Development and validation of prediction model for early allograft dysfunction following liver transplantation based on systematic review and meta-analysis

BACKGROUND: Early allograft dysfunction (EAD) is a common complication following liver transplantation. Early identification of high-risk recipients is crucial to improving postoperative outcomes. METHODS: A predictive model for EAD was developed based on a meta-analysis of 22 cohort studies involving 17 582 liver transplantation (LT) donor-recipient pairs. Risk factors and their odds ratios were extracted, and only those statistically significant in the pooled analysis were included in the model. The validation cohort, consisting of both deceased donor liver transplantation and living donor liver transplantation recipients from China, used a manually set cutoff value of 22.5. Risk of bias was assessed using the Newcastle-Ottawa Scale. RESULTS: Significant risk factors included donor after circulatory death, donor age, donor body mass index, cholestatic liver disease, cold ischemia time, intraoperative fresh frozen plasma, and intraoperative red blood cell transfusion. The final model achieved a mean area under the receiver operating characteristic curve of 0.744 in external validation. CONCLUSION: This prediction model reliably estimates the risk of EAD in adult LT recipients and may serve as a practical clinical tool. Cholestatic liver disease may play a role in the development of EAD, and further studies are warranted to validate this association.