Literature DB >> 24009288

Kidney Disease Improving Global Outcomes or creatinine kinetics criteria in acute kidney injury: a proof of concept study.

Alexandre Braga Libório1, Etienne Macedo, Rafaela Elizabeth Bayas de Queiroz, Tacyano Tavares Leite, Inessa Carvalho Queiroz Rocha, Ingrid Alves Freitas, Larissa Chagas Correa, Camila Pontes Bessa Campelo, Fabrícia Souza Araújo, Cláudio Alves de Albuquerque, Frederico Carlos de Sousa Arnaud, Francisco Daniel de Sousa, Fernanda Macedo de Oliveira Neves.   

Abstract

BACKGROUND: It has been recently mathematically demonstrated that the percentage increase in serum creatinine (SCr) can delay acute kidney injury (AKI) diagnosis in patients with previous chronic kidney disease (CKD). Based on creatinine (Cr) kinetics, it was suggested a new AKI classification using absolute increase in SCr elevation over specified time periods. However, this classification has not been evaluated in clinical studies.
METHODS: A prospective cohort study evaluated myocardial infarction patients during the first 7 days of hospital stay with daily SCr measurements. They were classified using Kidney Disease Improving Global Outcomes (KDIGO) and Cr kinetics systems. Both classifications were compared by net reclassification improvement (NRI) and area under the receiver operator characteristic (AuROC) curve regarding hospital mortality.
RESULTS: A total of 584 patients were included, of which 34.1% had previous CKD. Patients had more AKI by KDIGO than by Cr kinetics criteria (25.7 versus 18.0%, P < 0.001) and 81 patients (13.9%) had different AKI severity classification. Patients with AKI by KDIGO criteria and non-AKI by Cr kinetics had higher hospital mortality rates than patients with non-AKI using both classifications [adjusted mortality odds ratios (ORs): 4.753; 95% confidence interval (CI): 1.119-9.023, P = 0.014]. In patients with previous CKD, NRI analysis was 6.2% favoring Cr kinetics criteria. However, there was no difference using the AuROC curve analysis. In patients with no previous CKD, NRI analysis was 33.0%, favoring KDIGO, and this was in accordance with a better AuROC curve (0.828 versus 0.664, P < 0.05).
CONCLUSIONS: AKI classification proposed by a Cr kinetics model can be superior when diagnosing patients with previous CKD. However, KDIGO had a better performance in patients with no previous CKD.

Entities:  

Keywords:  acute kidney injury; acute myocardial infarction; creatinine kinetics

Mesh:

Substances:

Year:  2013        PMID: 24009288     DOI: 10.1093/ndt/gft375

Source DB:  PubMed          Journal:  Nephrol Dial Transplant        ISSN: 0931-0509            Impact factor:   5.992


  7 in total

1.  Evaluation of acute kidney injury (AKI) with RIFLE, AKIN, CK, and KDIGO in critically ill trauma patients.

Authors:  F Ülger; M Pehlivanlar Küçük; A O Küçük; N K İlkaya; N Murat; B Bilgiç; H Abanoz
Journal:  Eur J Trauma Emerg Surg       Date:  2017-07-17       Impact factor: 3.693

2.  False-Positive Rate of AKI Using Consensus Creatinine-Based Criteria.

Authors:  Jennie Lin; Hilda Fernandez; Michael G S Shashaty; Dan Negoianu; Jeffrey M Testani; Jeffrey S Berns; Chirag R Parikh; F Perry Wilson
Journal:  Clin J Am Soc Nephrol       Date:  2015-09-03       Impact factor: 8.237

3.  The clinical utility of kinetic glomerular filtration rate.

Authors:  Eoin D O'Sullivan; Arthur Doyle
Journal:  Clin Kidney J       Date:  2016-12-30

4.  Acute Kidney Injury Recognition in Low- and Middle-Income Countries.

Authors:  Jorge Cerdá; Sumit Mohan; Guillermo Garcia-Garcia; Vivekanand Jha; Srinivas Samavedam; Swarnalata Gowrishankar; Arvind Bagga; Rajasekara Chakravarthi; Ravindra Mehta
Journal:  Kidney Int Rep       Date:  2017-04-25

5.  Kinetic estimated glomerular filtration rate in critically ill patients: beyond the acute kidney injury severity classification system.

Authors:  Flávio de Oliveira Marques; Saulo Aires Oliveira; Priscila Ferreira de Lima E Souza; Wandervânia Gomes Nojoza; Maiara da Silva Sena; Taynara Muniz Ferreira; Bruno Gabriele Costa; Alexandre Braga Libório
Journal:  Crit Care       Date:  2017-11-18       Impact factor: 9.097

6.  Comparison of Plasma and Urine Biomarker Performance in Acute Kidney Injury.

Authors:  Gunnar Schley; Carmen Köberle; Ekaterina Manuilova; Sandra Rutz; Christian Forster; Michael Weyand; Ivan Formentini; Rosemarie Kientsch-Engel; Kai-Uwe Eckardt; Carsten Willam
Journal:  PLoS One       Date:  2015-12-15       Impact factor: 3.240

7.  A nationwide survey of clinical characteristics, management, and outcomes of acute kidney injury (AKI) - patients with and without preexisting chronic kidney disease have different prognoses.

Authors:  Heng-Chih Pan; Pei-Chen Wu; Vin-Cent Wu; Ya-Fei Yang; Tao-Min Huang; Chih-Chung Shiao; Te-Chuan Chen; Der-Cherng Tarng; Jui-Hsiang Lin; Wei-Shun Yang; Chiao-Yin Sun; Chan-Yu Lin; Tzong-Shinn Chu; Mai-Szu Wu; Kwan-Dun Wu; Yung-Chang Chen; Chiu-Ching Huang
Journal:  Medicine (Baltimore)       Date:  2016-09       Impact factor: 1.889

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.