Literature DB >> 31514906

The Role of Risk Prediction Models in Prevention and Management of AKI.

Luke E Hodgson1, Nicholas Selby2, Tao-Min Huang3, Lui G Forni4.   

Abstract

Acute kidney injury is a major health care problem. Improving recognition of those at risk and highlighting those who have developed AKI at an earlier stage remains a priority for research and clinical practice. Prediction models to risk-stratify patients and electronic alerts for AKI are two approaches that could address previously highlighted shortcomings in management and facilitate timely intervention. We describe and critique available prediction models and the effects of the use of AKI alerts on patient outcomes are reviewed. Finally, the potential for prediction models to enrich population subsets for other diagnostic approaches and potential research, including biomarkers of AKI, are discussed.
Copyright © 2019. Published by Elsevier Inc.

Entities:  

Keywords:  Acute kidney injury; electronic alerts; prediction models

Mesh:

Year:  2019        PMID: 31514906     DOI: 10.1016/j.semnephrol.2019.06.002

Source DB:  PubMed          Journal:  Semin Nephrol        ISSN: 0270-9295            Impact factor:   5.299


  10 in total

1.  Global Perspectives in Acute Kidney Injury: England.

Authors:  Andrew Lewington; Becky Bonfield
Journal:  Kidney360       Date:  2022-06-28

2.  Strategies to Prevent Acute Kidney Injury after Pediatric Cardiac Surgery: A Network Meta-Analysis.

Authors:  Jef Van den Eynde; Nicolas Cloet; Robin Van Lerberghe; Michel Pompeu B O Sá; Dirk Vlasselaers; Jaan Toelen; Jan Y Verbakel; Werner Budts; Marc Gewillig; Shelby Kutty; Hans Pottel; Djalila Mekahli
Journal:  Clin J Am Soc Nephrol       Date:  2021-10       Impact factor: 10.614

Review 3.  AKI: an increasingly recognized risk factor for CKD development and progression.

Authors:  J T Kurzhagen; S Dellepiane; V Cantaluppi; H Rabb
Journal:  J Nephrol       Date:  2020-07-10       Impact factor: 3.902

Review 4.  Artificial Intelligence in Acute Kidney Injury: From Static to Dynamic Models.

Authors:  Nupur S Mistry; Jay L Koyner
Journal:  Adv Chronic Kidney Dis       Date:  2021-01       Impact factor: 3.620

Review 5.  Artificial Intelligence in Acute Kidney Injury Risk Prediction.

Authors:  Joana Gameiro; Tiago Branco; José António Lopes
Journal:  J Clin Med       Date:  2020-03-03       Impact factor: 4.241

6.  Impact of a computerized decision support tool deployed in two intensive care units on acute kidney injury progression and guideline compliance: a prospective observational study.

Authors:  Christopher Bourdeaux; Erina Ghosh; Louis Atallah; Krishnamoorthy Palanisamy; Payaal Patel; Matthew Thomas; Timothy Gould; John Warburton; Jon Rivers; John Hadfield
Journal:  Crit Care       Date:  2020-11-23       Impact factor: 9.097

7.  External validation of the Madrid Acute Kidney Injury Prediction Score.

Authors:  Jacqueline Del Carpio; Maria Paz Marco; Maria Luisa Martin; Lourdes Craver; Elias Jatem; Jorge Gonzalez; Pamela Chang; Mercedes Ibarz; Silvia Pico; Gloria Falcon; Marina Canales; Elisard Huertas; Iñaki Romero; Nacho Nieto; Alfons Segarra
Journal:  Clin Kidney J       Date:  2021-03-26

8.  A Novel Radiomics-Based Machine Learning Framework for Prediction of Acute Kidney Injury-Related Delirium in Patients Who Underwent Cardiovascular Surgery.

Authors:  Xin Xue; Wen Chen; Xin Chen
Journal:  Comput Math Methods Med       Date:  2022-03-18       Impact factor: 2.238

9.  Prediction Models for One-Year Survival of Adult Patients with Acute Kidney Injury: A Longitudinal Study Based on the Data from the Medical Information Mart for Intensive Care III Database.

Authors:  Lifang Zhou; Laping Chu; Junqiong Peng; Shenhan Yin; Yafen Yu
Journal:  Evid Based Complement Alternat Med       Date:  2022-07-05       Impact factor: 2.650

10.  A Simpler Machine Learning Model for Acute Kidney Injury Risk Stratification in Hospitalized Patients.

Authors:  Yirui Hu; Kunpeng Liu; Kevin Ho; David Riviello; Jason Brown; Alex R Chang; Gurmukteshwar Singh; H Lester Kirchner
Journal:  J Clin Med       Date:  2022-09-26       Impact factor: 4.964

  10 in total

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