• Crit Care · Oct 2014

    Multi-scale symbolic entropy analysis provides prognostic prediction in patients receiving extracorporeal life support.

    • Yen-Hung Lin, Hui-Chun Huang, Yi-Chung Chang, Chen Lin, Men-Tzung Lo, Li-Yu Daisy Liu, Pi-Ru Tsai, Yih-Sharng Chen, Wen-Je Ko, Yi-Lwun Ho, Ming-Fong Chen, Chung-Kang Peng, and Timothy G Buchman.
    • Department of Internal Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan. austinr34@gmail.com.
    • Crit Care. 2014 Oct 24; 18 (5): 548548.

    IntroductionExtracorporeal life support (ECLS) can temporarily support cardiopulmonary function, and is occasionally used in resuscitation. Multi-scale entropy (MSE) derived from heart rate variability (HRV) is a powerful tool in outcome prediction of patients with cardiovascular diseases. Multi-scale symbolic entropy analysis (MSsE), a new method derived from MSE, mitigates the effect of arrhythmia on analysis. The objective is to evaluate the prognostic value of MSsE in patients receiving ECLS. The primary outcome is death or urgent transplantation during the index admission.MethodsFifty-seven patients receiving ECLS less than 24 hours and 23 control subjects were enrolled. Digital 24-hour Holter electrocardiograms were recorded and three MSsE parameters (slope 5, Area 6-20, Area 6-40) associated with the multiscale correlation and complexity of heart beat fluctuation were calculated.ResultsPatients receiving ECLS had significantly lower value of slope 5, area 6 to 20, and area 6 to 40 than control subjects. During the follow-up period, 29 patients met primary outcome. Age, slope 5, Area 6 to 20, Area 6 to 40, acute physiology and chronic health evaluation II score, multiple organ dysfunction score (MODS), logistic organ dysfunction score (LODS), and myocardial infarction history were significantly associated with primary outcome. Slope 5 showed the greatest discriminatory power. In a net reclassification improvement model, slope 5 significantly improved the predictive power of LODS; Area 6 to 20 and Area 6 to 40 significantly improved the predictive power in MODS. In an integrated discrimination improvement model, slope 5 added significantly to the prediction power of each clinical parameter. Area 6 to 20 and Area 6 to 40 significantly improved the predictive power in sequential organ failure assessment.ConclusionsMSsE provides additional prognostic information in patients receiving ECLS.

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