Acute Kidney Injury after Pediatric Cardiac Surgery: Risk Factors and Outcomes. Proposal for a Predictive Model

Objectives: To characterize the epidemiology and risk factors for acute kidney injury (AKI) after pediatric cardiac surgery in our center, to determine its association with poor short-term outcomes, and to develop a logistic regression model that will predict the risk of AKI for the study population. Methods: This single-center, retrospective study included consecutive pediatric patients with congenital heart disease who underwent cardiac surgery between January 2010 and December 2012. Exclusion criteria were a history of renal disease, dialysis or renal transplantation. Results: Of the 325 patients included, median age three years (1 day---18 years), AKI occurred in 40 (12.3%) on the first postoperative day. Overall mortality was 13 (4%), nine of whom were in the AKI group. AKI was significantly associated with length of intensive care unit stay, length of mechanical ventilation and in-hospital death (p<0.01). Patients’ age and postoperative serum creatinine, blood urea nitrogen and lactate levels were included in the logistic regression model as predictor variables. The model accurately predicted AKI in this population, with a maximum combined sensitivity of 82.1% and specificity of 75.4%. Conclusions: AKI is common and is associated with poor short-term outcomes in this setting. Younger age and higher postoperative serum creatinine, blood urea nitrogen and lactate levels were powerful predictors of renal injury in this population. The proposed model could be a useful tool for risk stratification of these patients.

Validation of Two US Risk Scores for Percutaneous Coronary Intervention in a Single-Center Portuguese Population of Patients with Acute Coronary Syndrome

INTRODUCTION: New scores have been developed and validated in the US for in-hospital mortality risk stratification in patients undergoing coronary angioplasty: the National Cardiovascular Data Registry (NCDR) risk score and the Mayo Clinic Risk Score (MCRS). We sought to validate these scores in a European population with acute coronary syndrome (ACS) and to compare their predictive accuracy with that of the GRACE risk score. METHODS: In a single-center ACS registry of patients undergoing coronary angioplasty, we used the area under the receiver operating characteristic curve (AUC), a graphical representation of observed vs. expected mortality, and net reclassification improvement (NRI)/integrated discrimination improvement (IDI) analysis to compare the scores. RESULTS: A total of 2148 consecutive patients were included, mean age 63 years (SD 13), 74% male and 71% with ST-segment elevation ACS. In-hospital mortality was 4.5%. The GRACE score showed the best AUC (0.94, 95% CI 0.91-0.96) compared with NCDR (0.87, 95% CI 0.83-0.91, p=0.0003) and MCRS (0.85, 95% CI 0.81-0.90, p=0.0003). In model calibration analysis, GRACE showed the best predictive power. With GRACE, patients were more often correctly classified than with MCRS (NRI 78.7, 95% CI 59.6-97.7; IDI 0.136, 95% CI 0.073-0.199) or NCDR (NRI 79.2, 95% CI 60.2-98.2; IDI 0.148, 95% CI 0.087-0.209). CONCLUSION: The NCDR and Mayo Clinic risk scores are useful for risk stratification of in-hospital mortality in a European population of patients with ACS undergoing coronary angioplasty. However, the GRACE score is still to be preferred.