American Journal of Kidney Diseases
Volume 56, Issue 4 , Pages 623-631, October 2010

Validation of Clinical Scores Predicting Severe Acute Kidney Injury After Cardiac Surgery

  • Lars Englberger, MD

      Affiliations

    • Division of Cardiovascular Surgery, Mayo Clinic, Rochester, MN
    • Corresponding Author InformationAddress correspondence to Lars Englberger, MD, Division of Cardiovascular Surgery, Mayo Clinic, 200 First St SW, Rochester, MN 55905
  • ,
  • Rakesh M. Suri, MD, DPhil

      Affiliations

    • Division of Cardiovascular Surgery, Mayo Clinic, Rochester, MN
  • ,
  • Zhuo Li, MS

      Affiliations

    • Division of Biostatistics, Mayo Clinic, Rochester, MN
  • ,
  • Joseph A. Dearani, MD

      Affiliations

    • Division of Cardiovascular Surgery, Mayo Clinic, Rochester, MN
  • ,
  • Soon J. Park, MD

      Affiliations

    • Division of Cardiovascular Surgery, Mayo Clinic, Rochester, MN
  • ,
  • Thoralf M. Sundt III, MD

      Affiliations

    • Division of Cardiovascular Surgery, Mayo Clinic, Rochester, MN
  • ,
  • Hartzell V. Schaff, MD

      Affiliations

    • Division of Cardiovascular Surgery, Mayo Clinic, Rochester, MN

Received 12 December 2009; accepted 21 April 2010. published online 14 July 2010.

Background

Acute kidney injury (AKI) requiring renal replacement therapy (RRT) in patients undergoing cardiac surgery is associated strongly with adverse patient outcomes. Recently, 3 predictive risk models for RRT have been developed. The aims of our study are to validate the predictive scoring models for patients requiring postoperative RRT and test applicability to the broader spectrum of patients with postoperative severe AKI.

Study Design

Diagnostic test study.

Setting & Participants

12,096 patients undergoing cardiac surgery with cardiopulmonary bypass at Mayo Clinic, Rochester, MN, from 2000 through 2007.

Index Test

Cleveland Clinic score, Mehta score, and Simplified Renal Index (SRI) score.

Reference Test or Outcome

Incidence of postoperative RRT or composite outcome of severe AKI, defined as serum creatinine level >2.0 mg/dL, and a 2-fold increase compared with the preoperative baseline creatinine level or RRT.

Results

RRT was used in 254 (2.1%) patients, whereas severe AKI was present in 467 (3.9%). Discrimination for the prediction of RRT and severe AKI was good for all scoring models measured using areas under the receiver operating characteristic curve (AUROCs): 0.86 (95% CI, 0.84-0.88) for RRT and 0.81 (95% CI, 0.79-0.83) for severe AKI using the Cleveland score, 0.81 (95% CI, 0.78-0.86) and 0.76 (95% CI, 0.73-0.80) using the Mehta score, and 0.79 (95% CI, 0.77-0.82) and 0.75 (95% CI, 0.72-0.77) using the SRI score. The Cleveland score and Mehta score consistently showed significantly better discrimination compared with the SRI score (P < 0.001). Despite lower AUROCs for the prediction of severe AKI, the Cleveland score AUROC was still >0.80. The Mehta score is applicable in only a subgroup of patients.

Limitations

Single-center retrospective cohort study.

Conclusions

The Cleveland scoring system offers the best discriminative value to predict postoperative RRT and covers most patients undergoing cardiac surgery. It also can be used for prediction of the composite end point of severe AKI, which enables broader application to patients at risk of postoperative kidney dysfunction.

Index Words: Acute kidney injury, renal replacement therapy, cardiac surgery, risk prediction

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 Originally published online as doi:10.1053/j.ajkd.2010.04.017 on July 14, 2010.

PII: S0272-6386(10)00914-5

doi:10.1053/j.ajkd.2010.04.017

American Journal of Kidney Diseases
Volume 56, Issue 4 , Pages 623-631, October 2010