ArticleCritical care (London, England)2024
Machine learning derived serum creatinine trajectories in acute kidney injury in critically ill patients with sepsis.
Article in Critical care (London, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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37 citing papers in PubMed.
- Targeting integrated cell death networks in sepsis‑associated acute kidney injury: Shared regulatory nodes and diet‑related small molecule modulation (Review).International journal of molecular medicine · 2026Review
- Impact of dynamic blood glucose trajectories on mortality in critically ill non-traumatic intracranial hemorrhage patients: a retrospective cohort study.BMC neurology · 2026Article
- Early identification of acute kidney injury progression in critically ill patients with sepsis: interpretable machine learning approach.Clinical kidney journal · 2026Article
- Explainable Retrospective Sepsis Classification Based on Elixhauser Comorbidity Groups Using Machine and Deep Learning on MIMIC-IV.Journal of clinical medicine · 2026Article
- 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
- Blood biomarker trajectories in ICU-directed prediction models - A scoping review.The EPMA journal · 2026Review
- Deep-learning time-series anomaly detection of acute kidney injury from creatinine-eGFR trajectories in the ICU.PLOS digital health · 2026Article
- Identification of Clinical Subtypes of Surgical Sepsis in Critically Ill Patients Based on K-Means Clustering and Development of Parsimonious Classifier Model for High-Risk Subtype.Journal of inflammation research · 2026Article
- Association of albumin trajectories and cumulative exposure with in-hospital mortality in acute pancreatitis: a retrospective cohort study.International journal of surgery (London, England) · 2026Article
- Cumulative burden and dynamic trajectories of heart rate as predictors of prognosis in acute pancreatitis: an 18-year cohort study.International journal of surgery (London, England) · 2026Article
- Trajectory models of serum creatinine and 28-day mortality in critically ill patients with sepsis complicated by type 2 diabetes mellitus: a cohort study.Frontiers in endocrinology · 2026Article
- Current and Future Applications of AI-Driven Predictive Modeling and a Proposed Framework for AI-Bioprognostics in Kidney Care.Risk management and healthcare policy · 2026Review
- Prioritizing perioperative organ injury prevention: a call to action from China's county-level hospitals.Frontiers in medicine · 2026Article
- Prognostic value of the creatinine-to-albumin ratio for 28-day mortality in patients with sepsis and diabetes: integrating renal and nutritional status in the ICU.Frontiers in nutrition · 2026Article
- NutriSighT: Interpretable Transformer Model for Dynamic Prediction of Underfeeding Enteral Nutrition in Mechanically Ventilated Patients.Nature communications · 2025Article
- Association of different serum creatinine trajectories with 28-day mortality in patients with acute kidney injury on chronic kidney disease: based on the MIMIC-IV database.European journal of medical research · 2025Article
- Early fluid therapy trajectories in acute pancreatitis: a retrospective cohort study.World journal of emergency surgery : WJES · 2025Article
- Influence of early temperature trajectories on clinical outcomes in traumatic brain injury: a multicenter validation study using machine learning.European journal of medical research · 2025Article
- Acute kidney injury after lung transplantation: prediction, prevention, and management.Renal failure · 2025Review
- Utilization of lactate trajectory models for predicting acute kidney injury and mortality in patients with hyperlactatemia: insights across three independent cohorts.Renal failure · 2025Article
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10 authors.
Funding
Abstract
backgroundCurrent classification for acute kidney injury (AKI) in critically ill patients with sepsis relies only on its severity-measured by maximum creatinine which overlooks inherent complexities and longitudinal evaluation of this heterogenous syndrome. The role of classification of AKI based on early creatinine trajectories is unclear.
methodsThis retrospective study identified patients with Sepsis-3 who developed AKI within 48-h of intensive care unit admission using Medical Information Mart for Intensive Care-IV database. We used latent class mixed modelling to identify early creatinine trajectory-based classes of AKI in critically ill patients with sepsis. Our primary outcome was development of acute kidney disease (AKD). Secondary outcomes were composite of AKD or all-cause in-hospital mortality by day 7, and AKD or all-cause in-hospital mortality by hospital discharge. We used multivariable regression to assess impact of creatinine trajectory-based classification on outcomes, and eICU database for external validation.
resultsAmong 4197 patients with AKI in critically ill patients with sepsis, we identified eight creatinine trajectory-based classes with distinct characteristics. Compared to the class with transient AKI, the class that showed severe AKI with mild improvement but persistence had highest adjusted risks for developing AKD (OR 5.16; 95% CI 2.87-9.24) and composite 7-day outcome (HR 4.51; 95% CI 2.69-7.56). The class that demonstrated late mild AKI with persistence and worsening had highest risks for developing composite hospital discharge outcome (HR 2.04; 95% CI 1.41-2.94). These associations were similar on external validation.
conclusionsThese 8 classes of AKI in critically ill patients with sepsis, stratified by early creatinine trajectories, were good predictors for key outcomes in patients with AKI in critically ill patients with sepsis independent of their AKI staging.
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