By Dr. Christopher Kent
Chaos theory
In the world of Newtonian physics, everything appeared predictable and causal. Relationships were linear, with an effect being proportional to its cause. However, there were situations where this did not seem to be the case. Poincare showed that there were stable and unstable types of orbits, and that a tiny disturbance could result in a significant change in the nature of the orbit. There were situations where similar causes resulted in dissimilar effects. [1]
Lorenz studied computerized weather forecasting, and noticed that starting such a program with only slightly different initial conditions would eventually result in completely different weather conditions. These findings led to the emergence of chaos theory. [1]
Chaos must be contrasted with randomness and periodicity. Random events are inherently unpredictable. In contrast, periodic behavior is highly predictable, as it repeats itself over time. Systems are close to static equilibrium unless there is an injection of energy to excite the system. Chaos shares characteristics of both randomness and periodicity. Chaos never repeats itself exactly, and although it may appear random, it is bounded, never wandering off into infinity. It has a definite form, and a particular pattern emerges. [2,3,4]
Autonomic tone
A recent paper by Lopez describes a proposed mechanism for control of vasomotor tone. Lopez wrote, “These postganglionic cells show bursts of activity with a periodicity that is related to cardiac and respiratory cycles, a coordination that might help to optimize the blood supply to every organ. How is this bursting activity controlled? One leading idea is that an oscillatory network in the brainstem entrains the sympathetic neurons, causing them to fire simultaneously.” [5]
What mediates this process? According to Staras et al [6] the answer is afferent somatic activity that can “reset” the oscillatory networks. This transiently synchronizes sympathetic neuron firing.
Heart rate variability
Many clinicians view the heart as a periodic oscillator, whose rate varies according to the demands of the organism. However, there is growing evidence that under physiologic conditions, the heart is not a periodic oscillator. [7,8,9,10,11]
Variability in heart rate reflects the vagal and sympathetic function of the autonomic nervous system, and has been used as a monitoring tool in clinical conditions characterized by altered autonomic nervous system function [12]. Spectral analysis of beattobeat variability is a simple, noninvasive technique to evaluate autonomic dysfunction [13].
Heart rate variability analysis has been used in the assessment of diabetic neuropathy and to predict the risk of arrhythmic events following myocardial infarction [14]. The technique has also been used to investigate autonomic changes associated with neurotoxicity [4], physical exercise [15], anorexia nervosa [16], brain infarction [17], angina [18], and panic disorder [19].
Normative data on heart rate variability have been collected [20,21,22]. This technology appears to hold promise for assessing overall fitness. Gallagher et al [23] compared agematched groups with different lifestyles. These were smokers, sedentary persons, and aerobically fit individuals. They found that smoking and a sedentary lifestyle reduces vagal tone, whereas enhanced aerobic fitness increases vagal tone. Dixon et al [24] reported that endurance training modifies heart rate control through neurocardiac mechanisms.
In occupational health, the effects of various stresses of the work environment of heart patients and asymptomatic workers may be evaluated using heart rate variability analysis [25].
Vertebral subluxation
Zhang and Dean [26] reported the results of an exciting study involving 520 subjects in a singlevisit group, and 111 subjects in a fourweek group. The purpose of the study was to investigate the effect of chiropractic care in a multiclinic setting on the balance of the sympathetic and parasympathetic nervous system using HRV (heart rate variability) analysis. The study demonstrated consistent changes in HRV. The authors reported, “The decreased heart rate and increased total power from the HRV analysis indicated a healthy autonomic nervous system balance after correction of vertebral subluxation.”
Acquired dysautonomia is one of the three elements in the threedimensional model of vertebral subluxation [27]. Skin temperature changes, reflecting alterations in vasomotor tone, are used clinically to assess autonomic changes associated with vertebral subluxations. Heart rate variability represents an exciting, noninvasive technology to assess subluxationrelated autonomic function. It will empower the practicing chiropractor to assess and communicate the farreaching impact of subluxation correction on global health.
References
1. Lorenz EN:”Deterministic nonperiodic flow.” J Atmospheric Sci 1963:20:130141.
2. Crutchfield JP, Farmer JD, Packard NH, Shaw RS: “Chaos.” Sci Am 1987;255: 3849.
3. Gleick J: Chaos: “Making of a New Science.” New York: Viking. 1987.
4. Goldberger AL: “Nonlinear dynamics for clinicians: chaos theory, fractals, and complexity at the bedside.” The Lancet 1996;347:13121314.
5. Lopez JC: “Autonomic nervous system. Rhythms of the periphery.” Nature Reviews Neuroscience 2001;2:454.
6. Staras K, et al: “Resetting of sympathetic rhythm by somatic afferents causes postreflex coordination of sympathetic activity in the rat.” J Physiol 2001;533:537.
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12. DeDenedittis G, Cigada M, Bianchi A, et al: “Autonomic changes during hypnosis: a heart rate variability power spectrum analysis as a marker of sympathovagal balance.” Int J Clin Exp Hypn 1994;42(2):140.
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15. Nakamura Y, Yamamoto Y, Muraoka I: “Autonomic control of heart rate during physical exercise and fractal dimension of heart rate variability.” J Appl Physiol 1993;74(2):875.
16. Petretta M, Bonaduce D, Scalfi L, et al: “Heart rate variability as a measure of autonomic nervous system function in anorexia nervosa.” Clin Cardiol 1997;20(3):219.
17. Korpelainen JT, Sotaniemi KA, Huikuri HV, Myllya VV: “Abnormal heart rate variability as a manifestation of autonomic dysfunction in hemispheric brain infarction.” Stroke 1996;27(11):2059.
18. Kamalesh M, Burger AJ, Kumar S, Nesto R: “Reproducibility of time and frequency domain analysis of heart rate variability in patients with chronic stable angina.” Pacing Clin Electrophysiol 1995;18(11):1991.
19. Yeragani VK, Pohl R, Berger R, et al: “Decreased heart rate variability in panic disorder patients: a study of powerspectral analysis of heart rate.” Psychiatry Res 1993;46(1):89.
20. O’Brien IA, O’Hare P, Corrall RJ: “Heart rate variability in healthy subjects: effect of age and the derivation of normal ranges for tests of autonomic function.” Br Heart J 1986;55(4):348.
21. Toyry J, Mantysaari M, Hartikainen J, Lansimies E: “Daytoday variability of cardiac autonomic regulation parameters in normal subjects.” Clin Physiol 1995;15(1):39.
22. Sato N, Miyake S, Akatsu J, Kumashiro M: “Power spectral analysis of heart rate variability in healthy young women during the normal menstrual cycle.” Psychosom Med 1995;57(4):331.
23. Gallagher D, Terenzi T, de Meersman R: “Heart rate variability in smokers, sedentary, and aerobically fit individuals.” Clin Auton Res 1992;2(6):383.
24. Dixon EM, Kamath MV, McCartney N, Fallen EL: “Neural regulation of heart rate variability in endurance athletes and sedentary controls.” Cardiovasc Res 1992;26(7):713.
25. KristalBoneh E, Raifel M, Froom P, Ribak J: “Heart rate variability in health and disease.” Scand J Work Environ Health 1995;21(2):85.
26. Zhang J, Dean D: “Effect of shortterm chiropractic care on pain and heart rate variability in a multisite clinical Study.” International Research and Philosophy Symposium: Abstracts. Sherman College of Straight Chiropractic. Spartanburg, SC. October 910, 2004.
27. Kent C: “A threedimensional model of vertebral subluxation.” The Chiropractic Journal 1998;12(9):38,50.