related encephalopathy.Frontiers in medicine · 2025Article
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7 authors.
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Abstract
Background: Sepsis-associated liver injury (SALI) is a frequent and lethal complication among critically ill patients in the intensive care unit (ICU). Despite its significance, there has been a notable lack of specialized tools for evaluating the in-ICU mortality risk in these patients. This study seeks to address this gap by developing a practical nomogram to predict risk factors associated with in-ICU mortality in patients suffering from SALI. Methods: Data were extracted from the MIMIC-IV database, a Critical Care Public Medical Information Mart. The diagnostic criteria for sepsis adhered to the Sepsis 3.0 guidelines, requiring a SOFA score of ≥ 2. SALI was defined as total bilirubin (TBIL) levels > 2 mg/dL in patients with sepsis and an International Normalized Ratio (INR) > 1.5. Lasso regression analyses were conducted on the training set ( Results: A total of 934 elderly patients with SALI were included in the study. Random seeds were allocated in a 7:3 ratio, resulting in training and validation sets comprising 653 and 281 patients, respectively. Variables were selected using lasso regression, culminating in the inclusion of six final variables within the model. The nomogram was evaluated against standard ICU scoring systems, specifically SAPS II and SOFA scores, yielding AUROC values of 0.814, 0.798, and 0.634 for the training set, respectively. Conversely, the validation set demonstrated AUROC values of 0.809, 0.791, and 0.596. The nomogram exhibited strong predictive performance for in-ICU outcomes. Conclusion: A prediction model of in-ICU mortality in SALI elderly patients was established by screening variables through lasso regression. Nomgram was the best predictor of in-ICU mortality in SALI patients, which has a high reference value and clinical application.
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