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估计心室颤动的持续时间。

Estimating the duration of ventricular fibrillation.

作者信息

Brown C G, Dzwonczyk R, Werman H A, Hamlin R L

机构信息

Division of Emergency Medicine, Ohio State University, Columbus 43210.

出版信息

Ann Emerg Med. 1989 Nov;18(11):1181-5. doi: 10.1016/s0196-0644(89)80056-3.

Abstract

As the duration of time between the onset of ventricular fibrillation and the application of defibrillation (downtime) increases, the rate of successful resuscitation decreases. Results of recent animal studies suggest that the rate of successful resuscitation may be increased after a prolonged cardiorespiratory arrest when pharmacologic therapy is instituted before defibrillation. An accurate estimation of downtime could be critical in selecting the most appropriate therapeutic intervention. The purpose of our study was to determine whether changes in the frequency or amplitude of the ventricular fibrillation ECG signal during cardiac arrest could be used to estimate downtime. We characterized the dynamics of both total power and frequency distribution of the power in the ECG during ventricular fibrillation in 11 swine to determine whether enough information existed in either parameter to estimate downtime. The median frequency of the power spectrum was used to track power distribution. Both parameters followed a dynamic, repeatable pattern. However, median frequency showed less intersubject variability than did total power. A mathematical model of median frequency was developed and used with data obtained from ten additional swine to estimate downtime. The model estimated downtime to within 1.3 minutes of actual downtime between one and ten minutes of ventricular fibrillation. Our study has identified a new, potentially useful parameter for studying various management strategies in ventricular fibrillation as a function of downtime.

摘要

随着心室颤动发作与除颤应用之间的时间间隔(停机时间)增加,成功复苏的几率会降低。近期动物研究结果表明,在长时间心肺骤停后,若在除颤前进行药物治疗,成功复苏的几率可能会提高。准确估算停机时间对于选择最合适的治疗干预措施可能至关重要。我们研究的目的是确定心脏骤停期间心室颤动心电图信号的频率或幅度变化是否可用于估算停机时间。我们对11头猪心室颤动期间心电图的总功率和功率频率分布动态进行了表征,以确定任一参数中是否存在足够信息来估算停机时间。功率谱的中位数频率用于追踪功率分布。两个参数均呈现出动态、可重复的模式。然而,中位数频率的个体间变异性比总功率小。我们开发了一个中位数频率的数学模型,并将其与从另外10头猪获得的数据一起用于估算停机时间。该模型在心室颤动1至10分钟时将停机时间估算在实际停机时间的1.3分钟范围内。我们的研究确定了一个新的、可能有用的参数,可用于研究作为停机时间函数的心室颤动的各种管理策略。

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