Validation of clinical scores predicting severe acute kidney injury after cardiac surgery.
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.


METHODS
Diagnostic test study.


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


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


METHODS
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.


CONCLUSIONS
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.
Englberger
Lars
L
Division of Cardiovascular Surgery, Mayo Clinic, Rochester, MN 55905, USA. lars.englberger@insel.ch
Suri
Rakesh M
RM
Li
Zhuo
Z
Dearani
Joseph A
JA
Park
Soon J
SJ
Sundt
Thoralf M
TM
Schaff
Hartzell V
HV
D058186:Acute Kidney Injury / Q000175:diagnosis* / Q000209:etiology / Q000628:therapy; D000328:Adult; D000368:Aged; D006348:Cardiac Surgical Procedures / Q000009:adverse effects* / Q000379:methods; D002315:Cardiopulmonary Bypass / Q000009:adverse effects* / Q000379:methods; D015331:Cohort Studies; D016001:Confidence Intervals; D001026:Coronary Artery Bypass / Q000009:adverse effects / Q000379:methods; D003404:Creatinine / Q000097:blood*; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D007677:Kidney Function Tests; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011183:Postoperative Complications / Q000175:diagnosis; D011237:Predictive Value of Tests; D012372:ROC Curve; D006435:Renal Dialysis / Q000379:methods; D012189:Retrospective Studies; D018570:Risk Assessment; D012720:Severity of Illness Index
D003404:Creatinine