Derivation and validation of the renal angina index to improve the prediction of acute kidney injury in critically ill children

Rajit K. Basu*, Michael Zappitelli, Lori Brunner, Yu Wang, Hector R. Wong, Lakhmir S. Chawla, Derek S. Wheeler, Stuart L. Goldstein

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

203 Scopus citations

Abstract

Reliable prediction of severe acute kidney injury (AKI) has the potential to optimize treatment. Here we operationalized the empiric concept of renal angina with a renal angina index (RAI) and determined the predictive performance of RAI. This was assessed on admission to the pediatric intensive care unit, for subsequent severe AKI (over 200% rise in serum creatinine) 72 h later (Day-3 AKI). In a multicenter four cohort appraisal (one derivation and three validation), incidence rates for a Day 0 RAI of 8 or more were 15-68% and Day-3 AKI was 13-21%. In all cohorts, Day-3 AKI rates were higher in patients with an RAI of 8 or more with the area under the curve of RAI for predicting Day-3 AKI of 0.74-0.81. An RAI under 8 had high negative predictive values (92-99%) for Day-3 AKI. RAI outperformed traditional markers of pediatric severity of illness (Pediatric Risk of Mortality-II) and AKI risk factors alone for prediction of Day-3 AKI. Additionally, the RAI outperformed all KDIGO stages for prediction of Day-3 AKI. Thus, we operationalized the renal angina concept by deriving and validating the RAI for prediction of subsequent severe AKI. The RAI provides a clinically feasible and applicable methodology to identify critically ill children at risk of severe AKI lasting beyond functional injury. The RAI may potentially reduce capricious AKI biomarker use by identifying patients in whom further testing would be most beneficial.

Original languageEnglish (US)
Pages (from-to)659-667
Number of pages9
JournalKidney international
Volume85
Issue number3
DOIs
StatePublished - Mar 2014

Funding

We thank the following investigators who contributed biological samples and patient data for the database supporting cohort 4: Natalie Z. Cvijanovich (Children’s Hospital Oakland), Mark Hall (Nationwide Children’s Hospital), Geoffrey L. Allen (Children’s Mercy Hospital), Neal J. Thomas (Hershey Children’s Hospital), Robert J. Freishtat (Children’s National Medical Center), Nick Anas (Children’s Hospital of Orange County), Keith Meyer (Miami Children’s Hospital), Paul A. Checchia (Texas Children’s Hospital), Richard Lin (The Children’s Hospital of Philadelphia), Michael T. Bigham (Akron Children’s Hospital), Anita Sen (Morgan Stanley Children’s Hospital), Jeffrey Nowak (Children’s Hospital and Clinics of Minnesota), Michael Quasney (Children’s Hospital of Wisconsin), Jared W. Henricksen (St Christopher’s Hospital for Children), Arun Chopra (CS Mott Children’s Hospital), Sharon Banschbach (CCHMC), Eileen Beckman (CCHMC), Kelli Harmon (CCHMC), Patrick Lahni (CCHMC), and Thomas P. Shanley (CS Mott). Cohort 4 patients were enrolled in a study supported by the following grants from the National Institutes of Health: RO1GM064619, RC1HL100474, and R01GM099773. The REDCap software was used for data collection and was supported by the following grant: UL1-RR026314-01 NCRR/NIH.

Keywords

  • acute kidney injury
  • biomarkers
  • pediatrics
  • renal angina

ASJC Scopus subject areas

  • Nephrology

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