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©The Author(s) 2022.
World J Hepatol. Mar 27, 2022; 14(3): 570-582
Published online Mar 27, 2022. doi: 10.4254/wjh.v14.i3.570
Published online Mar 27, 2022. doi: 10.4254/wjh.v14.i3.570
Table 7 Intraoperative events in 145 deceased-donor liver transplantations according to the occurrence of postoperative acute kidney injury
| Without AKI (n = 57) | With AKI (n = 88) | P value | |
| IOAH (bleeding/PRS), n (%) | 14 (24.5) | 54 (61.3) | < 0.001 |
| MBT, n (%) | 5 (8.7) | 15 (17.0) | < 0.001 |
| Vasoactive drugs, n (%) | 38(66.6) | 48 (54.5) | 0.197 |
| Cryoprecipitate transfusion, n (%) | 10 (17.5) | 18 (20.4) | 0.169 |
| Piggy-back clamping, n (%) | 30 (52.6) | 48 (54.5) | 0.072 |
| SL (mmol/L) at the end of LT, mean (± SD) | 1.4 (± 0.3) | 2.8 (± 0.7) | < 0.001 |
| Lower serum fibrinogen (mg/dL), mean (± SD) | 242 (± 34) | 214 (± 24) | 0.090 |
- Citation: Bredt LC, Peres LAB, Risso M, Barros LCAL. Risk factors and prediction of acute kidney injury after liver transplantation: Logistic regression and artificial neural network approaches . World J Hepatol 2022; 14(3): 570-582
- URL: https://www.wjgnet.com/1948-5182/full/v14/i3/570.htm
- DOI: https://dx.doi.org/10.4254/wjh.v14.i3.570