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Optimum methodology for estimating baseline serum creatinine for the acute kidney injury classification.

Publication ,  Journal Article
Thongprayoon, C; Cheungpasitporn, W; Kittanamongkolchai, W; Srivali, N; Ungprasert, P; Kashani, K
Published in: Nephrology (Carlton)
December 2015

AIM: This study aimed to investigate how varied methods of determining baseline serum creatinine (SCr) would affect acute kidney injury (AKI) diagnosis and prediction of 60 day mortality in critically ill patients following an episode of AKI. METHODS: This is a single-centre retrospective study conducted at a tertiary referral hospital. All adult intensive care unit (ICU) patients between January and December 2011, who had at least one SCr values measured between 7 days and 180 days before hospital admission and during ICU stay, were analyzed. The baseline SCr was calculated using either the most recent (SCrmost recent ) or the minimum (SCrmin ) value of SCr measurement over the specified assessment period before hospital admission. AKI was defined based on KDIGO SCr definition. The primary outcome was 60 day mortality after ICU admission. RESULTS: A total of 4020 patients were included in the analysis. AKI was detected in 1204 (30.0%) using the SCrmin and 945 (23.5%) using the SCrmost recent (P < 0.001). Compared with patients without AKI regardless of baseline SCr methodology, the 60 day mortality risk of patients who developed AKI using the SCrmin and SCrmost recent was significantly increased (odds ratio (OR) = 3.74; 95% confidence interval (CI) 2.98-4.70). Similarly, the risk of 60 day mortality in patients who met AKI criteria using the SCrmin but not the SCrmost recent was significant higher than in patients without AKI (OR = 2.04; 95% CI 1.36-3.00). CONCLUSION: Using the minimum value of preadmission SCr as a baseline kidney function not only can detect more AKI cases, but also provides the better predictive ability for 60 day mortality.

Duke Scholars

Published In

Nephrology (Carlton)

DOI

EISSN

1440-1797

Publication Date

December 2015

Volume

20

Issue

12

Start / End Page

881 / 886

Location

Australia

Related Subject Headings

  • Urology & Nephrology
  • Time Factors
  • Tertiary Care Centers
  • Risk Factors
  • Risk Assessment
  • Retrospective Studies
  • Prognosis
  • Predictive Value of Tests
  • Odds Ratio
  • Models, Biological
 

Citation

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Thongprayoon, C., Cheungpasitporn, W., Kittanamongkolchai, W., Srivali, N., Ungprasert, P., & Kashani, K. (2015). Optimum methodology for estimating baseline serum creatinine for the acute kidney injury classification. Nephrology (Carlton), 20(12), 881–886. https://doi.org/10.1111/nep.12525
Thongprayoon, Charat, Wisit Cheungpasitporn, Wonngarm Kittanamongkolchai, Narat Srivali, Patompong Ungprasert, and Kianoush Kashani. “Optimum methodology for estimating baseline serum creatinine for the acute kidney injury classification.Nephrology (Carlton) 20, no. 12 (December 2015): 881–86. https://doi.org/10.1111/nep.12525.
Thongprayoon C, Cheungpasitporn W, Kittanamongkolchai W, Srivali N, Ungprasert P, Kashani K. Optimum methodology for estimating baseline serum creatinine for the acute kidney injury classification. Nephrology (Carlton). 2015 Dec;20(12):881–6.
Thongprayoon, Charat, et al. “Optimum methodology for estimating baseline serum creatinine for the acute kidney injury classification.Nephrology (Carlton), vol. 20, no. 12, Dec. 2015, pp. 881–86. Pubmed, doi:10.1111/nep.12525.
Thongprayoon C, Cheungpasitporn W, Kittanamongkolchai W, Srivali N, Ungprasert P, Kashani K. Optimum methodology for estimating baseline serum creatinine for the acute kidney injury classification. Nephrology (Carlton). 2015 Dec;20(12):881–886.
Journal cover image

Published In

Nephrology (Carlton)

DOI

EISSN

1440-1797

Publication Date

December 2015

Volume

20

Issue

12

Start / End Page

881 / 886

Location

Australia

Related Subject Headings

  • Urology & Nephrology
  • Time Factors
  • Tertiary Care Centers
  • Risk Factors
  • Risk Assessment
  • Retrospective Studies
  • Prognosis
  • Predictive Value of Tests
  • Odds Ratio
  • Models, Biological