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

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. Diagnostic test study. 12,096 patients undergoing cardiac surgery with cardiopulmonary bypass at Mayo Clinic, Rochester, MN, from 2000 through 2007. Cleveland Clinic score, Mehta score, and Simplified Renal Index (SRI) score. 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. 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. Single-center retrospective cohort study. 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 L ，Suri RM ，Li Z ，Dearani JA ，Park SJ ，Sundt TM 3rd ，Schaff HV ... -  《-》

A comparison of the systems for the identification of postoperative acute kidney injury in pediatric cardiac patients.

The pediatric-modified Risk, Injury, Failure and Loss, and End-Stage (pRIFLE) criteria and a different but conceptually similar system termed Acute Kidney Injury Network (AKIN) were created to standardize the definition of acute kidney injury (AKI) in children. Kidney Disease: Improving Global Outcomes (KDIGO) currently recommends a combination of AKIN and pRIFLE in AKI. This study aimed to compare the three classifications for predicting AKI in pediatric patients undergoing cardiac operations. We analyzed the prospectively collected data of 1,489 consecutive pediatric patients undergoing cardiac operations between January 2004 and December 2008. AKI presence and severity was assessed for each classification using the change in serum creatinine and estimated creatinine clearance levels calculated by the Schwartz equation. AKI was present in 285 (20%), 481 (34%), and 409 (29%) patients according to the AKIN, pRIFLE, and KDIGO systems, respectively. The KDIGO classification categorized 121 patients (8%) who were placed in the AKIN 0 category, whereas the pRIFLE system categorized 74 (5%) in KDIGO 0 and 200 (14%) in AKIN 0 stages as having an AKI. The overall mortality rate was 3.9%. The KDIGO stage III (odds ratio [OR], 18.8; 95% confidence interval [CI], 9.6 to 36.6, p < 0.001), the AKIN stage III (OR, 38.3; 95% CI, 20.6 to 70.9, p < 0.001), and pRIFLE failure group (OR, 13.6, 95% CI, 7 to 26.3; p < 0.001) were associated with increased mortality. The pRIFLE system was the most sensitive test in detecting AKI, and this was especially so in the infant age group and also in the early identification of AKI in low-risk patients. The AKIN system was more specific and detected mostly high-risk patients across all age groups. The KDIGO classification system fell between pRIFLE and AKIN in performance. All three had increasing severity of AKI associated with mortality.

Lex DJ ，Tóth R ，Cserép Z ，Alexander SI ，Breuer T ，Sápi E ，Szatmári A ，Székely E ，Gál J ，Székely A ... -  《-》

Validation of Four Prediction Scores for Cardiac Surgery-Associated Acute Kidney Injury in Chinese Patients.

Jiang W ，Xu J ，Shen B ，Wang C ，Teng J ，Ding X ... -  《-》

Comparison and clinical suitability of eight prediction models for cardiac surgery-related acute kidney injury.

Kiers HD ，van den Boogaard M ，Schoenmakers MC ，van der Hoeven JG ，van Swieten HA ，Heemskerk S ，Pickkers P ... -  《-》

Validation of renal-risk models for the prediction of non-renal replacement therapy cardiac surgery-associated acute kidney injury.

Cardiac surgery-associated acute kidney injury (AKI) is a serious complication of cardiac surgery, even when renal replacement therapy (RRT) is not required. The existing risk models for cardiac surgery associated AKI are designed to predict AKI requiring RRT (RRT-AKI). The aim of this study is to validate three risk models for the prediction of RRT-dependent and non-RRT AKI after cardiac surgery. Retrospective analysis on 7675 consecutive adult patients undergoing cardiac surgery with cardiopulmonary bypass. AKI was defined according to the Kidney Disease: Improving Global Outcomes (KDIGO) criteria for stage 1 and 2. RRT AKI and non-RRT AKI were defined according to the need for RRT. Three risk models were validated separately for RRT and non-RRT AKI: the Cleveland Risk Score, the Bedside Risk Score, and the Simplified Renal Index Scoring Scheme. Discrimination power was assessed with Receiver Operating Characteristics analysis and c-statistics. There were 502 (6.5%) non-RRT AKI events, 128 (1.7%) RRT-AKI events, and 7045 (91.8%) no-events. The three models performed well for predicting RRT-AKI (c-statistics 0.75-0.79) and poorly for predicting non-RRT AKI (c-statistics 0.54-0.59). The models had an excellent calibration for RRT-AKI but not for non-RRT AKI. Preoperative serum creatinine and estimated glomerular filtration rate were associated with RRT AKI but not with non-RRT AKI. Mortality was 12.2% in non-RRT AKI and 46.9% in RRT-AKI, significantly (P = 0.001) higher than in patients without AKI (1.3%). The existing risk models are inadequate for predicting non-RRT AKI following cardiac surgery, both in terms of discrimination and calibration.

Ranucci M ，Aloisio T ，Cazzaniga A ，Di Dedda U ，Gallazzi C ，Pistuddi V ... -  《-》