ArticleScientific reports2024
Predictive model of risk factors for 28-day mortality in patients with sepsis or sepsis-associated delirium based on the MIMIC-IV database.
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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Who cites it
10 citing papers in PubMed.
- Artificial Intelligence Models for Mortality and Outcome Prediction in Intensive Care Unit Sepsis: A Systematic Review.Journal of personalized medicine · 2026Review
- Association between prognostic nutritional index and mortality in patients with sepsis-associated delirium: a retrospective cohort study using the MIMIC-IV database.BMC nutrition · 2026Article
- Joint analysis of hemoglobin-to-RDW and creatinine-to-albumin ratios for mortality prediction in critical heart failure.iScience · 2026Article
- Research Topics and Trends in MIMIC-IV: A Large ICU Database Relevant for Critical Care Nursing.Nursing in critical care · 2026Review
- Integrating serum ferritin and neutrophil-to-lymphocyte ratio with Sequential Organ Failure Assessment score improves mortality prediction in sepsis.World journal of methodology · 2026Article
- Serum iron is associated with the prognosis in sepsis based on a large-scale database.BMC infectious diseases · 2026Article
- Association between serum creatinine-to-albumin ratio and 28-day mortality in intensive care unit patients following cardiac surgery: analysis of mimic-iv data.BMC cardiovascular disorders · 2025Article
- Development of a prediction model for in-hospital mortality in immunocompromised chronic kidney diseases patients with severe infection.BMC nephrology · 2025Article
- Machine learning-based identification of leptin-associated biomarkers and prognostic prediction models in sepsis.Frontiers in cellular and infection microbiology · 2025Article
- Machine learning approach for the prediction of 30-day mortality in patients with sepsis-associated delirium.PloS one · 2025Article
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7 authors.
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Abstract
Research on the severity and prognosis of sepsis with or without progressive delirium is relatively insufficient. We constructed a prediction model of the risk factors for 28-day mortality in patients who developed sepsis or sepsis-associated delirium. The modeling group of patients diagnosed with Sepsis-3 and patients with progressive delirium of related indicators were selected from the MIMIC-IV database. Relevant independent risk factors were determined and integrated into the prediction model. Receiver operating characteristic (ROC) curves and the Hosmer-Lemeshow (HL) test were used to evaluate the prediction accuracy and goodness-of-fit of the model. Relevant indicators of patients with sepsis or progressive delirium admitted to the intensive care unit (ICU) of a 3A hospital in Xinjiang were collected and included in the verification group for comparative analysis and clinical validation of the prediction model. The total length of stay in the ICU, hemoglobin levels, albumin levels, activated partial thrombin time, and total bilirubin level were the five independent risk factors in constructing a prediction model. The area under the ROC curve of the predictive model (0.904) and the HL test result (χ
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