ArticleTransplantation2019
Prediction of Perioperative Mortality of Cadaveric Liver Transplant Recipients During Their Evaluations.
Article in Transplantation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Artificial intelligence and machine learning in transplantation surgery care pathway.World journal of transplantation · 2026Review
- A journey from marginality to routine and beyond: single center experience with DCD utilization for liver transplantation in Italy.Updates in surgery · 2026Article
- Impact of Pre-Transplant Frailty on Early Outcomes Following Liver Transplantation: A Propensity-Matched Multicenter Cohort Study.Journal of clinical medicine · 2026Article
- Tailoring Liver Transplant Decisions: How Donor-Recipient Age Matching Influences Outcomes.Clinical transplantation · 2026Article
- From prediction to practice: artificial intelligence as an enabling layer in liver transplant care - reflections on ILTS 2025.Frontiers in transplantation · 2026Article
- Gut microbiota reconstruction after liver transplantation and its association with early postoperative infections in patients with liver failure.Frontiers in cellular and infection microbiology · 2026Article
- Survival Outcomes of Liver Transplantation Amid Rising Recipient and Donor Risk Profiles.Clinical transplantation · 2025Article
- Liver Transplantation Using Allografts With Hepatic Artery Injury During Procurement: A Propensity Score-Matched Analysis of Outcomes.Clinical transplantation · 2025Article
- Sarcopenia and frailty: An in-depth analysis of the pathophysiology and effect on liver transplant candidates.World journal of hepatology · 2025Review
- Post-Liver Transplant Outcomes: A Comparative Study of 6 Predictive Models.Transplantation direct · 2024Article
- Use of machine learning models for the prognostication of liver transplantation: A systematic review.World journal of transplantation · 2024Article
- Artificial Intelligence in Liver Diseases: Recent Advances.Advances in therapy · 2024Review
- A narrative review: predicting liver transplant graft survival using artificial intelligence modeling.Frontiers in transplantation · 2024Review
- Guidelines to manage liver transplant recipients: time for consensus?Canadian journal of anaesthesia = Journal canadien d'anesthesie · 2023Article
- Diagnosing HFpEF and Predicting ESLD Liver Transplant Outcome Using HFA-PEFF Score.JACC. Asia · 2023Article
- A Novel Deep Learning Model as a Donor-Recipient Matching Tool to Predict Survival after Liver Transplantation.Journal of clinical medicine · 2022Article
- Development of a risk score model for 1-year graft loss after adult deceased donor liver transplantation in Japan based on a 20-year nationwide cohort.Annals of gastroenterological surgery · 2022Article
- Review
- Balancing Outcome vs. Urgency in Modern Liver Transplantation.Frontiers in surgery · 2022Article
- The liver transplant risk score prognosticates the outcomes of liver transplant recipients at listing.HPB : the official journal of the International Hepato Pancreato Biliary Association · 2021Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere are no instruments that can identify patients at an increased risk of poor outcomes after liver transplantation (LT) based only on their preoperative characteristics. The primary aim of this study was to develop such a scoring system. Secondary outcomes were to assess the discriminative performance of the predictive model for 90-day mortality, 1-year mortality, and 5-year patient survival.
methodsThe study population was represented by 30 458 adults who underwent LT in the United States between January 2002 and June 2013. Machine learning techniques identified recipient age, Model for End-Stage Liver Disease score, body mass index, diabetes, and dialysis before LT as the strongest predictors for 90-day postoperative mortality. A weighted scoring system (minimum of 0 to a maximum of 6 points) was subsequently developed.
resultsRecipients with 0, 1, 2, 3, 4, 5, and 6 points had an observed 90-day mortality of 6.0%, 8.7%, 10.4%, 11.9%, 15.7%, 16.0%, and 19.7%, respectively (P ≤ 0.001). One-year mortality was 9.8%, 13.4%, 15.8%, 17.2%, 23.0%, 25.2%, and 35.8% (P ≤ 0.001) and five-year survival was 78%, 73%, 72%, 71%, 65%, 59%, and 48%, respectively (P = 0.001). The mean 90-day mortality for the cohort was 9%. The area under the curve of the model was 0.952 for the discrimination of patients with 90-day mortality risk ≥10%.
conclusionsShort- and long-term outcomes of patients undergoing cadaveric LT can be predicted using a scoring system based on recipients' preoperative characteristics. This tool could assist clinicians and researchers in identifying patients at increased risks of postoperative death.
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