الفهرس 
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Abstract
Heart rate variability” has become the conventionally accepted term to describe variations of both instantaneous heart rate and RR intervals.
Under resting conditions, the ECG of healthy individuals exhibits periodic variation in R-R intervals. This rhythmic phenomenon, known as respiratory sinus arrhythmia (RSA), flactuates with the phase of respiration - cardio-acceleration during inspiration, and cardio-decelaration during expiration.
RSA is predominantly mediated by respiratory gating of parasympathetic efferent activity to the heart: vagal efferent traffic to the sinus node occurs primarily in phase with expiration and is absent or attenuated durind inspiration.
Heart rate variability provides us with an indirect measure of heart health, as defined by the degree of balance in sympathetic & vagus nerve activity.
Measurement of HRV
1. Time domain:-
Originally, HRV was assessed manually from calculation of the mean R-R interval and its standard deviation measured on short-term (e.g., 5 minute) electrocardiograms.
The smaller the standard deviation in R-R intervals, the lower is the HRV. To date, over 26 different types of arithmetic manipulations of R-R intervals have been used in the literature to represent HRV.
Examples include: the standard deviations of the normal mean R-R interval obtained from successive 5-minute periods over 24-hour Holter recordings (called the SDANN index); the number of instances per hour in which two consecutive R-R intervals differ by more than 50 msec over 24-hours (called the pNN50 index); the root-mean square of the difference of successive R-R intervals (the rMSSD index); the difference between the shortest R-R interval during inspiration and the longest during expiration (called the MAX-MIN, or peak-valley quantification of HRV); and so on.
So far, experimental and simulation data appear to indicate that the various methods of expressing HRV are largely equivalent, and there is no evidence that any one method is superior to another, provided measurement windows are 5 minutes or longer.
2. Frequency domain:-
Measures of HRV provide information on the frequency distribution of the component of HRV using power spectral density analysis. Spectral analysis of heart rate is characterized by four main component: the high frequency (HF) component, (0.15 HZ- 40 HZ) measures the influence of the vagus nerve in modulating the sinoatrial node.
The low frequency (LF) component (.04 HZ- 0.155 HZ) provides an index of sympathetic effect on the heart, particularly when these are measured in normalized units. The very low frequency (VLF) component ( 0.003 HZ – 0.04 HZ) reflects the influence of several factors on the heart, including chemreceptors, thermoreceptors, the renin angiotensin system and other factors.
Almost all of the variability from a short term spectral analysis of HRV is captured in these three compnent.
An ultra low frequency ( ULF) component ( < 0.003 HZ) can also be observed in the HRV spectrum analysis of a longer sample.
Value of HRV
There are several prospective studies that have shown the HRV independently predicts and early detect prognosis in many cardiovascular diseases.
In cardiac arrhythmia and sudden cardiac death, measurement of HR variability is a useful research tool for documenting changes in neural regulation in relation to arrhythmia events in various clinical settings. The value of HR variability analyses, not only for identifying patients at risk of sudden cardiac death but also for describing changes in autonomic control mechanisms immediately prior to onset of malignant ventricular arrhythmias.
In Chronic Heart Failure patients, Depressed heart rate variability has independent prognostic value; spectral analysis identifies an increased risk for sudden death in these patients.
In idiopathic dilated cardiomyopathy, Decrease in heart rate variability is an independent predictor of arrhythmic events and sudden death, whether the mechanism of sudden death is ventricular tachyarrhythmia or not.
In Hypertension, HRV is reduced in men and women with systemic hypertension. Among normotensive men, lower HRV was associated with greater risk for developing hypertension. Estimation of LF using spectral analysis of ambulatory ECG recordings improves the prediction of risk of hypertension in men above that which can be obtained from measurements of baseline systolic and diastolic blood pressures, body mass index, and age. These findings are consistent with the hypothesis that autonomic dysregulation is present in the early stage of hypertension.
Patients with uncomplicated coronary disease and no previous myocardial infarction had reduced heart rate variability, mainly affecting the high and low frequencies, reflecting vagal tone, while SDNN and SDANN, which mainly involve the very low and ultra low frequencies and are important for prognosis, were not significantly affected.
Patients with acute Myocardial infarction, Decreased heart rate variability independently predicted poor prognosis after myocardial infarction. However, the cut-off points that should be used in clinical practice are still a matter for further investigation.
Depression is common in patients with coronary heart disease (CHD) and is a risk factor for cardiac morbidity and mortality in these patients. Most studies - both in patients with stable CHD and in patients with a recent acute coronary event- have found HRV to be lower in depressed patients than in their nondepressed counterparts.
In diabetic patients, decrease in autonomic function are present at early stages of metabolic impairment and diabetic metabolic impairment is associated with a progressive worsening of autonomic function. Diabetic subjects had lower HRV in the cross-sectional analysis and a greater mean annual decrease in HRV conditional on baseline HRV. After adjustment for baseline HRV, diabetic subjects clearly had a greater decrease in HRV, consistent with their increased risk for neuropathy.
In chronic severe mitral regurgitation, Ultralow-frequency heart rate variability, as measured by SDANN, correlates with right and left ventricular performance and predicts development of atrial fibrillation, mortality, and progression to valve surgery in patients with chronic severe mitral regurgitation.