Acute kidney injury prediction models: Current concepts and future strategies

Sehoon Park, Hajeong Lee

Research output: Contribution to journalArticle

Abstract

Purpose of reviewAcute kidney injury (AKI) is a critical condition associated with poor patient outcomes. We aimed to review the current concepts and future strategies regarding AKI risk prediction models.Recent findingsRecent studies have shown that AKI occurs frequently in patients with common risk factors and certain medical conditions. Prediction models for AKI risk have been reported in medical fields such as critical care medicine, surgery, nephrotoxic agent exposure, and others. However, practical, generalizable, externally validated, and robust AKI prediction models remain relatively rare. Further efforts to develop AKI prediction models based on comprehensive clinical data, artificial intelligence, improved delivery of care, and novel biomarkers may help improve patient outcomes through precise AKI risk prediction.SummaryThis brief review provides insights for current concepts for AKI prediction model development. In addition, by overviewing the recent AKI prediction models in various medical fields, future strategies to construct advanced AKI prediction models are suggested.

Original languageEnglish
Pages (from-to)552-559
Number of pages8
JournalCurrent Opinion in Nephrology and Hypertension
Volume28
Issue number6
DOIs
StatePublished - 1 Nov 2019

Fingerprint

Acute Kidney Injury
Artificial Intelligence
Critical Care
Biomarkers
Medicine
Kidney
Wounds and Injuries

Keywords

  • acute kidney injury
  • artificial intelligence
  • machine-learning
  • model
  • outcome

Cite this

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Acute kidney injury prediction models : Current concepts and future strategies. / Park, Sehoon; Lee, Hajeong.

In: Current Opinion in Nephrology and Hypertension, Vol. 28, No. 6, 01.11.2019, p. 552-559.

Research output: Contribution to journalArticle

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