Heart Rate Variability to Assess Autonomic Function Phyllis K. Stein, Ph.D. Research Assistant Professor of Medicine and Director, HRV Lab Washington University School of Medicine, St. Louis, MO

Understanding ECGs and How the Heart Works PART I Understanding ECGs and How the Heart Works

Overview of Blood Circulation Red –oxygenated blood Blue – deoxygenated blood Pulmonary system –where blood flows through the arteries and veins of the lungs to pick up oxygen Arterial system - distributes blood - Muscular - high pressure - aorta acts is an auxiliary pump Capillaries - exchange of nutrients and gases Venous system - blood reservoir, low pressure Heart - 4 chambers, two pumps; pulmonary and systemic

The Heartbeat Valves Valves All four chambers relaxed-blood passively entering all chambers - diastole. Contraction of the left atrium and right atrium at the same time (atrial contraction or “atrial kick”) causes blood from the atria to enter the ventricles (Adding to the blood from passive filling. Maximum amount of blood ventricles will have) – atrial systole. Pressure in the ventricles greater than in the atria, which closes the valves so no blood can back flow into the atriums. Ventricles contract which opens the outflow valves so the blood can go to either the pulmonary or systemic system – ventricular systole. Pressure in ventricles decreases, valves close to protect against back flow. Valves

Electrical Pathways SA node - pacemaker of the heart. - “fires” an action potential 60 – 80 times a minute spontaneously. - firing rate = heart rate (HR) and changes with needs of the body. - regulated by the autonomic nervous system. - initiates atrial contraction via the posterior internodal tract, middle internodal tract, and Bachmann’s Bundle. - “activates” AV node AV node - delays SA signal before passing to the ventricles. - initiates ventriclular contraction via conduction pathways. - abnormal pathways result in abnormal-looking electrocardiogram

Action Potential Basics Resting voltage Resting voltage 1 2 3 4 5 Important ions - can be positive or negative (small circles) - Sodium (Na+) - Potassium (K+) - Calcium (Ca++) - Chloride (Cl-) Cell membranes - allows passage of ions into and out of cell (gray circle) - regulates ion passage through different type of channels Membrane potential - measured by looking at the inner cell membrane voltage compared with outside voltage Resting (1) - the cell has more negative ions inside than outside - membrane potential is negative Depolarization (2) - channels open to allow positive ions flow into cell by electrical attraction and diffusion - cell membrane potential rises Peak (3) - channels close - the cell now has more positive ions - cell membrane potential is positive Repolarization (4) - different set of channels open to allow positive ions to flow out of cell by electrical attraction and diffusion - cell membrane potential falls Resting (5) - cell membrane potential returns to resting

Cardiac Action Potential Action potentials (AP) in the heart - an electrocardiogram (ECG) is the AVERAGE of all the action potentials - when group of cells depolarizes: chain reaction, rest of heart depolarizes, unless cells have not yet recovered from last depolarization (refractory period: limit to peak heart rate) - normal AP starts at AP node 0) Na+ channels open; K+ channels close Na+ channels close; Ca++ channels open Ca++ close; some K+ channels open K+ channels open And many, many other channels.

Components of the ECG ECG = electrocardiogram - electrodes placed on the body record electrical signals from the heart. Depolarization – positively increases in voltage from resting voltage. Repolarization – decrease in voltage back to the resting voltage.

ECG Measurements

Autonomic Nervous System Effects on the Heart Autonomic nervous system is the “automatic” part of the central nervous system. -regulates all body functions including heart rate and blood pressure. Two arms of the autonomic nervous system. -Sympathetic=“fight or flight” responses -Parasympathetic=relaxation and recovery -Parasympathetic travels on vagus nerve, so parasympathetic also called vagal. Parasympathetic Nervous System (PNS), inhibits cardiac action potentials Sympathetic Nervous System (SNS), stimulates cardiac action potentials

Single Channel Normal ECG QRS complex ECG recordings can have one view (single channel) or many. t wave p wave

A Normal 12 Lead ECG 12 lead ECG - use 10 electrodes - allows 12 different views, from different directions, of the heart’s electrical activity - standard clinical ECG

Atrial Premature Contraction (APC) Early QRS APC = Supraventricular ectopy (SVE) - is early - p-wave usually abnormal - QRS is usually abnormal - cardiac output reduced because less time to fill Abnormal p wave

Atrial Bigeminy Atrial Bigeminy – each beat is followed by an atrial premature beat

Atrial Fibrillation (AF) - Atria contracting at random; P wave all over the place - SA node is not controlling HR - Usually fast, totally irregular rhythm but normal QRS - can lead to stroke; patients need blood thinners - 25% cardiac output because no “atrial kick”

Normal ECG with Ventricular Premature Contractions (VPCs) - VPCs are also called ventricular beats and are not under the control of the SA node - abnormal shape because order of depolarization in heart is abnormal - no p-wave; depolarization starts in the ventricle - low cardiac output because heart muscle does not contract in the correct sequence - can occur in healthy people

Right Bundle Block (RBB) RBB - has a wide QRS complex LBB (Left Bundle Block) - also has a wide QRS complex Wide QRS peak

Dangerously Abnormal ECGS

Ventricular Tachycardia (VT) - two VPCs in a row = “a couplet” - three or more VPCs in a row is called non-sustained ventricular tachycardia (NSVT). - A series of abnormal beats= a “run.” - if the VPCs continue it is called ventricular tachycardia (VT) - VT often very fast (>120 bpm) - In VT heart contraction is totally abnormal and little blood is pumped. - Can “degenerate” to Ventricular Fibrillation

Ventricular Fibrillation (VF) - the heart beats in a nearly random way. - usually fatal (sudden cardiac death). VT and VF - Defibrillators are designed to identify when happening and shock the heart back into a normal rhythm.

Keywords Atrium Ventricle SA node AV node ECG Components P wave QRS complex T wave Sympathetic Nervous System Parasympathetic Nervous System Vagal APC or SVE Bigeminy VPCs VT VF

Holter and Other Continuous ECG Data PART II Holter and Other Continuous ECG Data

Heart Rate Variability (HRV) Lab Analyzes Data from Continuous Electronically-Stored ECGs Cassette Tape Holter Monitor 2 or 3 channels of Simultaneous ECG signals Flash Card Electronic ECGs are obtained using ambulatory monitors called “Holter Recorders” ECGs can be stored on cassette tapes or flash cards Patient wearing a Holter device.

Continuous ECG Data Also Obtained from Overnight Sleep Studies Sleep studies have many channels of data including ECG Data stored on a hard disk and file exported to a CD One channel is ECG

Analysis of Stored ECG Signals Continuous ECG signal is digitized and loaded on the Holter scanner Holter scanner is a computer with special commercial software that can process ECGs Many other computer algorithms exist that can display and measure things from ECGs

The Job of the Holter Scanner Read and display the stored ECG Identify the peak of each beat Accurately label each beat as normal, APC or VPC Measure the time between the peaks of each beat Create a report describing the recording Export the results as a “beat file”

The QRS File MARS scanner exports “QRS” files. QRS file is a list of every detected event on the tape, with the time after the next event. Events can be normal beats, APCs, VPCs or just noise. QRS file is in binary format, so we need to convert it to something we can read. Binary format – uses ‘0’ and ‘1’ to store the data

Digitized ECG Format .MIT Format .RAW file .NAT file Binary format Consists of a .HDR file and .SIG file .RAW file Does not contain any header info Can be reloaded onto MARS like tape .NAT file Actual file on MARS Can be reloaded into MARS “slot” and restore all original data and analyses Filenames are the same as the ID of the subject .HDR file - header file - text file similar to .MIB header (example on next slides) .SIG file – contains the ECG signal

The .MIB file QRS file from the MARS scanners are saved to “HRV.” “HRV” is the name of the Sun computer that does all HRV calculations. QRS file is converted to MIB file and stored on “HRV.” .MIB= machine-independent beatfile Heart rate variability is calculated from the .MIB file

Example of the Beginning of a .MIB File # 13:46:03.726 Study code=8050MJP OK,1 Record number code=8050MJP1 Start time=13:41:00 First beat=13:46:03.726 Start date=02-May-03 Samples per second=128 Marquette conversion date=Thu Jun 10 13:19:17 2004 Marquette hardware revision=508 833 523 4.00 0.25 End header Q0.000000000 Q687.500000000 Q617.187500000 Q656.250000000 Q648.437500000 Q625.000000000 header Header - beginning of the file - contains information about the recording Q data - Q means normal beat - V means VPC (not shown) - A means APC (not shown) - Z means noise (not shown) - number is time from the last beat in milliseconds

Files Generated from the .MIB File All heart rate variability calculations are made and exported to an EXCEL spreadsheet with one row per subject Heart rate tachograms -beat-by-beat plots of heart rate vs. time HRV power spectral plots - graphical representation of HRV HRV Poincaré plots - graphical representations of HR patterns

Part of an HRV Spreadsheet ID avnnT avnnD avnnN pnn50T pnn50D pnn50N 1A36181 1010.034 988.613 1043.868 5.559 6.188 4.36 1A49681 999.295 988.617 1016.784 1.295 2.018 0.586 1A75451 846.611 849.501 836.082 0.482 0.4 0.572 1B74381 810.154 813.078 780.171 9.725 10.264 4.494 1B74391 725.69 710.065 777.362 6.451 5.553 12.008 1B74401 866.626 821.987 930.132 15.402 8.237 35.138 1B76181 674.383 703.628 646.714 0.933 1.38 0.398 1B76191 817.108 826.079 789.545 2.274 3.173 1.034

Heart Rate Tachogram x-axis = time in minutes (0-10 minutes) 0-100 bpm “x-axis” x-axis = time in minutes (0-10 minutes) y-axis for each 10-min plot is H (0-100 bpm in 5 cm) “x-axis” is mean HR for that 10-min segment

Hourly HRV Power Spectral Plots (much reduced in size)

Hourly Poincaré plots (much reduced in size)

Keywords Holter Scanner Beat file QRS File Binary .MIB Header Recognize: Tachograms Power spectral plots Poincaré plots

Part III HRV in Detail

Background (HRV) Decreased heart rate variability Abnormal heart rate variability Identify patients with autonomic abnormalities who are at increased risk of arrhythmic events. Arrhythmic Events = VT or VF HRV = Heart Rate Variability

Simplified Model of Cardiovascular Autonomic Control Renin angiotensin system Heart Rate Cardiac output Blood pressure Parasympathetic Nervous system Sympathetic The feedback loops are responsible for determining the actual heart rate.

How HRV Reflects the Effect of the Autonomic Nervous System of the Heart

HR Fluctuations Fluctuations in HR (HRV) are mediated by sympathetic (SNS) and parasympathetic (PNS) inputs to the SA node. Rapid fluctuations in HR usually reflect PNS control only (respiratory sinus arrhythmia). Slower fluctuations in HR reflect combined SNS and PNS + other influences. Autonomic nervous system - sympathetic nervous system (SNS) and parasympathetic nervous system (PNS) - responsible for bringing about changes in the body in response to external changes through mostly involuntary actions. SNS - “fight or flight” response by releasing epinephrine (also known as adrenaline). PNS - returns the body to normal by releasing acetylcholine. Respiratory Sinus Arrythmia (RSA) - a natural cycle of speeding up and slowing down of heart rate caused by breathing

Rapid Fluctuations in HR Are Vagally Mediated “Rapid” fluctuations in HR are at >10 cycles/min (respiratory frequencies) Vagal effect on HR mediated by acetylcholine binding which has an immediate effect on SA node. If HR patterns are normal, rapid fluctuations in HR are vagally modulated Vagus nerve - one of the 12 pairs of nerves originating in the brain - can directly stimulate the sinoatrial (SA) node. The release of acetycholine onto the SA node results in a change in channel properties, which then decreases the inward current so the action potential cycle last longer (slower HR) Cycles/min – think of a sinusoidal wave; how many complete “cycles” (such as peak to peak) are occurring per minute

Acetylcholine Binding Acetylcholine – directly binds to the receptor in the SA node which causes an immediate change in heart rate. The Acetylcholine Neurotransmitter binds to a receptor on a muscle once released from a neuron.

Slower Fluctuations in HR Reflect Both SNS and Vagal Influences “Slower” fluctuations in HR are <10 cycles per min. SNS effect on HR is mediated by norepinephrine release which has a delayed effect on SA node Both SNS and vagal nerve traffic fluctuate at >10 cycles/min, but the time constant for changes in SNS tone to affect HR is too long to affect HR at normal breathing frequencies.

Sympathetic activation takes too long to affect RSA NE – norepinephrine RSA - respiratory sinus arrhythmia There are many more steps here compared with acetylcholine receptor binding. NE takes longer to increase heart rate than acetylcholine does to decrease heart rate. *Don’t need to know details, just know this takes longer! NE blinds to the beta-receptor (Alpha subunit of G-protein). After binding, G protein links to second messenger (adenyl cyclase) which converts ATP to cAMP. cAMP activates protein kinase A which breaks ATP to ADP+phosphate which phosphorylates the pacemaker channels and increases HR

Assessment of HRV Approach 1 Physiologist’s Paradigm HR data collected over short period of time (~5-20 min), with or without interventions, under carefully controlled laboratory conditions. Physiologist - biologist that specializes in the study of the processes that occur within living organisms. HR = heart rate

Assessment of HRV Approach 2 Clinician’s/Epidemiologists’s Paradigm Ambulatory Holter Recordings usually collected over 24-hours or less, usually on outpatients. Clinician - directly involved with the care and treatment of patients. Epidemiologist - studies the presence of disease in populations. Approaches 1 and 2 can be combined

HRV Perspectives Longer-term HRV-quantifies changes in HR over periods of >5min. Intermediate-term HRV-quantifies changes in HR over periods of <5 min. Short-term HRV-quantifies changes in HR from one beat to the next Ratio HRV-quantifies relationship between two HRV indices.

Sources of Heart Rate Variability Extrinsic Activity - Sleep Apnea Mental Stress - Smoking Physical Stress Intrinsic Periodic Rhythms Respiratory sinus arrhythmia Baroreceptor reflex regulation Thermoregulation Neuroendocrine secretion Circadian rhythms Other, unknown rhythms Sleep apnea – brief breathing interruptions during sleep. Baroreceptor reflex regulation – short-term blood pressure regulation Theremoregulation – body temperature regulation Circadian rhythms – biological processes that take around 24 hours to complete

Time Domain and Geometric Analyses Ways to Quantify HRV Approach 1: How much variability is there? Time Domain and Geometric Analyses Approach 2: What are the underlying rhythms? What physiologic process do they represent? How much power does each underlying rhythm have? Frequency Domain Analysis Approach 3: How much complexity or self-similarity is there? Non-Linear Analyses

Time Domain HRV Longer-term HRV SDNN-Standard deviation of N-N intervals in msec (Total HRV) SDANN-Standard deviation of mean values of N-Ns for each 5 minute interval in msec (Reflects circadian, neuroendocrine and other rhythms + sustained activity) N-N - normal-to-normal To calculate a standard deviation of a series of numbers: Find the average Calculate the differences between each number and the average Square each difference (so they don’t cancel out) Sum Divide by number of datapoints Take square root

Time Domain HRV Intermediate-term HRV SDNNIDX-Average of standard deviations of N-Ns for each 5 min interval in ms (Combined SNS and PNS HRV) Coefficient of variance (CV)- SDNNIDX/AVNN. Heart rate normalized SDNNIDX.

Reflect PNS influence on HR Time Domain HRV Short-term HRV rMSSD-Root mean square of successive differences of N-N intervals in ms pNN50-Percent of successive N-N differences >50 ms Calculated from differences between successive N-N intervals Reflect PNS influence on HR Root mean square – average change from one beat to the next

Geometric HRV HRV Index-Measure of longer-term HRV Wider triangle – more HRV Narrower triangle – less HRV HRV Index-Measure of longer-term HRV From Farrell et al, J am Coll Cardiol 1991;18:687-97

Examples of Normal and Abnormal Geometric HRV

Frequency Domain HRV Based on autoregressive techniques or fast Fourier transform (FFT). Partitions the total variance in heart rate into underlying rhythms that occur at different frequencies. These frequencies can be associated with different intrinsic, autonomically-modulated periodic rhythms. FFT – transforms data from the time domain into the frequency domain (next slide shows an example)

What are the Underlying Rhythms? One rhythm 5 seconds/cycle or 12 times/min In the time domain, the plot can be drawn using one sinusoidal wave with a frequency of 0.2 Hz. Therefore, in the frequency domain, there is a peak at 0.2 Hz. 5 seconds/cycle= 1/5 cycle/second 1/5 cycle/second= 0.2 Hz

What are the Underlying Rhythms? Three Different Rhythms High Frequency = 0.25 Hz (15 cycles/min Low Frequency = 0.1 Hz (6 cycles/min) Very Low Frequency = 0.016 Hz (1 cycle/min)

Ground Rules for Measuring Frequency Domain HRV Only normal-to-normal (NN) intervals included At least one normal beat before and one normal beat after each ectopic beat is excluded Cannot reliably compute HRV with >20% ectopic beats With the exception of ULF, HRV in a 24-hour recording is calculated on shorter segments (5 min) and averaged. ULF – Ultra Low frequency

Frequency Domain HRV Longer-Term HRV Total Power (TP) Sum of all frequency domain components. Ultra low frequency power (ULF) At >every 5 min to once in 24 hours. Reflects circadian, neuroendocrine, sustained activity of subject, and other unknown rhythms.

Frequency Domain HRV Intermediate-term HRV Very low frequency power (VLF) At ~20 sec-5 min frequency Reflects activity of renin-angiotensin system, vagal activity, activity of subject. Exaggerated by sleep apnea. Abolished by atropine Low frequency power (LF) At 3-9 cycles/min Baroreceptor influences on HR, mediated by SNS and vagal influences. Abolished by atropine. Renin-angiotensin system – regulates blood pressure via the kidney Atropine – inhibits acetylcholine actions.

Frequency Domain HRV Short-term HRV High frequency power (HF) At respiratory frequencies (9-24 cycles/minute, respiratory sinus arrhythmia but may also include non-respiratory sinus arrhythmia). Normally abolished by atropine. Vagal influences on HR with normal patterns.

Frequency Domain HRV Ratio HRV LF/HF ratio-may reflect SNS:PNS balance under some conditions. Normalized LF power= LF/(TP-VLF)-correlates with SNS activity under some conditions. Normalized HF power=HF/(TP-VLF)-proposed as a measure of relative vagal control of HR. Increased for abnormal HRV. Fundamental assumption: - a reciprocal relationship between sympathetic and parasympathetic nervous systems. - sometimes it “works” and sometimes it doesn’t.

24-hour average of 2-min power spectral plots in a healthy adult LF peak HF peak Spectral plots – graphical technique for examining cyclical structure in frequency domain. 0.20 Hz 0.40 Hz 24-hour average of 2-min power spectral plots in a healthy adult

Relationship of Time and Frequency Domain HRV SDNN Total Power SDANN Ultra Low Frequency Power SDNNIDX Very Low Frequency Power Low Frequency Power pNN50 High Frequency Power rMSSD

Non-Linear HRV Non-linear HRV characterize the structure of the HR time series, i.e., is it random or self-similar. Increased randomness of the HR time series is associated with worse outcomes in cardiac patients. Non-linear HRV measures are not available from commercial Holter systems.

Non-Linear HRV Most commonly used measure of randomness is the short-term fractal scaling exponent (DFA1 or α1). Decreased DFA1  increased randomness of the HR. Another index is power law slope, a measure of longer term self-similarity of HR. Decreased slope  worse outcome. Normal DFA1 is about 1.1. DFA1<0.85 is associated with higher risk.

Detrended Fluctuation Analysis (DFA) slope of the line - is the scaling coefficient (alpha) - used to determine correlated randomness See Appendix article for more information

Power Law Slope

Comparison of Normal and Highly Random HRV Plots