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Background/Aims: Acute kidney injury (AKI) following surgery is a major complication, but the prevalence and risk factors in the Asian population are unclear. Recently, a consensus definition of AKI (AKIN) was proposed. We studied a cohort of cardiac surgery patients and identified AKI by AKIN and associated risk factors. Methods: We retrospectively evaluated 1,056 consecutive patients undergoing cardiac surgery in Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China from January 1, 2004 to June 30, 2007. We recorded AKIN stage, clinical characteristics, perioperative variables and complications, as well as clinical outcomes. Univariate and multivariate regression as well as survival analysis was performed. Results: AKI occurred in 328 (31.1%) patients, stage 1 in 21.1%, stage 2 in 6.3% and stage 3 in 3.7%. Patients with AKI were older (65.8 vs. 53.5 years, p < 0.001), more often male (66.8 vs. 54.1%, p < 0.001), and had higher Charlson Comorbidity Index (CCI) (CCI >2: 22.6 vs. 7.8%, p < 0.001). In logistic regression, advanced age (OR 1.48 per decade, 95% CI 1.32–1.67), CCI >2 (OR 2.82, 95% CI 1.80–4.41), hypertension (OR 2.13, 95% CI 1.47–3.09), left ventricular ejection fraction (LVEF) 2O (OR 13.28, 95% CI 8.72–20.14) and postoperative use of ACEI/ARB (OR 1.90, 95% CI 1.27–2.85) were risk factors of AKI. Mortality rose progressively with increased AKIN stage (non-AKI 0.7%, stage 1 4.9%, stage 2 12.1% and stage 3 48.7%). In ROC analysis, AKIN classification was identified to be associated with in-hospital mortality with an AUC of 0.865 (95% CI 0.801–0.929, sensitivity 0.884, specificity 0.714, p < 0.001). Finally, in a Cox proportional hazards model, AKIN stage (HR 2.40, p < 0.001), re-exploration (HR 6.30, p = 0.002) and multiple organ dysfunction syndrome (MODS) (HR 4.42, p = 0.001) were associated risk factors for in-hospital mortality. Conclusion: We evaluated AKIN as a marker of AKI and mortality risk in a large, unselected Chinese cohort of incident patients undergoing cardiac surgery. AKI following cardiac surgery was diagnosed by AKIN criteria in around one third of the patients, and AKI may be associated with outcome. The value of preventative strategies to reduce AKI and their effect on in-hospital mortality should be studied.

Background/Aims: Acute kidney injury (AKI) is common following cardiac surgery and predicts a poor outcome. However, the early detection of AKI has proved elusive and most cases are diagnosed only following a significant rise in serum creatinine (SCr). We compared a panel of early biomarkers of AKI for the detection of AKI in patients undergoing heart surgery. This study included serum cystatin C (CyC) and urinary levels of neutrophil gelatinase-associated lipocalin (NGAL), interleukin-18 (IL-18), retinol-binding protein (RBP) and N-acetyl-β-D-glucosaminidase (NAG). Methods: We retrospectively identified 15 patients undergoing open cardiac surgery who developed AKI within 72 h postoperatively. For these, we identified 15 matched controls also having undergone surgery but without AKI. Serial serum and urine samples had prospectively been postoperatively obtained from all patients at 0, 2, 4, 6, 10, 24, 48 and 72 h after admission to the intensive care unit. AKI was defined as a >50% increase in SCr. CyC was measured by nephelometry, while NGAL, IL-18, and RBP were measured by ELISA and NAG was measured by spectrophotometry. The urinary biomarkers were normalized to urinary creatinine (UCr) concentration. Each marker was assessed at each time point for its predictive value using receiver operating characteristic curves to predict AKI. Results: Following the exclusion of 1 case due to a urinary tract infection, the final cohort consisted of 29 patients aged 62.9 ± 13.7 years with baseline SCr of 73.2 ± 11.9 µmol/l. While there were no differences in the demographics between cases and controls, the aortic clamp time was predictably higher in AKI cases than in controls (60.6 ± 13.9 vs. 43.0 ± 9.2 min, p < 0.05). Each biomarker differed significantly between cases and controls for at least one time point. The optimal area under the curve (AUC) was for CyC at 10 h (sensitivity 0.71, specificity 0.92, cutoff 1.31 mg/l), NGAL at 0 h (sensitivity 0.84, specificity 0.80, cutoff 49.15 µg/g UCr), IL-18 at 2 h (sensitivity 0.85, specificity 0.73, cutoff 285.65 ng/g UCr), RBP at 0 h (sensitivity 0.75, specificity 0.67, cutoff 2,934.65 µg/g UCr) and NAG at 4 h (sensitivity 0.86, specificity 0.67, cutoff 37.05 U/mg UCr). Using a combination of all 5 biomarkers analyzed at the optimal time point as above, we were able to obtain an AUC of 0.98 (0.93–1.02, p < 0.001) in this limited sample. Conclusion: The use of serum and urinary biomarkers for the prediction of AKI in patients undergoing cardiac surgery is highly dependent on the sampling time. Of the evaluated markers urinary NGAL had the best predictive profile. The previously unstudied marker of urinary RBP showed similar predictive power as more established markers. By combining all 5 studied biomarkers we were able to predict significantly more cases, suggesting that the use of more than one marker may be beneficial clinically.