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

机译:健康人类受试者心周期变异性的常见测量指标的表征:对患者监测的影响。

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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.
机译:目的:心律变异性已被考虑用于自主神经功能的临床评估,确定出血或疾病状态的存在以及预测外伤的死亡率。但是,为了使心脏周期变异性在临床上有用,应解决许多重要的方法论问题,包括准确推导所需的最小R-R间隔(RRI)数以及这些指标的可重复性。方法:在18名静息仰卧位受试者(12 M / 6 F; 19-55岁)中记录ECG> 10分钟或= 10分钟。心周期变异性分析包括21个时间,频率和复杂性域指标。为了评估所需的最小RRI,通过有条理地截断数据集,从5分钟的ECG记录(到30 s)进行时域和频域度量,从800 RRI到100 RRI(对于复杂性度量)进行测量。通过计算所有受试者的变异范围和变异系数(%CV)评估受试者间变异性。通过计算每个受试者的%CV,使用两个独立的30 s或100个RRI ECG节段评估受试者内部的变异性。结果:六个时域和频域指标对30 s的数据具有鲁棒性,而五个复杂度指标对100 RRI的鲁棒性强。所有时域和频域指标(RRI除外)均表现出较高的受试者间可变性(CV>或= 30.0%),而11个复杂度指标中的五个指标显示出较低的受试者间可变性(CVs <或= 8.5%)。在评估心电图的30秒或100个RRI有效的指标的受试者内部变异性时,只有一个时域和四个复杂性指标的CV <10%。结论:可重复性高且需要很少RRI的指标有利于患者监测,因为需要较少的时间来评估生理状态并开始早期干预。根据我们对健康,处于静息状态的人类的分析,我们确定了一组精选的心周期变异性指标,在这两个标准方面表现良好。

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