ArticleRenal failure2025
Heart failure subphenotypes based on mean arterial pressure trajectory identify patients at increased risk of acute kidney injury.
Article in Renal failure, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Net renal perfusion - an emerging concept during development of AKI in the critically ill.Renal failure · 2026Article
- Heart Failure sub-phenotyping and in-hospital and 28-day mortality prediction based on mean arterial pressure trajectory modeling.American heart journal plus : cardiology research and practice · 2026Article
- Blood pressure response index and acute kidney injury progression in heart failure patients: a retrospective cohort study from MIMIC-IV.BMC nephrology · 2025Article
- The Impact of Triglyceride-Glucose Index Trajectories on Incidence and Recurrent Cardiovascular Events: Evidence from a Retrospective Cohort Study.Vascular health and risk management · 2025Article
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7 authors.
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Abstract
backgroundAcute kidney injury (AKI) is a common complication in heart failure (HF) patients. Patients with heart failure who experience renal injury tend to have a poor prognosis. The objective of this study is to examine the correlation between the occurrence of AKI in heart failure patients and different mean arterial pressure (MAP) trajectories, with the goal of improving early identification and intervention for AKI.
methodsA retrospective study was conducted on patients with heart failure using data from the Medical Information Mart for Intensive Care IV (MIMIC-IV). We utilized the group-based trajectory modeling (GBTM) method to classify the 24-hour MAP change trajectories in heart failure patients. The occurrence of AKI within the first 7 days of intensive care unit (ICU) admission was considered the outcome. The impact of MAP trajectories on AKI occurrence in heart failure patients was analyzed using Cox proportional hazards models, competing risk models, and doubly robust estimation methods.
resultsA cohort of 8,502 HF patients was analyzed, with their 24-hour MAP trajectories categorized into five groups: Low MAP group (Class 1), Medium MAP group (Class 2), Low-medium MAP group (Class 3), High-to-low MAP group (Class 4), and High MAP group (Class 5). The results from the doubly robust analysis revealed that Class 4 exhibited a significantly increased AKI risk than Class 3 (HR 1.284, 95% CI 1.085-1.521,
conclusionsThe 24-hour MAP trajectory in HF patients influences the risk of AKI. A rapid decrease in MAP (Class 4) is associated with a higher AKI risk, while maintaining MAP at a moderate level (Class 2) significantly reduces this risk. Therefore, closely monitoring MAP changes is crucial for preventing AKI in HF.
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