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P l e x u s Insights from complexity science for the practice of medicine Robert A. Lindberg, MD Darien, CT Plexus Institute.

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Presentation on theme: "P l e x u s Insights from complexity science for the practice of medicine Robert A. Lindberg, MD Darien, CT Plexus Institute."— Presentation transcript:

1 P l e x u s Insights from complexity science for the practice of medicine Robert A. Lindberg, MD Darien, CT Plexus Institute

2 P l e x u s Complexity Science Other labels used: – Chaos Theory – Nonlinear Dynamics – Science of Complex Adaptive Systems – Systems Theory Deals with the behavior and properties of systems

3 P l e x u s System definition A collection of agents interconnected around a common purpose

4 P l e x u s System examples Weather system Phone system Internet Stock Market Central Nervous System Immune System Human Body

5 P l e x u s Complex Dynamic System Properties Weather Agents obey Simple Rules – Wind, water, thermodynamics, etc Continual Dynamic Interplay between all the interconnected agents Net consequence cannot be forecast nor engineered

6 P l e x u s Weather patterns T I M E UNITUNIT

7 P l e x u s Complex Adaptive System Stock Market Agents follow simple rules – e.g. buy low, sell high Dynamic interplay between agents that have the ability to learn and adapt Consequences cannot be forecast or engineered

8 P l e x u s Dow Jones Average T I M E UNITUNIT

9 P l e x u s Properties of Complex Nonlinear Systems Simple Rules underlie complexity of system “Nonlinear” or variable Emergent order or stability created by the dynamic interactions between the agents of the system

10 P l e x u s Relevance of Complexity Science to Medicine Alternative model to the Mechanistic or Reductionist Model – Understand the whole by studying the parts – The body is similar to a machine with independent parts Concept of the human body as a complex adaptive system Systems embedded within systems The sum is greater than the parts

11 P l e x u s Human Body = Complex Adaptive System Comprised of many systems – Central Nervous System – Immune System – Cardiovascular System – G.I. System – Etc. Systems embedded within systems

12 P l e x u s Human Body Interacting with Larger Systems Nature Ecosystems Solar Cycles Micro-organisms Families, Organizations System embedded within systems

13 P l e x u s Complexity Determinants Number of Interconnected Agents and Number of Connections

14 P l e x u s Signature of Complex System behavior over time Waves, Rhythms, Oscillations, 1/f Noise, Chaotic Resonance, Nonlinear Dynamics, etc.

15 P l e x u s Thermostat – Closed System TEMPTEMP

16 P l e x u s Thermostat – Open System TEMPTEMP

17 P l e x u s Simple vs Complex Systems

18 P l e x u s Pattern of a Simple System: two agents, one connection

19 P l e x u s Pattern of a complex system: many agents, many connections

20 P l e x u s Diurnal Thermostat System

21 P l e x u s Circadian Body Temperature

22 P l e x u s Circadian Body Temperature wave on a wave

23 P l e x u s Waves vs Particles Observing the pattern of a system’s “waves” provides insight into it’s relative health and degree of complexity Wave patterns suggest the number of agents and the number of connections and their relative responsiveness to each other

24 P l e x u s Some examples of waves or rhythms Heart rate Brainwaves Temperature curve Action potential of nerves, muscles Blood pressure Hormonal pulses Circadian rhythm

25 P l e x u s Heart Rate Variability (HRV) An Independent Risk Factor for All Cause Mortality Why? – Represents a wave or rhythm indicative of the degree of physiologic health of the human system

26 P l e x u s Normal Heart Rate Variability Beats per minute time

27 P l e x u s Heart Rate Variability The Heart Rate cycles in a Wave like pattern over time A reflection of the behavior of the Cardiovascular System interacting and connected to many other agents Its pattern has prognostic implications A signature of complex systems behavior

28 P l e x u s Abnormal Heart Rate Variability Beats Per minute time

29 P l e x u s Chronotropic Response Beats per minute with exercise time

30 P l e x u s Usefulness of impaired chronotropic response to exercise as a predictor of mortality Chronotropic incompetence is a strong and independent predictor of death, even after accounting for angio severity of CAD 384 pt’s for Thallium stress tests Dresing;Am J Cardiol 2000;86:602

31 P l e x u s Prognostic implications of chronotropic incompetence in the Framingham Heart Study An attenuated heart rate response to exercise is predictive of increased mortality and coronary heart disease incidence 1575 males, mean age 43, prospective Lauer;Circulation.1996;93:1520

32 P l e x u s Effects of exercise training on chronotropic incompetence in pt’s with heart failure Exercise results in an increase in peak heart rate and partial reversal of chronotropic incompetence in patients with stable heart failure Keteyian; Am Heart J. 1999;138:233

33 P l e x u s Heart Rate Recovery Beats per minute time

34 P l e x u s Heart-Rate Recovery Immediately After Exercise as a Predictor of Mortality A delayed decrease in the heart rate during the first minute after graded exercise…is a powerful and independent predictor of the risk of death Cole; NEJM 1999;341:1351-7

35 P l e x u s Heart Rate Recovery after Submaximal Exercise Testing as a Predictor of Mortality Healthy Cohorts, routine testing Heart rate recovery 2 minutes after ETT Reduced HR recovery a powerful independent predictor of mortality in healthy adults Cole; Annals of Int Med. 2000;132:552

36 P l e x u s Heart rate variability Chronotropic response Heart rate recovery +

37 P l e x u s Heart Rate Variability Beats per minute time

38 P l e x u s Normal Heart Rate Variability restexertion

39 P l e x u s Decreased Heart Rate Variability rest exertion

40 P l e x u s Decreased HRV and its association with increased mortality after acute MI Multicenter Post-Infarction research group Reduced HRV post MI poor prognosis independent of traditional risk factors Kleiger. Am J Cardiol. 1987;59:256

41 P l e x u s HRV as a predictor of mortality in the Elderly Random sample of elderly over 65, # 347 followed for 10 yrs Prognostic power of traditional risk factors compared 24 hr HRV best predictor of death in elderly subjects Circulation 1998;97:2031

42 P l e x u s Reduced Heart Rate Variability and Mortality Risk in an Elderly Cohort 2 hour Holter Moniter analysis Estimation of HRV offers prognostic information for all cause mortality beyond that provided by evaluation of traditional risk factors Circulation. 1994;90:878-883 Framingham Heart Study

43 P l e x u s HRV Components The Wave Model of HRV Amplitude – Rate of Change – Degree of Change Frequency – Variation in frequency rate

44 P l e x u s HRV Amplitude -- degree of change goodbad

45 P l e x u s HRV Amplitude -- rate of change good bad

46 P l e x u s HRV Frequency good bad

47 P l e x u s Cardiac Interbeat Interval Dynamics From Childhood to Senescence Healthy aging is associated with a loss of complex variability in R-R intervals New methods of R-R interval variability based on nonlinear dynamics may give insight into heart rate dynamics Pikkujamsa;Circulation.1999;100:393

48 P l e x u s Heritability of HRV The Framingham Heart Study Holter moniter data, comparing siblings “Heritable factors may explain a substantial proportion of the variance in HR and HRV” Singh;Circulation.1999;99:2251

49 P l e x u s Association of Depression With Reduced HRV in Coronary Artery Disease Depressed patients with CAD have decreased HRV compared with nondepressed CAD patients even after adjusting for relevant covariates Decreased HRV may explain the increased risk for cardiac mortality and morbidity in depressed patients Carney;Am J Cardiol 1995;76:562

50 P l e x u s HRV in healthy middle age pts, post MI pts and heart transplants HRV excellent predictor of death of any cause or arrhythmic death Heart Transplant most reduced HRV Circulation. 1996;93:2142

51 P l e x u s Association of hyperglycemia with reduced HRV Framingham Heart Study HRV is inversely associated with plasma glucose levels. It is reduced in both DM and in subjects with impaired fasting glucose Does reduced HRV contribute to increased cardiac mortality of DM and impaired FBG? Am J Cardiol 2000;86:309

52 P l e x u s Short and long term effects of cigarette smoking on HRV Smoking results in decreased vagal cardiac control leading to diminished HRV Hayano; Am J Cardiol 1990;65:84

53 P l e x u s Decreased HRV associations – a few examples Aging Diseases – CHF, Parkinsons, DM, Cancer, Depression Syndromes – Chronic Fatigue Syndrome, Sleep Apnea, Septic Shock Lifestyle – Smoking, Sedentary

54 P l e x u s Reduced HRV precedes Arrhythmias – atrial and ventricular Cardiac mortality All cause mortality Manifest disease

55 P l e x u s Altered Complexity and Correlation Properties of R-R Interval Dynamics Before Spontaneous Paroxysmal Atrial Fibrillation A decrease in HRV precedes the onset of AF in patients with no structural heart disease Vikman;Circulation.1999;100:2079

56 P l e x u s Low HRV in a 2 minute rhythm strip predicts rsk of CHD & mortality from several causes Middle aged men and women Low HRV predictive of increased mortality rates…this relation could not be attributed to cardiovascular risk factors or to underlying disease Low HRV precedes manifest disease Dekker;Circulation.2000;102:1239

57 P l e x u s Decomplexification in critical illness and injury: Relationship between HRV, severity of illness, and outcome 135 pediatric ICU admissions, mean age 6.8 Decomplexification of physiologic dynamics is equivalent to loss of variability or increased regularity The greater the severity of illness, the less HRV was detected. Applied to all illnesses Crit Care Med 1998;26:352-357

58 P l e x u s Multiple Organ Dysfunction Syndrome Linked with progressive reduction in Heart Rate Variability as the syndrome progresses HRV reflects trends and level of severity Correlation holds regardless of the inciting event of MODS

59 P l e x u s Uncoupling of biologic oscillators: A hypothesis re the pathogenesis of MODS Healthy organs behave as biologic oscillators, coupled and maintained by a communications network that includes neural, humoral and cytokine components HRV is a reflection of the degree of coupling between organ systems Godin; Crit Care Med;1996

60 P l e x u s Coupling of biological oscillators Heart CNS Immune Coupling

61 P l e x u s MODS and HRV SIRS initiates disruption of communication and uncoupling which if severe enough leads to MODS MODS a consequence of the uncoupling of organ systems as reflected by loss of biologic oscillations or variability HRV decreases as SIRS and MODS unfolds

62 P l e x u s Uncoupling of biologic oscillators: A hypothesis re the pathogenesis of MODS HRV decreases (organ isolation) with age HRV decreases (organ isolation) with SIRS Advanced age and SIRS means higher risk for MODS (irreversible organ isolation) Crit Care Med 1996;24:1107

63 P l e x u s Experimental human endotoxemia increases cardiac regularity Prospective, randomized, crossover trial Infusion of endotoxin into human volunteers causes loss of HRV HRV is an indicator of coupling between biologic oscillators(e.g. heart, brain, lung) MODS caused by an uncoupling of organ systems Crit Care Med 1996;24:1117

64 P l e x u s Decreased HRV Implies reduced interconnections Associated with reduced waves or rhythms throughout, ie – Temperature Variability – Diurnal Rhythms – Hormonal Pulses – Gait, agility, CNS activity, EEG pattern

65 P l e x u s Wave resonance - healthy Heart rate Brain Temperature Diurnal

66 P l e x u s Wave resonance - unhealthy Heart Brain Temperature Diurnal

67 P l e x u s HRV Implications HRV = Wave Wave = Signature of system dynamics System Dynamics = Complexity Complexity = Biologic Health/Resiliency

68 P l e x u s Biologic Resiliency Biology is mutually supportive systems Systems embedded within systems The rich and responsive interconnections between systems is key to robust health Wave patterns reflect the status of the interconnections and the responsiveness of the agents

69 P l e x u s Implications of HRV Insights from wave patterns Pharmacology Lifestyle choices Influencing HRV with training Ubiquity of waves or rhythms Everything is connected to everything else

70 P l e x u s HRV Implications Wave pattern implications – Decrease complexity = poor health – Increase complexity = good health

71 P l e x u s HRV Implications Pharmacology – Medications that can decrease HRV Amitryptiline, Anticholinergics, Anti-arryhthmics – Medications that can increase HRV in CHF Beta blockers, spironolactone – Testing of prospective new drugs

72 P l e x u s HRV Implications Lifestyle choices – Decrease HRV Smoking Sedentary – Increase HRV Exercise Meditation or relaxation techniques

73 P l e x u s HRV Implications Influencing HRV with training – Sprinters have high HRV – Ultra marathoners have low HRV Sprint training may have more of a health benefit than endurance training

74 P l e x u s HRV Implications Ubiquity of waves or rhythms at all levels – Biochemical oscillation – Cell cycles – Organ system – Organisms – Biosphere

75 P l e x u s HRV Implications Everything is connected to everything else

76 P l e x u s Circadian (24 hr) Rhythm an indicator of system health 6 am12 noon6 pm 12 pm

77 P l e x u s Healthy Circadian Rhythm “waves on waves” 6 am12 noon6 pm 12 pm

78 P l e x u s Abnormal Circadian Rhythm - less “waves on waves” 6 am12 noon6 pm12 pm

79 P l e x u s

80 end

81

82 Heart Rate Variability A risk factor for all cause mortality Robert A. Lindberg, MD

83 P l e x u s Effects of Spironolactone on HRV and LV systolic function in severe ischemic heart failure In CHF pt’s on conventional medications, the addition of spironolactone induces a favorable sympathovagal balance Korkmaz; Am J Cardiol 2000;86:649

84 P l e x u s Non-linear dynamics for clinicians: chaos theory, fractals, and complexity at the bedside Normal HRV represents multiscale fractal complexity of the heart rate Abnormal HRV represents loss of multiscale fractal complexity Goldberger;Lancet.1996;347:1312

85 P l e x u s Multifractality in human heartbeat dynamics Physiological signals under healthy conditions have a fractal temporal structure The healthy human heartbeat has fractal scaling There is a loss of fractal scaling in congestive heart failure Ivanov;Nature.1999;399:461

86 P l e x u s Fractals An object composed of subunits that resembles the larger scale structure, a property known as self-similarity At each scale of magnification, the pattern remains the same

87 P l e x u s Classical vs Fractal Geometry Classical Geometry – Smooth, regular, and integer dimensions (1, 2 and 3 for line, surface and volume respectively) Fractal Geometry – Rough, irregular and non-integer, or fractional dimensions

88 P l e x u s Classical (Euclidian) vs Fractal Line Classical: single scale and length Fractal: multiple scales, self-similar

89 P l e x u s Examples of Fractal Structures Trees, coral formations, clouds, coastlines, mountain ranges, galaxies Arterial and venous trees, neurons, tracheobronchial tree, His Purkinje network, intestinal villi

90 P l e x u s Examples of Non Fractal Structures

91 P l e x u s Fractal Structures

92 P l e x u s Fractal Processes Fractal processes generate irregular fluctuations on multiple time scales, analogous to fractal objects that have wrinkly structure on different length scales The variation over time is statistically self- similar

93 P l e x u s Examples of Fractal Processes Weather patterns, Dow Jones average, population dynamics Heart Rate, Respirations, Blood pressure, WBC counts, temperature Demonstrate Self-Similar Dynamics

94 P l e x u s Complex Nonlinear Systems A system consisting of a large and variable number of component parts The components display marked variability over time There is a high degree of connectivity and interdependence between variables

95 P l e x u s Complex nonlinear systems are ubiquitous in nature Weather patterns Biosphere of our planet Stock market Ecosystem of a tropical rain forest Central nervous system Immune system

96 P l e x u s Relevance of Complexity Science to Medicine Concept of the human body as a complex adaptive system Systems embedded within systems The sum is greater than the parts


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