ArticleMedicine2020
A nomogram for prediction of early allograft dysfunction in living donor liver transplantation.
Article in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Intraoperative Hemodynamic Monitoring and Prediction of Early Allograft Dysfunction Following Living Donor Liver Transplantation: A Systematic Review.Clinical transplantation · 2025Pooled it
- Uric Acid as a Predictor for Early Allograft Dysfunction after Living Donor Liver Transplantation: A Prospective Observational Study.Journal of clinical medicine · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Liver transplantation is the treatment of choice for end-stage liver diseases. However, early allograft dysfunction (EAD) is frequently encountered and associated with graft loss or mortality after transplantation. This study aimed to establish a predictive model of EAD after living donor liver transplantation. A total of 77 liver transplants were recruited to the study. Multivariate analysis was utilized to identify significant risk factors for EAD. A nomogram was constructed according to the contributions of the risk factors. The predictive values were determined by discrimination and calibration methods. A cohort of 30 patients was recruited to validate this predictive model. Four independent risk factors, including donor age, intraoperative blood loss, preoperative alanine aminotransferase (ALT), and reperfusion total bilirubin, were identified and used to build the nomogram. The c-statistics of the primary cohort and the validation group were 0.846 and 0.767, respectively. The calibration curves for the probability of EAD presented an acceptable agreement between the prediction by the nomogram and the actual incidence. In conclusion, the study developed a new nomogram for predicting the risk of EAD following living donor liver transplantation. This model may help clinicians to determine individual risk of EAD following living donor liver transplantation.
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