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健康人体中心律变异性常见测量指标的特征:对患者监测的影响。

Characterization of common measures of heart period variability in healthy human subjects: implications for patient monitoring.

机构信息

Department of Health and Kinesiology, University of Texas at San Antonio, 78249, USA.

出版信息

J Clin Monit Comput. 2010 Feb;24(1):61-70. doi: 10.1007/s10877-009-9210-z. Epub 2009 Nov 22.

Abstract

OBJECTIVE

Heart period variability has been considered for clinical assessment of autonomic function, determining the presence of haemorrhage or disease states, and for predicting mortality from traumatic injury. However, for heart period variability to be clinically useful, a number of important methodological issues should be addressed, including the minimum number of R-R intervals (RRI) required for accurate derivation, and the reproducibility of these metrics.

METHODS

ECGs were recorded for > or =10 min in 18 resting, supine subjects (12 M/6 F; 19-55 years). Heart period variability analyses included 21 time, frequency and complexity domain metrics. For assessment of minimum RRIs required, measurements were made from ECG recordings of 5 min down to 30 s for time and frequency domain metrics, and from 800 RRIs down to 100 RRIs for complexity metrics, by methodical truncation of the data set. Inter-subject variability was assessed by calculating the range and co-efficient of variation (%CV) across all subjects. Two independent 30 s or 100 RRI ECG segments were used to assess intra-subject variability via calculation of %CV in each subject.

RESULTS

Six time and frequency domain metrics were robust down to 30 s of data, while five complexity metrics were robust down to 100 RRIs. All time and frequency domain metrics (except for RRI) exhibited high inter-subject variability (CVs > or = 30.0%), while five of eleven complexity metrics displayed low inter-subject variability (CVs < or = 8.5%). In the assessment of intra-subject variability in metrics valid with 30 s or 100 RRIs of ECG, only one time domain and four complexity metrics had CVs < 10%.

CONCLUSIONS

Metrics that are highly reproducible and require few RRIs are advantageous for patient monitoring as less time is required to assess physiological status and initiate early interventions. Based on our analyses from healthy, resting humans, we have identified a select cohort of heart period variability metrics that performed well in regards to these two criteria.

摘要

目的

心率变异性已被用于临床评估自主功能,确定是否存在出血或疾病状态,并预测创伤性损伤的死亡率。然而,为了使心率变异性在临床上有用,需要解决一些重要的方法学问题,包括准确推导所需的最小 R-R 间隔 (RRI),以及这些指标的可重复性。

方法

18 名静息仰卧受试者(12 名男性/6 名女性;19-55 岁)进行了>或=10 分钟的心电图记录。心率变异性分析包括 21 个时间、频率和复杂度域指标。为了评估所需的最小 RRI,通过有系统地截断数据集,对 5 分钟至 30 秒的时间和频率域指标以及 800 个 RRI 至 100 个 RRI 的复杂度指标进行测量。通过计算所有受试者的范围和变异系数(%CV)来评估受试者间的变异性。使用两个独立的 30 秒或 100 个 RRI 的 ECG 段通过计算每个受试者的 %CV 来评估受试者内变异性。

结果

六个时间和频率域指标在数据缩短至 30 秒时仍然稳健,而五个复杂度指标在缩短至 100 个 RRI 时仍然稳健。所有时间和频率域指标(除 RRI 外)均表现出较高的受试者间变异性(CVs>或=30.0%),而 11 个复杂度指标中的五个则显示出较低的受试者间变异性(CVs<或=8.5%)。在评估 30 秒或 100 个 RRI 的 ECG 中指标的受试者内变异性时,只有一个时间域和四个复杂度指标的 CV<10%。

结论

高度可重复且需要较少 RRI 的指标有利于患者监测,因为评估生理状态和早期干预所需的时间更少。基于我们对健康静息人群的分析,我们已经确定了一组选择的心率变异性指标,它们在这两个标准方面表现良好。

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