Applicability of the Cleveland clinic scoring system for the risk prediction of acute kidney injury after cardiac surgery in a South Asian cohort.

Acute kidney injury (AKI) after cardiac surgery is a frequent post-operative complication associated with an increased risk of mortality, morbidity and hospital costs. Preoperative risk scores such as the Cleveland Clinic Scoring Tool (CCST) have been validated in Western population group to identify patients at higher risk of AKI and may facilitate preventive strategies. However, the scoring tool has not been validated systematically in a South Asian cohort. We aimed to evaluate the applicability of the CCST in prediction of AKI after open cardiac surgery in a South-Indian tertiary care center. A retrospective study of all patients who underwent elective open cardiac surgery over a 4year period from Jan 2012 to Dec 2015 at a single centre were included and relevant details extracted from a comprehensive chart review. The primary outcome was AKI as defined by the Kidney Disease Improving Global Outcomes (KDIGO) criteria. Patients were risk stratified as per the CCST to assess for prediction of AKI into low risk (0-2), intermediate risk (3-5) and high risk (>6) groups. A total of 276 patients underwent open cardiac surgery with mean age of 51.5±13.06 yrs. This included 177 (64.1%) males and 99 females (35.8%). Overall incidence of AKI was 6.88%. Mean age, gender, BMI, preoperative serum creatinine, diabetes mellitus, chronic obstructive pulmonary disease, cardiopulmonary bypass time was similar in patients who developed AKI vs those who did not have AKI postoperatively. The mean CCST scores were 1.6 in those without AKI, 1.5 in stage 1, 3.0 in stage 2 and 3.4 in stage 3 AKI. Higher risk scores predicted greater risk of AKI. A total of 106 patients (38.4%) were on ACE/ARB, 119 patients (43.1%) received beta-blockers, 110 (39.8%) received diuretics while 144(52.1%) had received preoperative statins. Comparison of drug use between the two groups revealed that preoperative use of ACEI/ARB was associated with highest risk of AKI (p=0.006). Mortality rate was also high at 15.7% in those with AKI compared to 3.1% in non-AKI group (p=0.04). The modified CCST was valid in risk identification of patients with severe stage of AKI but did not have strong discrimination for early AKI stages. Preoperative statin use did not protect against AKI in our study, however preoperative ARB/ACEI use was significantly associated with occurrence of postoperative AKI.

Rao SN ，Shenoy M P ，Gopalakrishnan M ，Kiran B A ... -  《-》

Preoperative plasma growth-differentiation factor-15 for prediction of acute kidney injury in patients undergoing cardiac surgery.

Heringlake M ，Charitos EI ，Erber K ，Berggreen AE ，Heinze H ，Paarmann H ... -  《CRITICAL CARE》

Cardiac surgery-associated acute kidney injury: risk factors analysis and comparison of prediction models.

Cardiac surgery-associated acute kidney injury (AKI) is a well-known factor influencing patients' long-term morbidity and mortality. Several prediction models of AKI requiring dialysis (AKI-D) have been developed. Only a few direct comparisons of these models have been done. Recently, a new, more uniform and objective definition of AKI has been proposed [Kidney Disease: Improve Global Outcomes (KDIGO)-AKI]. The performance of these prediction models has not yet been tested. Preoperative demographic and clinical characteristics of 1056 consecutive adult patients undergoing cardiac surgery were collected retrospectively for the period 2012-2014. Multivariable logistic regression analysis was used to determine the independent predictors of AKI-D and the KDIGO-AKI stages. Risk scores of five prediction models were calculated using corresponding subgroups of patients. The discrimination of these models was calculated by the c-statistics (area under curve, AUC) and the calibration was evaluated for the model with the highest AUC by calibration plots. The incidence of AKI-D was 3.5% and for KDIGO-AKI 23% (17.3% for Stage 1, 2.1% for Stage 2 and 3.6% for Stage 3). Older age, atrial fibrillation, NYHA class III or IV heart failure, previous cardiac surgery, higher preoperative serum creatinine and endocarditis were independently associated with the development of AKI-D. For KDIGO-AKI, higher body mass index, older age, female gender, chronic obstructive pulmonary disease, previous cardiac surgery, atrial fibrillation, NYHA class III or IV heart failure, higher preoperative serum creatinine and the use of cardiopulmonary bypass were independent predictors. The model by Thakar et al. showed the best performance in the prediction of AKI-D (AUC 0.837; 95% CI = 0.810-0.862) and also in the prediction of KDIGO-AKI stage 1 and higher (AUC = 0.731; 95% CI = 0.639-0.761), KDIGO-AKI stage 2 and higher (AUC = 0.811; 95% CI = 0.783-0.838) and for KDIGO-AKI stage 3 (AUC = 0.842; 95% CI = 0.816-0.867). The performance of known prediction models for AKI-D was found reasonably well in the prediction of KDIGO-AKI, with the model by Thakar having the highest predictive value in the discrimination of patients with risk for all KDIGO-AKI stages.

Kristovic D ，Horvatic I ，Husedzinovic I ，Sutlic Z ，Rudez I ，Baric D ，Unic D ，Blazekovic R ，Crnogorac M ... -  《-》

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 ... -  《-》

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 ... -  《-》