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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 5 Patients’ preoperative baseline information according to the occurrence of acute kidney injury after deceased-donor liver transplantation (n = 145)
| No AKI (n = 57) | AKI (n = 88) | P value | |
| Male gender, n (%) | 29 (50.8) | 49 (55.6) | 0.441 |
| Age (yr), mean (± SD) | 53.2 (± 13.56) | 56.2 (± 13.26) | 0.352 |
| BMI, mean (± SD) | 18.2(± 4.54) | 22.7 (± 4.92) | 0.065 |
| Biological MELD score, mean (± SD) | 21.67 (± 2.15) | 26.05 (± 3.05) | < 0.001 |
| Previous ascites, n (%) | 24 (42.1) | 52 (59.0) | 0.013 |
| Previous encephalopathy, n (%) | 18 (31.5) | 39 (44.3) | 0.025 |
| Previous upper digestive bleeding, n (%) | 21 (36.8) | 45 (51.1) | 0.018 |
| Preexisting KD, n (%) | 15 (26.3) | 60 (68.1) | < 0.001 |
| HCC, n (%) | 20 (35.0) | 37 (42.0) | 0.069 |
| Systemic arterial hypertension, n (%) | 28 (49.1) | 46 (52.2) | 0.083 |
| Diabetes mellitus, n (%) | 23 (40.3) | 43 (48.8) | 0.254 |
- 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