ArticleProceedings. IEEE International Conference on Healthcare Informatics2019
Identifying KDIGO Trajectory Phenotypes Associated with Increased Inpatient Mortality.
Article in Proceedings. IEEE International Conference on Healthcare Informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Methods for phenotyping adult patients with acute kidney injury: a systematic review.Journal of nephrology · 2025Pooled it
- Electronic Phenotype for Detection, Staging, and Subtyping of Acute Kidney Injury.American journal of kidney diseases : the official journal of the National Kidney Foundation · 2026Article
- Presepsin as a Diagnostic and Prognostic Biomarker of Sepsis-Associated Acute Kidney Injury: A Scoping Review of Clinical Evidence.Journal of clinical medicine · 2025Review
- Machine learning-derived multivariate renal function trajectories in acute kidney injury in critically ill patients: a multicentre retrospective study.Clinical kidney journal · 2025Article
- Evaluating the kidney disease progression using a comprehensive patient profiling algorithm: A hybrid clustering approach.PloS one · 2025Article
- [Artificial intelligence and acute kidney injury].Medizinische Klinik, Intensivmedizin und Notfallmedizin · 2024Review
- A Review of Electronic Early Warning Systems for Acute Kidney Injury.Advances in urology · 2024Review
- Incidence, Outcomes, and Predictors of Subphenotypes of Acute Kidney Injury among Acute Respiratory Distress Syndrome Patients: A Prospective Observational Study.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2023Article
- Precision management of acute kidney injury in the intensive care unit: current state of the art.Intensive care medicine · 2023Review
- Subphenotypes in acute kidney injury: a narrative review.Critical care (London, England) · 2022Review
- Comparison of Static and Dynamic Baseline Creatinine Surrogates for Defining Acute Kidney Injury.Nephron · 2021Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Acute kidney injury (AKI) is a complex systemic syndrome associated with high morbidity and mortality and risk for the subsequent development of renal and non-renal complications. Nearly 50% of patients in the ICU experience AKI. AKI severity is a key metric for evaluating patients risk of hospital mortality. Current AKI stratification is based on absolute changes in Serum Creatinine (SCr) and the maximal increase relative to the patients baseline value. However, such measurement does not consider either the progression or duration of AKI, both of which are associated with adverse outcomes post-AKI. In this article, by leveraging a large volume of SCr temporal variabilities, we present a novel model called Trajectory of Acute Kidney Injury (TAKI) for the identification of AKI trajectory subtypes. Experimental results demonstrate that TAKI is better than the existing trajectory subtyping methods on both the inpatient mortality stratification and the post-7-day AKI progression estimation. With TAKI, it is found that the trend of KDIGO trajectory appears to be more highly associated with inpatient mortality rates than the maximum KDIGO score.
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Registered trials
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