In this study, we compared two standardized criteria for the diagnosis of AKI; the KDIGO and AKIN criteria in the prediction of DGF development and also other clinical outcomes in KTRs. When they were applied for the diagnosis of AKI in DDs, the KDIGO criteria had a superior predictive value for the development of DGF in corresponding KTRs in comparison with the AKIN criteria. However, this higher accuracy for DGF did not result in a better prediction of long-term allograft outcomes.
First, we compared the KDIGO criteria with the AKIN criteria in terms of the detection rate of AKI in DDs, and a significant discrepancy was found between the two criteria. According to the KDIGO criteria, additional 39 DDs were diagnosed as having AKI, which resulted in a higher incidence of AKI (54.6% (106/205)) in comparison with that using the AKIN criteria (35.6% (73/205)). In addition, a considerable discrepancy was detected in the distribution of AKI stage between the two criteria. AKI diagnosis by KDIGO showed a higher stage distribution compared to that of the AKI stage according to the AKIN criteria (P?=?0.001). Indeed, in non-AKI patients according to the AKIN criteria, nearly 30% was defined as AKI by the KDIGO criteria, and even more, 5% was defined as stage 3 AKI (Fig. 2).
These discrepancies between the KDIGO and AKIN criteria in the diagnosis of AKI in DDs may have resulted from the differences in the details between two criteria. Although both criteria are commonly based on the change in serum creatinine and urine output, some differences exist in detailed components between the two criteria. For example, in the KDIGO criteria, AKI was defined as an increase in SCR to ?1.5 times baseline, which is known or presumed to have occurred within the prior 7 days. In contrast, increase in SCR by ?0.3 mg/dl within the 48 h time constraint was necessary for the diagnosis of AKI by the AKIN criteria [16, 22]. Therefore, use of the KDIGO criteria can detect AKI in more patients in comparison with the AKIN criteria as shown in a previous study performed in AKI populations [17].
Our next aim was to investigate whether a different detection rate of AKI by the KDIGO criteria can result in a difference in the prediction of DGF in corresponding KTRs. The incidence of DGF showed a significant increase in the AKI group compared to the non-AKI group, irrespective of the criteria applied in DDs (Fig. 3a, b), which is fully consistent with many previous studies [3, 5–7, 23, 24]. However, we mainly were interested in the 61 KTRs who were diagnosed as having AKI by the KDIGO criteria but not by the AKIN criteria (the AKI by KDIGO only group), because the result in this group may differentiate the predictive value for DGF between the KDIGO and AKIN criteria. Interestingly, the incidence of DGF in the AKI by KDIGO only group was very similar to that in the AKI by both criteria group and it was significantly higher than that in the non-AKI by both criteria group. This suggests that the kidney functions of patients in the AKI by KDIGO only group were more alike to those of the AKI by both criteria group rather than the non-AKI by both criteria group.
In addition, in the multivariate analysis using logistic regression analysis, detection of AKI either by KDIGO or AKIN in DDs was independently associated with DGF in corresponding KTRs. In further analysis using ROC analysis, both criteria significantly predicted DGF in corresponding KTRs. However, area under the curve in ROC analysis was significantly larger in the KDIGO criteria than in the AKIN criteria. This is consistent with the above findings, which showed that the incidence of DGF in the AKI by KDIGO only group was more alike to that of the AKI by both criteria group rather than that of the non-AKI by both criteria group. All our results suggest that the KDIGO criteria may be better in discriminating kidneys which will result in DGF in comparison with the AKIN criteria in DDs.
Third, allograft function showed a worse value during post-transplant 6 months in the AKI group in comparison with the non-AKI group in both analyses using either the KDIGO or AKIN criteria. However, this difference disappeared at one year from KT, similar to that in our previous report [5]. In three group analysis, allograft function was inferior in the AKI by both criteria group in comparison with the non-AKI by both criteria group, but this difference also disappeared at 1 year from KT (Fig. 4c). Interestingly, the AKI by KDIGO only group showed a very similar pattern of allograft function to that in the AKI by both criteria group, which is consistent with the result about DGF development. On comparison of the long-term allograft survival rate, no significant difference was detected between the two groups or among the three groups, irrespective of the applied AKI criteria as for the comparison of the 1 year allograft function in each group. Finally, diagnosis of AKI either by AKIN or KDIGO in DDs was not a significant risk factor for allograft failure in a Cox regression hazard model.
Meanwhile, the development of DGF was independently associated with allograft failure along with acute rejection and recipient BMI as in many previous studies [25–27]. This suggests that even though a high incidence of DGF in KT from an AKI donor did not result in an adverse allograft outcome, DGF itself is still an important risk factor. The exact reason for this is unclear, but it may be because the development of DGF in the non-AKI group is associated with worse allograft outcomes. The development of DGF in non-AKI kidneys from DDs is frequently due to acute rejection not due to acute tubular necrosis, which may explain the poor allograft outcome in those cases [6, 28]. However, further investigation is required to clarify this issue.
Lastly, we investigated whether the severity of AKI in DDs has a significant impact on the clinical outcomes of corresponding KTRs. As expected, stage 3 AKI in DDs resulted in the highest incidence of DGF and a lower allograft function during post-transplant 6 months in corresponding KTRs compared to that in stage 1 or 2 AKI in DDs in both analyses using the KDIGO or AKIN criteria. However, these differences showed a decreasing pattern in allograft function at one year from KT, and long term allograft survival rate did not show significant differences in comparison across the AKI stage both by the KDIGO or AKIN criteria. This suggests that not only AKI diagnosis but also the severity of AKI in DDs may not have a significant impact on long-term allograft outcomes in corresponding KTRs.
Our study has some limitations. Firstly, not all recipients corresponding to the donors included in this study were included in this analysis because some organs were transferred to another institution according to the organ distribution rule in Korea, which could have induced a bias during analysis. Secondly, this study was performed as a retrospective chart review. A prospective multicenter study conducted in a larger patient group is required to overcome the above issues.