多器官功能衰竭综合征患者中自主神经信息流对预后的影响

来源 :世界核心医学期刊文摘(心脏病学分册) | 被引量 : 0次 | 上传用户:nvhuang123
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Background: Multiple organ dysfunction syndrome(MODS) is the sequential failure of several organ systems after a trigger event, like cardiogenic shock or decompensated heart failure. Mortality is high, up to 70% . Autonomic dysfunction(AD)may substantially contribute to the development of MODS. In cardiology, it has recently been shown that nonlinear parameters could predict mortality.Our study aimed at 1. characterising the complex characteristics of AD of critically ill MODS patients by the nonlinear parameters of autonomic information flow(AIF), 2. comparing AIF with autonomic function of healthy controls, and 3. characterising the accuracy of this parameter in predicting mortality in MODS. Methods: We enrolled 43 score-defined MODS patients who were consecutively admitted to a twelve-bed medical intensive care unit in a university centre into this prospective outcome study. Additionally, we assigned 50 healthy controls to the study. AIF was assessed as a complexity function of AD using 24-h ECG. Measures of AIF were introduced according to the standard HRV concept. The patients were followed up for 28-day mortality. Results: MODS causes a disorganisation of short term AIF in favour of an enhanced(rigid) long term AIF. Concerning prognosis increased short term AIF was associated with survival. Short term AIF discriminated between MODS survivors and nonsurvivors at the level of APACHE II score. Conclusions: This is the first study providing evidence that complex AD of MODS patients is specifically assessed by AIF time scales and that AIF has significant prognostic impact. Background: Multiple organ dysfunction syndrome (MODS) is the sequential failure of several organ systems after a trigger event, like cardiogenic shock or decompensated heart failure. Mortality is high, up to 70%. Autonomic dysfunction (AD) may substantially contribute to the development of the MODS. In cardiology, it has recently been shown that that nonlinear parameters could predict mortality. Our study aimed at 1. characterizing the complex characteristics of AD of critically ill MODS patients by the nonlinear parameters of autonomic information flow (AIF), 2. AIF with autonomic function of healthy controls, and 3. characterising the accuracy of this parameter in predicting mortality in MODS. Methods: We enrolled 43 score-defined MODS patients who were consecutively admitted to a twelve-bed medical intensive care unit in a university center into this prospective outcome study. Additionally, we assigned 50 healthy controls to the study. AIF was assessed as a complexity function of AD u Sing 24-h ECG. Measures of AIF were introduced according to the standard HRV concept. The patients were followed up for 28-day mortality. Results: MODS causes a disorganization of short term AIF in favor of an enhanced (rigid) long term AIF Short term AIF discriminated between MODS survivors and nonsurvivors at the level of APACHE II score. Conclusions: This is the first study providing evidence that complex AD of MODS patients specifically identifying by AIF time scales and that AIF has significant prognostic impact.
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