ArticleCritical care (London, England)2022
Gene signature for the prediction of the trajectories of sepsis-induced acute kidney injury.
Article in Critical care (London, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine learning-based mortality risk prediction models in patients with sepsis-associated acute kidney injury: a systematic review.Frontiers in medicine · 2025Pooled it
- Machine learning model for predicting hypotension following continuous renal replacement therapy initiation in end-stage kidney disease patients: a SHAP-interpretable approach.Frontiers in medicine · 2026Article
- Integrative multi-omics analysis identifies microbial dysbiosis and functional metabolic reprogramming in acute kidney injury.Frontiers in medicine · 2026Article
- Machine learning model predicts clotting risk during CRRT in ESKD patients: a SHAP-interpretable approach.Renal failure · 2025Article
- Research Progress on Sepsis Diagnosis and Monitoring Based on Omics Technologies: A Review.Diagnostics (Basel, Switzerland) · 2025Review
- A study on the factors influencing mortality risk in sepsis-induced acute kidney injury based on analysis of the MIMIC database.Clinical and experimental medicine · 2025Article
- Current and novel biomarkers in cardiogenic shock.European journal of heart failure · 2025Review
- Identification of Key Genes and Potential Therapeutic Targets in Sepsis-Associated Acute Kidney Injury Using Transformer and Machine Learning Approaches.Bioengineering (Basel, Switzerland) · 2025Article
- Establishment and validation of the prediction model based on lymphocyte subsets for acute kidney injury in sepsis patients.Frontiers in immunology · 2025Article
- Predictive models of sepsis-associated acute kidney injury based on machine learning: a scoping review.Renal failure · 2024Article
- Chest computed tomography for patients with sepsis in the emergency intensive care unit.Scientific data · 2024Article
- Identifying septic shock subgroups to tailor fluid strategies through multi-omics integration.Nature communications · 2024Article
- Associations between life's essential 8 and metabolic health among us adults: insights of NHANES from 2005 to 2018.Acta diabetologica · 2024Article
- Exploring disease axes as an alternative to distinct clusters for characterizing sepsis heterogeneity.Intensive care medicine · 2023Article
- SOD1 is a novel prognostic biomarker of acute kidney injury following cardiothoracic surgery.BMC nephrology · 2023Article
- Development of a nomogram model for the early prediction of sepsis-associated acute kidney injury in critically ill patients.Scientific reports · 2023Observational
- Review
- Strength of Omics in Uncovering Sepsis Mechanisms-A Perspective.Current health sciences journalReview
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Authors and funding
12 authors.
Funding
Abstract
backgroundAcute kidney injury (AKI) is a common complication in sepsis. However, the trajectories of sepsis-induced AKI and their transcriptional profiles are not well characterized.
methodsSepsis patients admitted to centres participating in Chinese Multi-omics Advances In Sepsis (CMAISE) from November 2020 to December 2021 were enrolled, and gene expression in peripheral blood mononuclear cells was measured on Day 1. The renal function trajectory was measured by the renal component of the SOFA score (SOFA
resultsA total of 172 sepsis patients were enrolled during the study period. The renal function trajectory was classified into four types: non-AKI (SOFA
conclusionsOur study identified four subtypes of sepsis-induced AKI based on kidney injury trajectories. The landscape of host response aberrations across these subtypes was characterized. An SVM model based on a gene signature was developed to predict renal function trajectories, and showed better performance than the clinical variable-based model. Future studies are warranted to validate the gene model in distinguishing persistent from transient AKI.
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