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The role of autonomic dysfunction in predicting 1‐year mortality after liver transplantation
Author(s) -
Chan KuangCheng,
Yeh JiaRong,
Sun WeiZen
Publication year - 2017
Publication title -
liver international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.873
H-Index - 110
eISSN - 1478-3231
pISSN - 1478-3223
DOI - 10.1111/liv.13364
Subject(s) - liver transplantation , medicine , receiver operating characteristic , predictability , liver disease , mortality rate , transplantation , cardiology , statistics , mathematics
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.