• Annals of surgery · Sep 2020

    Predictors of Survival After Liver Transplantation in Patients With the Highest Acuity (MELD ≥40).

    • Michael D Evans, Jessica Diaz, Anna M Adamusiak, Timothy L Pruett, Varvara A Kirchner, Raja Kandaswamy, Vanessa R Humphreville, Thomas M Leventhal, Jeffrey O Grosland, David M Vock, Arthur J Matas, and Srinath Chinnakotla.
    • Clinical and Translational Science Institute, University of Minnesota Medical School, Minneapolis, Minnesota.
    • Ann. Surg. 2020 Sep 1; 272 (3): 458-466.

    ObjectiveTo identify factors that accurately predict 1-year survival for liver transplant recipients with a MELD score ≥40.BackgroundAlthough transplant is beneficial for patients with the highest acuity (MELD ≥40), mortality in this group is high. Predicting which patients are likely to survive for >1 year would be medically and economically helpful.MethodsThe Scientific Registry of Transplant Recipients database was reviewed to identify adult liver transplant recipients from 2002 through 2016 with MELD score ≥40 at transplant. The relationships between 44 recipient and donor factors and 1-year patient survival were examined using random survival forests methods. Variable importance measures were used to identify the factors with the strongest influence on survival, and partial dependence plots were used to determine the dependence of survival on the target variable while adjusting for all other variables.ResultsWe identified 5309 liver transplants that met our criteria. The overall 1-year survival of high-acuity patients improved from 69% in 2001 to 87% in 2016. The strongest predictors of death within 1 year of transplant were patient on mechanical ventilator before transplantation, prior liver transplant, older recipient age, older donor age, donation after cardiac death, and longer cold ischemia.ConclusionsLiver transplant outcomes continue to improve even for patients with high medical acuity. Applying ensemble learning methods to recipient and donor factors available before transplant can predict survival probabilities for future transplant cases. This information can be used to facilitate donor/recipient matching and to improve informed consent.Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.

      Pubmed     Full text   Copy Citation     Plaintext  

      Add institutional full text...

    Notes

     
    Knowledge, pearl, summary or comment to share?
    300 characters remaining
    help        
    You can also include formatting, links, images and footnotes in your notes
    • Simple formatting can be added to notes, such as *italics*, _underline_ or **bold**.
    • Superscript can be denoted by <sup>text</sup> and subscript <sub>text</sub>.
    • Numbered or bulleted lists can be created using either numbered lines 1. 2. 3., hyphens - or asterisks *.
    • Links can be included with: [my link to pubmed](http://pubmed.com)
    • Images can be included with: ![alt text](https://bestmedicaljournal.com/study_graph.jpg "Image Title Text")
    • For footnotes use [^1](This is a footnote.) inline.
    • Or use an inline reference [^1] to refer to a longer footnote elseweher in the document [^1]: This is a long footnote..

    hide…