ReviewAmerican journal of nephrology2024
Biomarker Enrichment in Sepsis-Associated Acute Kidney Injury: Finding High-Risk Patients in the Intensive Care Unit.
Review in American journal of nephrology, 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 12 citations in OpenAlex.
- Biomarker-guided immunomodulation in septic shock: navigating controversies and therapeutic implications for Critical Care.Critical care (London, England) · 2026Article
- Serum Human epididymal protein 4 as a predictor of adverse events in acute ischemic stroke patients receiving antiplatelet therapy.BMC cardiovascular disorders · 2026Article
- Pioglitazone Attenuates Sepsis-Associated Acute Kidney Injury by Modulating TLR-4/NF-κB Signaling and Improving Survival and Renal Function.Journal of clinical medicine · 2026Article
- S100A12 drives inflammatory and metabolic reprogramming in sepsis-associated acute kidney injury.Frontiers in molecular biosciences · 2026Review
- The Clinical View of Sepsis-Associated AKI: How Basic Science Can Help Solve This Problem.Seminars in nephrology · 2025Review
- The predictive value of renal vascular resistance index and serum biomarkers for sepsis-associated acute kidney injury: a retrospective study.BMC nephrology · 2025Article
- Acute Kidney Injury During Sepsis and Prognostic Role of Coexistent Chronic Heart Failure.Journal of clinical medicine · 2025Review
- The Crucial Roles of Platelets as Immune Mediators in Sepsis.Journal of inflammation research · 2025Review
- Characteristics and prognosis of patients with pathogenic microorganism-positive sepsis AKI from ICU: a retrospective cohort study.Frontiers in cellular and infection microbiology · 2025Article
- Clinical impact and safety of continuous renal replacement therapy in critically ill patients with solid tumors and acute kidney injury: a retrospective cohort analysis.American journal of cancer research · 2025Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
backgroundSepsis-associated acute kidney injury (AKI) is a leading comorbidity in admissions to the intensive care unit. While a gold standard definition exists, it remains imperfect and does not allow for the timely identification of patients in the setting of critical illness. This review will discuss the use of biochemical and electronic biomarkers to allow for prognostic and predictive enrichment of patients with sepsis-associated AKI over and above the use of serum creatinine and urine output. SUMMARY: Current data suggest that several biomarkers are capable of identifying patients with sepsis at risk for the development of severe AKI and other associated morbidity. This review discusses these data and these biomarkers in the setting of sub-phenotyping and endotyping sepsis-associated AKI. While not all these tests are widely available and some require further validation, in the near future we anticipate several new tools to help nephrologists and other providers better care for patients with sepsis-associated AKI. KEY MESSAGES: Predictive and prognostic enrichment using both traditional biomarkers and novel biomarkers in the setting of sepsis can identify subsets of patients with either similar outcomes or similar pathophysiology, respectively. Novel biomarkers can identify kidney injury in patients without consensus definition AKI (e.g., changes in creatinine or urine output) and can predict other adverse outcomes (e.g., severe consensus definition AKI, inpatient mortality). Finally, emerging artificial intelligence and machine learning-derived risk models are able to predict sepsis-associated AKI in critically ill patients using advanced learning techniques and several laboratory and vital sign measurements.
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Registered trials
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