We have located links that may give you full text access.
Journal Article
Research Support, Non-U.S. Gov't
The role of autonomic dysfunction in predicting 1-year mortality after liver transplantation.
Liver International : Official Journal of the International Association for the Study of the Liver 2017 August
BACKGROUND & AIMS: Model for end-stage liver disease (MELD) score has been extensively used to prioritize patients for liver transplantation and determine their prognosis, but with limited predictive value. Autonomic dysfunction may correlate with increased mortality after liver transplant. In this study, two autonomic biomarkers, complexity and deceleration capacity, were added to the predicting model for 1-year mortality after liver transplantation.
METHODS: In all, 30 patients with end-stage liver diseases awaiting liver transplantation were included. Complexity and deceleration capacity were calculated by multi-scale entropy and phase-rectified signal averaging, respectively. Different combinations of autonomic factors and MELD score were used to predict mortality rate of liver transplant after 1-year follow-up. Receiver-operating characteristics curve analysis was performed to determine clinical predictability. Area under the receiver-operating characteristics curve represents the overall accuracy.
RESULTS: The 1-year mortality rate was 16.7% (5/30). The overall accuracy of MELD score used for predicting mortality after liver transplantation was 0.752. By adding complexity and deceleration capacity into the predicting model, the accuracy increased to 0.912. Notably, the accuracy of the prediction using complexity and deceleration capacity alone was 0.912.
CONCLUSION: Complexity and deceleration capacity, which represent different dynamical properties of a human autonomic system, are critical factors for predicting mortality rate of liver transplantation. We recommend that these pre-operative autonomic factors may be helpful as critical adjuncts to predicting model of mortality rate in prioritizing organ allocation.
METHODS: In all, 30 patients with end-stage liver diseases awaiting liver transplantation were included. Complexity and deceleration capacity were calculated by multi-scale entropy and phase-rectified signal averaging, respectively. Different combinations of autonomic factors and MELD score were used to predict mortality rate of liver transplant after 1-year follow-up. Receiver-operating characteristics curve analysis was performed to determine clinical predictability. Area under the receiver-operating characteristics curve represents the overall accuracy.
RESULTS: The 1-year mortality rate was 16.7% (5/30). The overall accuracy of MELD score used for predicting mortality after liver transplantation was 0.752. By adding complexity and deceleration capacity into the predicting model, the accuracy increased to 0.912. Notably, the accuracy of the prediction using complexity and deceleration capacity alone was 0.912.
CONCLUSION: Complexity and deceleration capacity, which represent different dynamical properties of a human autonomic system, are critical factors for predicting mortality rate of liver transplantation. We recommend that these pre-operative autonomic factors may be helpful as critical adjuncts to predicting model of mortality rate in prioritizing organ allocation.
Full text links
Related Resources
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app