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Autonomic dysfunction in patients with fibromyalgia: Application of power spectral analysis of heart rate variability
Autonomic Dysfunction in Patients With Fibromyalgia: Application of Power Spectral Analysis of Heart Rate Variability Hagit Cohen, Lily Neumann, Margarita Shore, Marianne Amir, Yair Cassuto, and Dan Buskila
Objectives: To assess the interaction between the sympathetic and parasympathetic systems in patients with fibromyalgia syndrome (FM), using power spectrum analysis (PSA) of heart rate variability (HRV). In addition, we explored the association between HRV, measures of tenderness, FM symptoms, physical function, psychological well being and quality of life. Methods: We studied 22 women with FM and 22 age-matched healthy women. Twenty-minute electrocardiogram recordings were obtained in a supine position during complete rest. Spectral analysis of R-R intervals was done by the fast-Fourier transform algorithm. Results: Heart rate was significantly higher in FM patients compared with controls {P < .006). FM patients had significantly lower HRV compared with controls (P = .001), and higher low-frequency (LF) and lower high-frequency (HF) components of PSA than controls (P < .001). Quality of life, physical function, anxiety, depression, and perceived stress were moderately to highly correlated with LF, HF (in normalized units), and LF/HE No association was observed between HRV parameters and measures of tenderness and FNI symptoms. Conclusions: The basal autonomic state of patients with FM is characterized by increased sympathetic and decreased parasympathetic tones. Autonomic dysregulation may have implications regarding the symptomatology, physical and psychological aspects of health status. Semin Arthritis Rheum 29:217-227. Copyright © 2000 by W.B. Saunders Company
INDEX WORDS: Fibromyalgia syndrome; power spectrum analysis; heart rate variability; autonomic nervous system.
From the Ministry of Health Mental Health Center, Faculty of Health Sciences, Anxiety and Stress Research Unit, the Epidemiology Department, Rheumatic Disease Unit, Department of Medicine B, Soroka Medieal Center, Department of Behavioral Sciences, Department of Life-Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel. Hagit Cohen, Phl): Lecturer, Anxiety and Stress Research Unit; Ministry of Health Mental Health Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel," Lily Neumann, PhD: Professor, Epidemiology Department, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel; Margarita Shore, MD: Instructor, Rheumatic Disease Unit, Department of Medicine B, Soroka Medical Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel," Marianne Amir,
PhD: Senior Lecturer, Department of Behavioral Sciences, Faculty. of Humanities and Social Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel; Yair Cassuto, PhD: Professor, Department of Life-Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel; Dan Buskila, MD: Professor, Rheumatic Disease Unit, Department of Medicine B, Soroka Medical Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel. Address reprint requests to Dan Buskila, MD, Professor, Rheumatic Disease Unit, Department of Medicine B, Soroka Medical Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel. Copyright © 2000 by W.B. Saunders Company 0049-0172/00/2904-0003510.00/0
Seminars in Arthritis and Rheumatism, Vol 29, No 4 (February), 2000: pp 217-227
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IIBROMYALGIA (FM) SYNDROME is a chronic, painful musculoskeletal disorder of unknown cause affecting mostly women (1, 2). The pathophysiology of FM is not clear; however, neurochemical or central pain and soft tissue or peripheral mechanisms have been suggested (3-6). There is some evidence suggesting autonomic nervous system (ANS) involvement in the this syndrome (7-9). Several autonomic function tests were significantly deranged in the FM group when compared with controls: elevated heart rate (9), blood pressure decrease on tilting, heart rate increase with postural change (9), blood pressure decrease in stage I of the upright tilt test (10), and orthostatic sympathetic derangement of the baroreflex (11). Spectral analysis of heart rate variability is a simple noninvasive method for quantifying activity of the ANS functions (12). It is based on the fact that heart rate (HR) is not constant but oscillates around a mean value. These oscillations are due to modulations of ANS activity, which control the HR through the sympathetic and parasympathetic systems. The cyclic changes in sinus rate over time are termed heart rate variability (HRV) (12). Analysis of HRV provides quantitative information on autonomic tone as reflected by the effects of control mechanisms. In normal subjects, this includes the reaction to activity or postural changes (13), physical exercise (14), and mental/emotional stress (15). It has been proved useful in the study of various diseases, such as hypertension (16), diabetic neuropathy (17), heart failure (18), myocardial ischemia (19), and acute myocardial infarction (20). Spectral analysis of HRV usually demonstrates three major components ranging from 0 to 0.4 Hz. The most commonly employed bandwidths are the following: (a) very-low-frequency (0.01 to 0.04 Hz), designated VLF; (b) mid-frequency (0.04 to 0.2 Hz), designated LF; and (c) high-frequency (0.2 to 0.4 Hz), designated HE Power is calculated for each individual component (the area under the portion of the power Spectrum density [PSD] curve related to each component) and total power, represented by the total area under the PSD curve (12). Power can be provided in absolute units (msec 2) and in normalized units (nu). Normalized power, as well as the LF/HF ratio, quantify the fractional distribution of power across the frequency axis, irrespective of total power, and are commonly used to describe the sympathovagal balance. This ratio
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reflects the reciprocal relationship between the activity of the sympathetic system and the activity of the parasympathetic system (21). Numerous experimental results have suggested that HF is a marker of vagal activity (22). The LF power is considered a marker of both sympathetic and parasympathetic activity and apparently is associated with baroreceptor activity (22). The VLF component has not been given a precise physiological meaning and is subject to considerable debate, having been attributed variously to thermoregulatory processes, peripheral vasomotor activity, and the renin-angiotensin system. It is considered to be a predominately sympathetic indicator. Some investigators distinguish an additional ultra-low-frequency (ULF) component ranging from 10 -2 to 10 -5 Hz. A possible interpretation for the ULF component is that it is the result of long-term regulating mechanisms of heart rate as given by nonlinear chaotic deterministic systems (23). This study sought to explore the possible application of power spectrum analysis (PSA) of HRV in studying the dynamics of the interaction between the sympathetic and parasympathetic systems in fibromyalgia patients, as compared to healthy control subjects under the same conditions, and to explore the possible associations between HRV and measures of tenderness, FM symptoms, physical function, and quality of life.
METHODS Patients
The subjects were diagnosed as having FM if they fulfilled the currently accepted criteria of the American College of Rheumatology (2). We enrolled 22 women with FM (between the ages of 33 and 60 years), with a mean age of 47 + 7.1 years (15 were nonsmokers and 7 smokers) attending the rheumatology outpatient clinic in the University Hospital, Beer-Sheva, Israel. Participants had not taken any psychotropic or other medications known to alter autonomic activity for at least 4 weeks before the study, including antihypertensive drugs, tranquilizers, or antidepressants. Patients had no known history of structural cardiac abnormalities or any concomitant inflammatory rheumatic disease or any other illness known to affect the autonomic nervous system.
APPLICATION OF PSA OF HRV
Controls The control group comprised 22 healthy volunteers matched for age, sex, smoking, and time of day of electrocardiogram (ECG) recordings. They were chosen from a list of hospital personnel. All controls were healthy, with no serious or disabling coexisting diseases, specifically FM, as evidenced from their medical records and examination. Participants had not taken any psychotropic or other medications known to alter autonomic activity for at least 4 weeks before the study. The study was approved by the Helsinki Ethics Committee of the hospital. All participants gave their written consent after receiving detailed information about the study.
Instruments Electrocardiogram recording. The ECGrecording was obtained by connecting the subjects to a Holter monitor in a supine position during complete rest (Oxford 4-24). Twenty-minute segments of lead II ECG were amplified, digitized, and stored using a personal computer-based software system. To minimize anticipatory stress, the room was quiet, isolated from patient traffic, and a pleasant atmosphere was maintained at 25°C (to eliminate variations in temperature that might activate thermoregulatory mechanisms and change distribution of power frequencies in various bands). A detailed explanation of the procedure was given to the patients. After allowing 15 minutes for stabilization, the tests, consisting of a 20-minute recording of E C G while resting, began. Patients were instructed to breathe normally, and the respiratory rate was measured. ECG data were digitized at rate of 250 Hz (width pass, 0.05 to 35 Hz). The ECG signal was convetted into an event series, which required the measurement of R-R intervals (256 consecutive RR intervals). Premature beats and noise were excluded both automatically and manually, and only segments with greater than 90% qualified beats wer e included in the analysis, Representing this series a s a ~ c t i o n of the R-wave time of occurrenc e created a non-uniformly sampled event seties. Therefore, the second phase of the algorithm wa s interpolated Finally, analyses of HRV, fastF o Y e r transform, PSD (calculated as/as/Hz), were p e r f o ~ e d using signal processing software as described by others (21). We divided the power spectrum into 2 major frequency ranges: LF band
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(0.04 to 0.15 Hz) and HF band tO. 15 to 0.5 Hz). The integral of the power spectrum within each region was calculated (Simpson integration). Caution is required in interpreting our results because of possible artifacts in HF caused by respiration, secondary to hemodynamic effects of pressure variations, within the chest cavity. In our sample there were no differences in respiratory rate between the 2 groups. This implies that the hemodynamic changes, which could affect I-IF recording, were equivalent in both settings, so that any significant difference in HF can be mainly attributed to changes in parasympathetic tone. All ECG recordings were performed by another independent observer (H.C.), who was unaware of the subjects' stares (FM patient or a control). Arthritis Impact Measurement Scale (AIMS2). The AIMS2 instrument is a 78-item questionnaire (24). The first 57 items are broken down into 12 scales: mobility level, walking and bending, hand and finger function, arm function, self-care tasks, household tasks, social activity, support from family and friends, pain, work limitation, and level of tension and mood. The current study used the two subscales of tension and mood, each consisting of 6 items, Physical Function Assessment. Physical function and health status was assessed using the Fibromyalgia Impact Questionnaire (FIQ) (25). The first part of the FIQ focuses on the patient's ability to perform daily tasks (ie, cooking, cleaning, walking, etc ) and contains 10 items with responses ranked 0 to 3, where 0 = always able to do. and 3 = never able to do. The FIQ was translated and validated by us in a Hebrew version (26). The SF-36. This is a short health-related quality of life (QOL) questionnaire with 36 items whose reliability, validity, and acceptability have been demonstrated (27) and is widely used in medical outcomes research (28-30). The scale has been adapted to Hebrew and validated (31). The SF-36 is analyzed in 8 scale profiles (32) as follows: (1) Physical Function (10 items) asks about the extent to which health limits physical activity such as walking, climbing stairs, and vigorous activities. (2) Role Punctioning--Physica1 (4 items) asks about the extent to which physical health interferes with work or other daily activities. (3) R o l e Functioning-Emotional (3 items) asks about the extent to which emotional problems interfere with work or other daily activi-
220
ties. (4) Social Functioning (2 items) asks about the extent to which physical health or emotional problems interfere with normal social activities. (5) Bodily Pain (2 items) asks about the intensity of pain and the effect of pain on normal work. (6) Mental Health (5 items) asks about general mental health, inclnding depression, anxiety, behavioralemotional control, and general positive affect. (7) Vitality (4 items) asks whether a person feels energetic and full of pep versus tired and worn out. (8) General Health Perceptions (5 items) asks about personal evaluations of health, including current health, health outlook, and resistance to illness. The scales are normalized so that the scores range from 0 to 100; a higher score indicates better functioning. A last single item asks the subject to evaluate current health compared with 1 year ago, on a 5-point scale (1 = "much worse now than 1 year ago"; 5 = "much better now than 1 year ago"). Daily Stress Inventory. The Daily Stress Inventory (DSI) is a 57-item self-report measure that asks a person to indicate events that have been experienced in the past 24 hours (33). After indicating which events occurred, individuals rate the stressfulness of those events, on a Likert-type scale from 1 ("occmled but not stressful") to 7 ("caused me to panic"). Three scores are derived for each individual: (1) the number of events that are endorsed as having occurred (FREQ), (2) the sum of the total of the impact rating of these events (SUM), and (3) the average impact rating of the events (MR; SUM divided by FREQ) (33). Perceived Stress Scale. This scale is designed to measure the degree to which situations in one's life are perceived as stressful and assesses the degree to which respondents found their lives unpredictable and uncontrollable (34). The scale consists of 14 items measuring the occurrence of events on a Likert-type scale from 0 (never) to 4 (very often), for example, "In the last month, how often have you felt difficulties were piling up so high that you could not overcome them?" Severity of FM symptoms. Visual analog scales (VAS) were used by each patient to evaluate the current levels of pain, anxiety, depression, fatigue, morning Stiffness, and global well-being. The items were scored on a scale of 0 to 10, with 10 denoting the worst possible condition. The Symptom Checklist (SCL-90). The scale includes 90 items measuring 9 clinical subscales and was developed as a measure of general psychi=
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attic symptoms severity and as a descriptive measure of psychopathology (35, 36). Subjects report the degree to which they have been distressed by symptoms in the past month on a 5-point Likert scale. The scale has been extensively used and validated in Hebrew (37). The current study used the subscale of anxiety that is a common feature associated with FM. All questionnaires were completed in the presence of an interviewer, and assistance in answering the questions was given if needed. The interviewer ascertained that all subjects clearly understood the content of each item and the different aspects of various components. Tenderness assessment. Tenderness assessment (manually and with a dolotimeter) has been described i n great detail elsewhere (2). In all subjects, a count of 18 tender points (TPs) at 9 symmetrical sites was performed by thumb palpation. Definite tenderness at any point was considered present if some involuntary verbal or facial expression of pain occurred or a wince or withdrawal was observed. Thirteen sites (9 TP sites and 4 control sites) were further studied using a dolorimeter (38). All dolorimeter measurements of the 13 sites as well as a total point count were done by one observer (M.S.), before the interview about FM symptoms. Subjects were not told which were TPs and which were control points, and the points were mixed during the examination.
Statistical Analysis Student's t-tests were used to compare means of quantitative variables, and proportions were compared by chi-square tests. Associations between quantitative variables were analyzed using Pearson correlation coefficients. Because of the skewness of the data, logarithmic transformation was performed on the absolute units of the spectral components of HRV before the statistical analysis. RESULTS Demographic data of the subjects are summarized in Table 1. Gender, age distribution, marital status, and educational level were comparable in both groups. Percentage of employment was significantly lower in the FM group compared with the controls (P < .05). Prevalence of FM symptoms, their severity, and measures of tenderness in patients with FM and controls are presented in Table 2. The patients
221
APPLICATION OF PSA OF HRV
Table 1: Demographic Background of 22 Patients With FM and 22 Age-Matched Healthy Controls Variable
Age (years, mean _+ SD) Education (years, mean + SD) % Employed % Married Disease duration (years), mean ± SD Range
FNI Patients Controls Signif(N = 22) (N = 22) icance
47 (7)
47 (7)
NS
12 (5) 68 86
15 (4) 95 82
NS P < .05 NS
8 (8) 1-33
diagnosed as having FM reported significantly higher levels of pain (8.2 _+ 1.6 v 1.4 _+ 2.4, P < .01), fatigue (7.9 -+ 1.9 v 2.7 _+ 2.8, P < .01), morning stiffness (6.6 + 2.7 v 0.1 + 0.2, P < .01), depression (3.4 + 3.4 v 0.1 -+ 0.6, P < .01) and anxiety (4.9 + 3.2 v 1.3 _+ 2.2, P < .01) than controis. The prevalence of sleep disturbances, paresTable 2: Fibromyalgia Symptoms and Tenderness Measures of 22 FM Patients and 22 Healthy Controls
Variable
FM Patients (N = 22)
Controls (N = 22)
FM s y m p t o m s
Pain (0-10") Fatigue (0-10) Morning stiffness (0-10) Depression (0-10) Anxiety (0-10) Sleep problems (%) Headache (%) Paresthesias (%) Swelling (%) Irritable bowel syndrome (%) Tenderness measures Point count (0-18) Mean tenderness threshold at 9 tender sites Mean tenderness threshold at 4 control sites
8.2 (1.6)
1.4 (2.4)
7.9 (1.9)
2.7 (2,8)
6.6 (2.7) 3,4 (3.4) 4.9 (3.2)
0,1 (0.2) 0,1 (0,6) 1.3 (2.2)
91 86 86 73
14 64 9 14
64
5
14.9 (2.2)
0.3 (0.2)
2.2 (0.8)
4.1 (0.6)
2.9 (1.4)
5.8 (0.8)
NOTE. Results are expressed as mean and SD. All differences except "headache" between FM patients and healthy controls a re statistically sign ifica nt (P < .01 ). "VAS: 0-!0; 10, worst condition.
thesias, swelling, and irritable bowei syndrome was significantly (P < .01) higher among the FM patients. As expected, patients with FM were remarkably more tender than the control subjects. FM patients had higher TP counts and lower dolorimeter thresholds: the mean TP counts were 14.9 -+ 2.2 and 0.3 -+ 2.4 (P < .01), respectively, and the mean dolorimetry thresholds at 9 TP sites were 2.2 + 0.8 and 4.1 + 0.6 (P < .01), respectively. Table 3 summarizes the measures of physical function quality of life, psychological well-being, and stress in FM patients and controls. Patients with FM had significantly higher total emotional and behavioral scores than controls. Significant differences in mean physical function scores and mean quality of life scores in all subscales were found between the FM patients and controls. FM patients had significantly higher anxiety (according to SCL-90 and AIMS), depression, and perceived stress scores than normal subjects. Power spectrum analysis results are summarized in Table 4 and in Figure 1. HR was significantly higher in FM patients compared with controls IP = .0057). FM patients had significantly lower HRV compared with controls (P = .0012). They also had a significantly higher LF component and lower HF component (nu) compared with controls (P < .0001)i The LF component° in absolute units, was lower in FM patients than in controls, and, because the total power spectrum in FM also is lower than controls, the computed relative ratio (% nu) is higher in FM patients! These resuks indicate low HRV, low cardiac P arasympathetic tone, and , , elevated sympathetic activity in the FM patients in the rest stage in comparison with healthy controls. Correlations between HRV parameters (nu) and severity of FM symptoms and measures of tenderness in FM patients are summarize d in Table 5. There wasno association between HRV parameters (LF, HF, HRV, and HR) and the severity of FM and measures of tenderness in FM patients (except "pain" and HRV). Correlations between HRV parameters and physical function, quality of life, psychological wellbeing, and stress are summarized in Table 6. The most prominent relationship was between LF%. HF% and the ratio LF/HF, which had a significant negative correlation with 8 of the 9 QOL subscales. We found a significant correlation between LF%, HF% and the ratio LF/HF and physical function anxiety (accordir~g to SCL-90 and AIMS), depres-
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Table 3: Measures of Physical Function, Quality of Life, Psychological Well-Being, and Stress in FM Patients and Healthy Age-Matched Controls Number of Items
Measure (scale) Physical Function
10
Quality of life (SF-36) 1. Physical function 2. Role--physical 3. Bodily pain 4. General health 5. Vitality 6. Social function 7. Role--emotional 8. Mental health 9. Change in health Anxiety (SCL-90) Anxiety (AIMS) Depression (AIMS) Perceived stress (Cohen) Daily stress (DSI) 1, Number of events (FREQ) 2. Total impact (SUM) 3. Average impact (AIR)
36 10 4 2 5 4 2 3 5 1 10 6 6 14 57
Possible Range 0-31
FM Patients (N = 22)
Controls (N = 22)
1,1 (1,0)
0,1 (0,2)
0-1002 0-1002 0-1002 0-1002 0-1002 0-1002 0-1002 0-1002 1-53 14-5 14-6 14-6 05-56
43 (22) 24 (29) 31 (17) 44 (19) 42 (20) 55 (29) 61 (48) 51 (17) 2.9 (1.1) 2.0 (0.5) 5.3 (1.8) 3.6 (2.1) 26 (9)
94 (7) 99 (5) 80 (14) 71 (21) 69 (13) 93 (12) 92 (23) 70 (9) 3.1 (0.6) 1.2 (0.2) 3.0 (1.4) 1.6 (1.0) 16 (6)
05-57 05-399 14+
15 (8) 49 (43) 3.0 (1.4)
10 (8) 16 (14) 1.4 (0.5)
NOTE. The results are expressed as mean and SD. 31 = worst; 1002 = best; 53 = best; 14 = best; 0s = best. Description of measures--refer to "Methods" section. All differences (except "change in health") between FM patients and healthy controls are statistically significant (P < .01 ),
sion, perceived stress, and 2 subscales of daily stress: average impact and total impact. A significant correlation was found between total HRV and 4 of the 9 QOL subscales: physical function, role--physical, bodily pain, and general health. A Table 4: Power Spectral Analysis in FM Patients and Normal Controls
Frequency Domain
Fibromyalgia Patients (n = 22)
Control Group (n = 22)
Absolute (log) power values of the frequency bands: (msec 2) LF HF POWER normalized units LF (%) HF (%) LF/HF Heart Rate (beats/min) Heart rate variability
2.82 (2.6) 2.83 (1.88) 87 (6) 13 (6) 9 (5) 84 (10) 0.08 (0.05)
2.95 (2.79) 2.83 (2.78} 58 (24) 42 (24) 2,2 (1.7) 77 (7) 0.16 (0.1)
NOTE. Results are expressed as mean and SD. All differences are statistically significant (P < ,01 ).
negative association was observed between HR and the physical function subscale of SF-36. There were no significant correlations between HR and physical function (FIQ), 8 of 9 QOL scales, anxiety, depression, perceived stress, and daily stress. Interestingly, age and FM duration were not correlated with any of the PSA parameters. DISCUSSION
Using HRV, we showed a significant reduction in HRV, vagal tone, and augmented sympathetic activity in FM patients at rest, compared with normal age-matched controls. The above reflects a basal autonomic state of hyperactivafion characterized by increased sympathetic and decreased parasympathetic tone. Our findings support those of other researchers who have shown that FM patients have hyperactivity of the sympathetic nervous system (7) and elevated HR (10). Martinez-Lavin et al (10) assessed the sympathetic-parasympathetic balance in patients with FM and its response to orthostatic stress, by PSA of HRV. There was a deranged sympathetic response to orthostatic stress as compared with normal control subjects. Although con-
APPLICATION OF PSA OF HRV
N -r-
223
..... FMS P A T I E N T S ......... CONTROL
E Io
im
ill
U) C~
E
•
•
R
AI
L.
0~
U~ L_
HF
LF
O
0
FREQUENCY (Hz) Fig 1.
Spectral analysis of R-R interval variability in FM patients vhealthy controls.
trols displayed an increased PSD on standing (+0.081-+ 0.217 Hz), the FM patients bad a discordant response ( - 0 . 0 5 7 - 0.097 Hz) (P = .018). In patients with FM, the expected Table 5: Correlation (Pearson's Coefficients) Between Measures of HRV Parameters and Severity of FM Syndromes, and Measures of Tenderness in 22 FM Patients Variable
LF
HF
FM s y m p t o m s Pain
0.11
Fatigue Morning stiffness Depression Anxiety Tenderness Point count TP9 TC4
LF/HF
HRV
Heart Rate
-0.11
0.10
0.44* - 0 . 2
0.4
0,04
0.01
0.31
-0.2
-0.01
0,01
0.06 - 0 , 0 5
-0.3
0.02 0.01
0.04 0,28
-0,3 -0.04
0.28 0.04 -0.12 -0.38
-0.14 0.08
0.14 0.14 0.03 - 0 . 0 3 -0,01 -0.01
0.01 0,01
0.04 - 0 . 0 4
-0.15
-0.3
0.02
NOTE. Results are expressed as correlation coefficients ('/'). LF, low-frequency component (in normalized units); HF, high-frequency component (in normalized units); HRV, heart rate variability (in normalized units); TP9, mean tenderness at 9 tender point sites; TC4, mean tenderness at 4 control sites, * P < .05,
Abbreviations:
0.4
sympathetic surge in response to orthostatic stress was considered impaired. The authors also showed that the sympathetic component is markedly increased in supine patients, as compared with normal subjects in the same posture. After orthostatic stress, this component is decreased in FM patients, whereas the HR is increased. Martinez-Lavin et al (39) reported that patients with FM have diminished 24-hour HRV caused by an increased nocturnal predominance of the lowfrequency band oscillations consistent with an exaggerated sympathetic modulation of the sinus node. Qiao et al (40) measured electrodermal and microcirculatory parameters at baseline and after acoustic stimulation or cold pressor tests, extending the observation of a decreased sympathetic response to diverse stimuli. Vaeroy et al (41) reported that auditory stimulation and cold pressor tests elicited diminished vasoconstrictor response in patients with FM compared with controls. Elam et al (42) recorded muscle sympathetic activity with microneurography (direct measurement of the sympathetic activity from the peroneal nerve) and found less pronounced activation during isometric muscle contraction in patients with FM. These studies support the proposition that such patients have a decreased sympathetic response to stress.
224
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Table 6: Correlation (Pearson's Coefficients) Between Measures of HRV Parameters and Physical Function, Quality of Life, Psychological Well-Being and Stress (N = 44) FM S y m p t o m s
LF
HF
Physical function (FIQ) Quality of life (SF-36)
0.44*
1. Physical function 2. Role--physical 3. 4. 5. 6. 7.
Bodily pain General health Vitality Social function Role--emotional
8. Mental health 9. Change in health Anxiety (SCL-90) Anxiety (AIMS) Depression (AIMS) Perceived stress (Cohen) Daily stress t. Number of events 2. Total impact 3, Average impact
LF/HF
HRV
Heart Rate
0.44*
0.64t
-0,08
-0.54t 0.60t
-0.54t -0.60t
- 0.66t -0.67t
0.35~ 0.325
-0.42* 0,26
-0.59t -0.40* -0.41 * 0.51t 0.335
0.59t -0.40* -0.41 * 0.51t -0.335
- 0.61t - 0.38* -0,38" -0.62t -0.40*
0.35~ 0.295 0,19 0,23 0,11
-0.28 -0.15 -0.08 -0.11 0,05
-0.325 0.02 0.49t 0.38* 0.295 0.37*
-0.325 0.02 0.49t 0.38* 0,295 0.37*
-0.29~; 0.03 0.42* 0.40* 0.23 0.34~
0,09 0,01 -0,27 -0,20 -0,11 -0.23
-0.02 0.04 0.23 0.21 0.07 0.12
0,20 0.315 0.43*
0.20 0.315 0.43*
0.15 0.27 0.43*
-0.16 -0.23 -0.24
0,04 0.10 0.06
0.09
NOTE. Results are expressed as correlation coefficients ("r"). Abbreviations: LF, low-frequency component (in normalized units); HF, high-frequency component (in normalized units); HRV, heart rate variability (in normalized units). * P < .01. tP < .001. ~:P< .05.
There is evidence that patients suffering from certain psychiatric disorders, such as posttraumatic stress disorder (PTSD) (43, 44) and panic disorder (45) (both related strongly to anxiety and associated with depressive symptoms), show inordinately high/hyperactive sympathetic baseline parameters and low sympathetic system responses to stress. Thus, our findings of sympathetic hyperactivity at rest may not be contradictory to the dysfunctional response to stress. Because anxiety and depression are prevalent in FM, it will be interesting to see whether assessment of HRV at rest and in response to a stress paradigm in patients with FM (as done in PTSD and panic disorder [43, 44]) will elicit patterns similar to those reported by others. If so, it will be compatible with the results just presented, showing an attenuated stress response. One may speculate that the diminished or absent sympathetic response to stress in patients with FM results from chronic autonomic overstimulation at rest, preventing further response. Conversely, the disparity in sympathetic response in the different
studies in response to stress may be the result of limitations of the tool--that is, a ceiling effect. Thus, patients with FM showed autonomic dysregulation, expressed as an increased sympathetic tone, with concomitant decreased vagal tone at rest. This appears to reflect dysfunction of autonomic neuroregulation, as proposed by Martinez-Lavin et al (10). We postulate that sympathetic autonomic system overactivity at rest could be related, in part, to symptoms such as fatigue, sleep disturbances, paresthesias, and irritable bowel syndrome. The abnormal autonomic response to sympathetic challenges or physiological (tilt test) or psychological stress could explain findings such as low muscle tissue oxygen (46), abnormal muscle phosphate metabolism (47), decreased threshold for pain, and increased fatigue (48) in patients with FM. Because respiration can affect the reliability of HRV assessment, it is important to note that in our sample there were no changes in the respiratory rate (13 to 15 cyclic/rain) either in patients or
APPLICATION OF PSA OF HRV
225
controls at all stages. This implies that hemodynamic changes, which might affect I-IF recording, are equivalent in both settings, so that any significant difference in HF can be reliably attributed to changes in parasympathetic tone. PSA parameters correlated with physical func. tion, quality of life, anxiety, depression, and perceived stress. Interestingly, no significant associations were observed between HRV parameters and the severity of FM and measures of tenderness in patients, except pain and HRV. Reduction in parasympathetic tone was found at rest in some HRV studies of panic disorder patients (49), generalized anxiety disorder (50), depression (51), and PTSD (43, 44). Perhaps our findings are characteristic of anxiety disorders or depression in general and are not sPecific:for FM; that is, our findings may reflect a nonspecific anxiety-related response pattern in patients with FM. Experimental and clinical studies show that cardiovascular autono~c regulation plays an important role in cardiac morbidity and mortality (5254)~ Previous smdies indicate that decreased vagal activity, defined in terms: of a low HRV and low HF, is associated with several disease states and in-
creased risk of mortality, including sudden cardiac death (54, 55). The possible limitations of our study are (1) The study group is small (as in other trials), and the investigation should be repeated in larger patient populations; and (2) There is no consensus on the association between LF and sympathetic nervous system activity. The Task Force (21), Winchell and Hoyt (56), Amadi et al (57), and others, regard LF as reflecting sympathetic activity directly, whereas Sloan et al (58) and Skyschally et al (59) demonstrate no association between serum epinephrine levels and LF power. In summary, the findings of this study indicate a new aspect of autonomic dysfunction in FM. At rest, F M patients exhibit sympathetic hyperactivity and concomitantly reduced parasympathetic activity, Accordingly, analysis of HRV may be relevant for the assessment of autonomic dysregutadon in other disorders. Because changes in HRV are risk factors for cardiovascular morbidity, followrup studies are necessary to determine the course and effect of autonomic dysregulation in patients with FM.
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19. Rocco MB, Barry J, Cambell S, Nabel E, Cook EF, Goldman L, et al. Circadian variations of transient myocardial ischemia in patients with coronary artery disease. Circulation 1987;75:395-400. 20. Muller JE, Stone PH, Turi ZG, mad Mills study group. Circadian variation in the frequency of onset of acute myocardial infarction. N Engl J Med 1985;313:1315-22. 21. Task force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Heart rate variability: standards of measurement, physiological interpretation and clinical use. Circulation 1996;93:1043-65. 22. Ori Z, Monir G, Weiss J, Sayhouni X, Singer DH. Heart rate variability: frequency domain analysis. Ambulatory Electrocardiography 1992;10:499-537. 23. Cerutti S, Baselli G, Bianchi A, Signorini MG, Lissandrello F, Solari S, et al. Chaotic characteristics of heart rate and arterial pressure variability signals in 24 hours. IEEE Comp in Cardiol 1992;6:705-8. 24. Meenan RF, Mason JH, Anderson JJ, Guccione AA, Kazis LE. The content and properties of a revised and expanded arthritis impact measurement scales health status questionnaire. Arthritis Rheum 1992;35:1-10. 25. Burckhardt CS, Clark SR, Bennett RM. The fibromyalgia impact questionnaire: development and validation. J Rheumatol 1991;18:728-33. 26. Buskila D, Neumann L Assessing functional disability and health status of woman with fibromyalgia: validation of a Hebrew version of the fibromyalgia impact questionnaire. J Rheumatol 1996;23:903-6. 27. Mchorney CA, Ware JE, Rachel LU JF, Sherbourne CD. The MOS 36-item short-form health survey (SF-36): III. Tests of data quality, scaling assumptions, and reliability across diverse patients groups. Medical Care 1994;32:40. 28. Buchwall D, Peartman T, Umali J, Scmaling K, Katon W. Functional status in patients with chronic fatigue syndrome, other fatiguing illnesses, and healthy individuals. Am J Med 1996;171:364-70. 29. Rata DA, Hurst NP, Kind P, Hater M, Stubbings A. Measuring health status in British patients with rheumatoid arthritis: reliability, validity and responsiveness. Br J Rheumatol 1998;37:425-36. 30. Ware JE, Keller SD, Gandek B, Brazier JE, Sullivan M, and the IQOLA Project Group. Evaluating translations of health status questionnaires: methods from the IQOLA Project. Int J Technol Assess Health Care 1995;11:525-31. 31. Lewin-Epstein N, Sagiv-Sehifter T, Shabtal E, Shmueli A. Validation of the SF-36-Item short-form health survey (Hebrew version) in the adult population of Israel. Med Care 1998;36:1361-70. 32. Ware JE. SF-36 health survey, manual, and interpretation guide. Boston: The Health Institute, 1993. 33. Brantley PJ, Waggoner GNJ, Rappaport NB. A daily stress inventory: development, reliability, and validity. J Behav Meal 1987;10:61-9. 34. Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soe Behav 1983;24:385-96. 35. Derogatis L, Clearly R A confirmation of dimensional structure of the SCL-90: a study in consmact validity. J Clin Psychiatry 1977;33:981-9. 36. Derogatis L. The SCL-90 Manual: Scoring, administra-
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tion and procedure for the SCL-90. Baltimore: John Hopkins University, School of Medicine, 1979. 37. Swartzwald J, Solomon Z, Weisenberg M, Mikulincer M. Validation of the Impact of Event Scale for psychological sequel of combat. J Consult Clin Psychol 1987;55:251-6. 38. McCarty DJ, Gatter RD, Steele AD. A twenty pound dolorimeter for quantification of articular tenderness. Arthritis Rheum 1968;11:696-7. 39. Martinez-Lavin M, Hermosillo AG, Rosas M, Sort ME. Circadian studies of autonomic nervous balance in patients with fibromyalgia: a heart rate variability analysis. Arthritis Rheum 1998;41:1966-71. 40. Qiao Z, Vaeroy H, Morkrid L. Eleetrodermal and microcirculatory activity in patients with fibromyalgia during daseline, acoustic stimulation and cold pressor tests. J Rheumatol 1991;18:1383-9. 41. Vaeroy H, Qiao Z, Morkrid L, Forte O. Altered sympathetic nervous system response in patients with fibromyalgia (fibrositis syndrome). J Rheumatol 1989;16:1460-5. 42. Elam M, Johansson G, Wallin G. Do patients with primary fibromyalgia have an altered muscle sympathetic nerve activity? Pain 1992;48:371-5. 43. Cohen H, Kotler M, Matar MA, Kaplan Z, Miodownik H, Cassuto 51. Power spectral analysis of heart rate variability in post-traumatic stress disorder patients. Biol Psychiatry 1997;41: 627-9. 44. Cohen H, Matar AM, Kaplan Z, Mike A, Kotler M. Analysis of heart rate variability in post-traumatic stress disorder patients: at rest and in response to a trauma-related reminder. Biological Psychiatry 1998;44:1054-9. 45. Tucker P, Adamson P, Corbin B, Williams D, Groff J, Bottoms M. Heart rate variability in panic patients: autonomic balance. Abstract and poster presentation, annual meeting of American Psychiatric Association, San Francisco, CA, 1997. 46. Lund N, Bengtsson A, Thorborg E Muscle oxygen pressure in primary fibromyalgia. Scand J Rheumatol 1986;15: 165-73. 47. Bengtsson A, Henriksson KG, Larsson R Reduced high energy phosphate levels in the painful muscles of patients with primary fibromyalgia. Arthritis Rheum 1986;29:817-21. 48. Lefkowitz R, Hoffman B, Taylor R Neurohumoral transmission: the autonomic and somatic nervous system. In: Goodman-Gilman Arall T, editor. The pharmacological basis of therapeutics. New York: McGraw-Hill, International Edition, 1991:84-121. 49. Yeragani VK, Pohl R, Berger R, Balon R, Ramesh C, Glitz D, et al. Decreased heart rate variability in panic disorder patients: a study of power spectral analysis of heart rate. Psychiatry Res 1993;46:89-103. 50. Rechlin T. The significance of heart rate analysis in psychiatric questions. Fortschr Neurol Psychiatr 1995;63: 106-20. 51. Rechlin T. Decreased parameters of heart rate variation in amitriptyline treated patients: low parameters in melancholic depression than in neurotic depression--a biological marker? Biol Psychiatry 1994;36:705-7. 52. Schwartz PJ, Billman GE, Stone HL. Autonomic mechanisms in ventricular fibrillation induced by myocardial ischemia during exercise in dogs with a healed infarction: an experimental preparation for sudden cardiac death. Circulation 1984;69: 780-90.
APPLICATION OF PSA OF HRV
53. Kleiger RE, Miller JP, Bigger JT Jr, Moss AJ. Decreased heart rate variability and its association with increased mortality after acute myocardial infarction. Am J Cardiol 1987;59:256-62. 54. Tsuji H, Venditti F Jr, Manders ES, Evans JC, Larson MG, Feldman CL, et al. Reduced heart rate variability and mortality risk in an elderly cohort2 Circulation 1994;90:878-83. 55. Singer DH, Martin GJ, Magid N. Low heart rate variability and sudden cardiac death. J Electrocardiol 1988;21:46-55. 56. Winchell RJ, Hoyt DB. Spectral analysis of heart rate variability in the ICU: a measure of autonomic function. J Surg Res 1996;63:11-6.
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57. Amadi A, Ponikowski R Coats AJ. Role of catecholamines and sympathetic activation as a risk factor for coronary artery disease. J Cardiovasc Risk 1995;2:222-8. 58. Sloan RP, Shapiro PA, Bagie]la E, Bigger JT, Lo ES, Gorman JM. Relationships between circulating catecholarmnes and low frequenc~ heart period variability as indices of cardiac sympathetic activity during mental stress. Psychosom Med 1996:58:25-31. 59. Skyschally A. Breuer HW, Heusch G. The analysis of heart rate variability does not provide a reliable measurement of cardiac sympathetic activity. Clin Sci 1996:91:102-4.
Objectives: To assess the interaction between the sympathetic and parasympathetic systems in patients with fibromyalgia syndrome (FM), using power spectrum analysis (PSA) of heart rate variability (HRV). In addition, we explored the association between HRV, measures of tenderness, FM symptoms, physical function, psychological well being and quality of life. Methods: We studied 22 women with FM and 22 age-matched healthy women. Twenty-minute electrocardiogram recordings were obtained in a supine position during complete rest. Spectral analysis of R-R intervals was done by the fast-Fourier transform algorithm. Results: Heart rate was significantly higher in FM patients compared with controls {P < .006). FM patients had significantly lower HRV compared with controls (P = .001), and higher low-frequency (LF) and lower high-frequency (HF) components of PSA than controls (P < .001). Quality of life, physical function, anxiety, depression, and perceived stress were moderately to highly correlated with LF, HF (in normalized units), and LF/HE No association was observed between HRV parameters and measures of tenderness and FNI symptoms. Conclusions: The basal autonomic state of patients with FM is characterized by increased sympathetic and decreased parasympathetic tones. Autonomic dysregulation may have implications regarding the symptomatology, physical and psychological aspects of health status. Semin Arthritis Rheum 29:217-227. Copyright © 2000 by W.B. Saunders Company
INDEX WORDS: Fibromyalgia syndrome; power spectrum analysis; heart rate variability; autonomic nervous system.
From the Ministry of Health Mental Health Center, Faculty of Health Sciences, Anxiety and Stress Research Unit, the Epidemiology Department, Rheumatic Disease Unit, Department of Medicine B, Soroka Medieal Center, Department of Behavioral Sciences, Department of Life-Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel. Hagit Cohen, Phl): Lecturer, Anxiety and Stress Research Unit; Ministry of Health Mental Health Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel," Lily Neumann, PhD: Professor, Epidemiology Department, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel; Margarita Shore, MD: Instructor, Rheumatic Disease Unit, Department of Medicine B, Soroka Medical Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel," Marianne Amir,
PhD: Senior Lecturer, Department of Behavioral Sciences, Faculty. of Humanities and Social Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel; Yair Cassuto, PhD: Professor, Department of Life-Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel; Dan Buskila, MD: Professor, Rheumatic Disease Unit, Department of Medicine B, Soroka Medical Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel. Address reprint requests to Dan Buskila, MD, Professor, Rheumatic Disease Unit, Department of Medicine B, Soroka Medical Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel. Copyright © 2000 by W.B. Saunders Company 0049-0172/00/2904-0003510.00/0
Seminars in Arthritis and Rheumatism, Vol 29, No 4 (February), 2000: pp 217-227
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IIBROMYALGIA (FM) SYNDROME is a chronic, painful musculoskeletal disorder of unknown cause affecting mostly women (1, 2). The pathophysiology of FM is not clear; however, neurochemical or central pain and soft tissue or peripheral mechanisms have been suggested (3-6). There is some evidence suggesting autonomic nervous system (ANS) involvement in the this syndrome (7-9). Several autonomic function tests were significantly deranged in the FM group when compared with controls: elevated heart rate (9), blood pressure decrease on tilting, heart rate increase with postural change (9), blood pressure decrease in stage I of the upright tilt test (10), and orthostatic sympathetic derangement of the baroreflex (11). Spectral analysis of heart rate variability is a simple noninvasive method for quantifying activity of the ANS functions (12). It is based on the fact that heart rate (HR) is not constant but oscillates around a mean value. These oscillations are due to modulations of ANS activity, which control the HR through the sympathetic and parasympathetic systems. The cyclic changes in sinus rate over time are termed heart rate variability (HRV) (12). Analysis of HRV provides quantitative information on autonomic tone as reflected by the effects of control mechanisms. In normal subjects, this includes the reaction to activity or postural changes (13), physical exercise (14), and mental/emotional stress (15). It has been proved useful in the study of various diseases, such as hypertension (16), diabetic neuropathy (17), heart failure (18), myocardial ischemia (19), and acute myocardial infarction (20). Spectral analysis of HRV usually demonstrates three major components ranging from 0 to 0.4 Hz. The most commonly employed bandwidths are the following: (a) very-low-frequency (0.01 to 0.04 Hz), designated VLF; (b) mid-frequency (0.04 to 0.2 Hz), designated LF; and (c) high-frequency (0.2 to 0.4 Hz), designated HE Power is calculated for each individual component (the area under the portion of the power Spectrum density [PSD] curve related to each component) and total power, represented by the total area under the PSD curve (12). Power can be provided in absolute units (msec 2) and in normalized units (nu). Normalized power, as well as the LF/HF ratio, quantify the fractional distribution of power across the frequency axis, irrespective of total power, and are commonly used to describe the sympathovagal balance. This ratio
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reflects the reciprocal relationship between the activity of the sympathetic system and the activity of the parasympathetic system (21). Numerous experimental results have suggested that HF is a marker of vagal activity (22). The LF power is considered a marker of both sympathetic and parasympathetic activity and apparently is associated with baroreceptor activity (22). The VLF component has not been given a precise physiological meaning and is subject to considerable debate, having been attributed variously to thermoregulatory processes, peripheral vasomotor activity, and the renin-angiotensin system. It is considered to be a predominately sympathetic indicator. Some investigators distinguish an additional ultra-low-frequency (ULF) component ranging from 10 -2 to 10 -5 Hz. A possible interpretation for the ULF component is that it is the result of long-term regulating mechanisms of heart rate as given by nonlinear chaotic deterministic systems (23). This study sought to explore the possible application of power spectrum analysis (PSA) of HRV in studying the dynamics of the interaction between the sympathetic and parasympathetic systems in fibromyalgia patients, as compared to healthy control subjects under the same conditions, and to explore the possible associations between HRV and measures of tenderness, FM symptoms, physical function, and quality of life.
METHODS Patients
The subjects were diagnosed as having FM if they fulfilled the currently accepted criteria of the American College of Rheumatology (2). We enrolled 22 women with FM (between the ages of 33 and 60 years), with a mean age of 47 + 7.1 years (15 were nonsmokers and 7 smokers) attending the rheumatology outpatient clinic in the University Hospital, Beer-Sheva, Israel. Participants had not taken any psychotropic or other medications known to alter autonomic activity for at least 4 weeks before the study, including antihypertensive drugs, tranquilizers, or antidepressants. Patients had no known history of structural cardiac abnormalities or any concomitant inflammatory rheumatic disease or any other illness known to affect the autonomic nervous system.
APPLICATION OF PSA OF HRV
Controls The control group comprised 22 healthy volunteers matched for age, sex, smoking, and time of day of electrocardiogram (ECG) recordings. They were chosen from a list of hospital personnel. All controls were healthy, with no serious or disabling coexisting diseases, specifically FM, as evidenced from their medical records and examination. Participants had not taken any psychotropic or other medications known to alter autonomic activity for at least 4 weeks before the study. The study was approved by the Helsinki Ethics Committee of the hospital. All participants gave their written consent after receiving detailed information about the study.
Instruments Electrocardiogram recording. The ECGrecording was obtained by connecting the subjects to a Holter monitor in a supine position during complete rest (Oxford 4-24). Twenty-minute segments of lead II ECG were amplified, digitized, and stored using a personal computer-based software system. To minimize anticipatory stress, the room was quiet, isolated from patient traffic, and a pleasant atmosphere was maintained at 25°C (to eliminate variations in temperature that might activate thermoregulatory mechanisms and change distribution of power frequencies in various bands). A detailed explanation of the procedure was given to the patients. After allowing 15 minutes for stabilization, the tests, consisting of a 20-minute recording of E C G while resting, began. Patients were instructed to breathe normally, and the respiratory rate was measured. ECG data were digitized at rate of 250 Hz (width pass, 0.05 to 35 Hz). The ECG signal was convetted into an event series, which required the measurement of R-R intervals (256 consecutive RR intervals). Premature beats and noise were excluded both automatically and manually, and only segments with greater than 90% qualified beats wer e included in the analysis, Representing this series a s a ~ c t i o n of the R-wave time of occurrenc e created a non-uniformly sampled event seties. Therefore, the second phase of the algorithm wa s interpolated Finally, analyses of HRV, fastF o Y e r transform, PSD (calculated as/as/Hz), were p e r f o ~ e d using signal processing software as described by others (21). We divided the power spectrum into 2 major frequency ranges: LF band
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(0.04 to 0.15 Hz) and HF band tO. 15 to 0.5 Hz). The integral of the power spectrum within each region was calculated (Simpson integration). Caution is required in interpreting our results because of possible artifacts in HF caused by respiration, secondary to hemodynamic effects of pressure variations, within the chest cavity. In our sample there were no differences in respiratory rate between the 2 groups. This implies that the hemodynamic changes, which could affect I-IF recording, were equivalent in both settings, so that any significant difference in HF can be mainly attributed to changes in parasympathetic tone. All ECG recordings were performed by another independent observer (H.C.), who was unaware of the subjects' stares (FM patient or a control). Arthritis Impact Measurement Scale (AIMS2). The AIMS2 instrument is a 78-item questionnaire (24). The first 57 items are broken down into 12 scales: mobility level, walking and bending, hand and finger function, arm function, self-care tasks, household tasks, social activity, support from family and friends, pain, work limitation, and level of tension and mood. The current study used the two subscales of tension and mood, each consisting of 6 items, Physical Function Assessment. Physical function and health status was assessed using the Fibromyalgia Impact Questionnaire (FIQ) (25). The first part of the FIQ focuses on the patient's ability to perform daily tasks (ie, cooking, cleaning, walking, etc ) and contains 10 items with responses ranked 0 to 3, where 0 = always able to do. and 3 = never able to do. The FIQ was translated and validated by us in a Hebrew version (26). The SF-36. This is a short health-related quality of life (QOL) questionnaire with 36 items whose reliability, validity, and acceptability have been demonstrated (27) and is widely used in medical outcomes research (28-30). The scale has been adapted to Hebrew and validated (31). The SF-36 is analyzed in 8 scale profiles (32) as follows: (1) Physical Function (10 items) asks about the extent to which health limits physical activity such as walking, climbing stairs, and vigorous activities. (2) Role Punctioning--Physica1 (4 items) asks about the extent to which physical health interferes with work or other daily activities. (3) R o l e Functioning-Emotional (3 items) asks about the extent to which emotional problems interfere with work or other daily activi-
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ties. (4) Social Functioning (2 items) asks about the extent to which physical health or emotional problems interfere with normal social activities. (5) Bodily Pain (2 items) asks about the intensity of pain and the effect of pain on normal work. (6) Mental Health (5 items) asks about general mental health, inclnding depression, anxiety, behavioralemotional control, and general positive affect. (7) Vitality (4 items) asks whether a person feels energetic and full of pep versus tired and worn out. (8) General Health Perceptions (5 items) asks about personal evaluations of health, including current health, health outlook, and resistance to illness. The scales are normalized so that the scores range from 0 to 100; a higher score indicates better functioning. A last single item asks the subject to evaluate current health compared with 1 year ago, on a 5-point scale (1 = "much worse now than 1 year ago"; 5 = "much better now than 1 year ago"). Daily Stress Inventory. The Daily Stress Inventory (DSI) is a 57-item self-report measure that asks a person to indicate events that have been experienced in the past 24 hours (33). After indicating which events occurred, individuals rate the stressfulness of those events, on a Likert-type scale from 1 ("occmled but not stressful") to 7 ("caused me to panic"). Three scores are derived for each individual: (1) the number of events that are endorsed as having occurred (FREQ), (2) the sum of the total of the impact rating of these events (SUM), and (3) the average impact rating of the events (MR; SUM divided by FREQ) (33). Perceived Stress Scale. This scale is designed to measure the degree to which situations in one's life are perceived as stressful and assesses the degree to which respondents found their lives unpredictable and uncontrollable (34). The scale consists of 14 items measuring the occurrence of events on a Likert-type scale from 0 (never) to 4 (very often), for example, "In the last month, how often have you felt difficulties were piling up so high that you could not overcome them?" Severity of FM symptoms. Visual analog scales (VAS) were used by each patient to evaluate the current levels of pain, anxiety, depression, fatigue, morning Stiffness, and global well-being. The items were scored on a scale of 0 to 10, with 10 denoting the worst possible condition. The Symptom Checklist (SCL-90). The scale includes 90 items measuring 9 clinical subscales and was developed as a measure of general psychi=
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attic symptoms severity and as a descriptive measure of psychopathology (35, 36). Subjects report the degree to which they have been distressed by symptoms in the past month on a 5-point Likert scale. The scale has been extensively used and validated in Hebrew (37). The current study used the subscale of anxiety that is a common feature associated with FM. All questionnaires were completed in the presence of an interviewer, and assistance in answering the questions was given if needed. The interviewer ascertained that all subjects clearly understood the content of each item and the different aspects of various components. Tenderness assessment. Tenderness assessment (manually and with a dolotimeter) has been described i n great detail elsewhere (2). In all subjects, a count of 18 tender points (TPs) at 9 symmetrical sites was performed by thumb palpation. Definite tenderness at any point was considered present if some involuntary verbal or facial expression of pain occurred or a wince or withdrawal was observed. Thirteen sites (9 TP sites and 4 control sites) were further studied using a dolorimeter (38). All dolorimeter measurements of the 13 sites as well as a total point count were done by one observer (M.S.), before the interview about FM symptoms. Subjects were not told which were TPs and which were control points, and the points were mixed during the examination.
Statistical Analysis Student's t-tests were used to compare means of quantitative variables, and proportions were compared by chi-square tests. Associations between quantitative variables were analyzed using Pearson correlation coefficients. Because of the skewness of the data, logarithmic transformation was performed on the absolute units of the spectral components of HRV before the statistical analysis. RESULTS Demographic data of the subjects are summarized in Table 1. Gender, age distribution, marital status, and educational level were comparable in both groups. Percentage of employment was significantly lower in the FM group compared with the controls (P < .05). Prevalence of FM symptoms, their severity, and measures of tenderness in patients with FM and controls are presented in Table 2. The patients
221
APPLICATION OF PSA OF HRV
Table 1: Demographic Background of 22 Patients With FM and 22 Age-Matched Healthy Controls Variable
Age (years, mean _+ SD) Education (years, mean + SD) % Employed % Married Disease duration (years), mean ± SD Range
FNI Patients Controls Signif(N = 22) (N = 22) icance
47 (7)
47 (7)
NS
12 (5) 68 86
15 (4) 95 82
NS P < .05 NS
8 (8) 1-33
diagnosed as having FM reported significantly higher levels of pain (8.2 _+ 1.6 v 1.4 _+ 2.4, P < .01), fatigue (7.9 -+ 1.9 v 2.7 _+ 2.8, P < .01), morning stiffness (6.6 + 2.7 v 0.1 + 0.2, P < .01), depression (3.4 + 3.4 v 0.1 -+ 0.6, P < .01) and anxiety (4.9 + 3.2 v 1.3 _+ 2.2, P < .01) than controis. The prevalence of sleep disturbances, paresTable 2: Fibromyalgia Symptoms and Tenderness Measures of 22 FM Patients and 22 Healthy Controls
Variable
FM Patients (N = 22)
Controls (N = 22)
FM s y m p t o m s
Pain (0-10") Fatigue (0-10) Morning stiffness (0-10) Depression (0-10) Anxiety (0-10) Sleep problems (%) Headache (%) Paresthesias (%) Swelling (%) Irritable bowel syndrome (%) Tenderness measures Point count (0-18) Mean tenderness threshold at 9 tender sites Mean tenderness threshold at 4 control sites
8.2 (1.6)
1.4 (2.4)
7.9 (1.9)
2.7 (2,8)
6.6 (2.7) 3,4 (3.4) 4.9 (3.2)
0,1 (0.2) 0,1 (0,6) 1.3 (2.2)
91 86 86 73
14 64 9 14
64
5
14.9 (2.2)
0.3 (0.2)
2.2 (0.8)
4.1 (0.6)
2.9 (1.4)
5.8 (0.8)
NOTE. Results are expressed as mean and SD. All differences except "headache" between FM patients and healthy controls a re statistically sign ifica nt (P < .01 ). "VAS: 0-!0; 10, worst condition.
thesias, swelling, and irritable bowei syndrome was significantly (P < .01) higher among the FM patients. As expected, patients with FM were remarkably more tender than the control subjects. FM patients had higher TP counts and lower dolorimeter thresholds: the mean TP counts were 14.9 -+ 2.2 and 0.3 -+ 2.4 (P < .01), respectively, and the mean dolorimetry thresholds at 9 TP sites were 2.2 + 0.8 and 4.1 + 0.6 (P < .01), respectively. Table 3 summarizes the measures of physical function quality of life, psychological well-being, and stress in FM patients and controls. Patients with FM had significantly higher total emotional and behavioral scores than controls. Significant differences in mean physical function scores and mean quality of life scores in all subscales were found between the FM patients and controls. FM patients had significantly higher anxiety (according to SCL-90 and AIMS), depression, and perceived stress scores than normal subjects. Power spectrum analysis results are summarized in Table 4 and in Figure 1. HR was significantly higher in FM patients compared with controls IP = .0057). FM patients had significantly lower HRV compared with controls (P = .0012). They also had a significantly higher LF component and lower HF component (nu) compared with controls (P < .0001)i The LF component° in absolute units, was lower in FM patients than in controls, and, because the total power spectrum in FM also is lower than controls, the computed relative ratio (% nu) is higher in FM patients! These resuks indicate low HRV, low cardiac P arasympathetic tone, and , , elevated sympathetic activity in the FM patients in the rest stage in comparison with healthy controls. Correlations between HRV parameters (nu) and severity of FM symptoms and measures of tenderness in FM patients are summarize d in Table 5. There wasno association between HRV parameters (LF, HF, HRV, and HR) and the severity of FM and measures of tenderness in FM patients (except "pain" and HRV). Correlations between HRV parameters and physical function, quality of life, psychological wellbeing, and stress are summarized in Table 6. The most prominent relationship was between LF%. HF% and the ratio LF/HF, which had a significant negative correlation with 8 of the 9 QOL subscales. We found a significant correlation between LF%, HF% and the ratio LF/HF and physical function anxiety (accordir~g to SCL-90 and AIMS), depres-
COHEN ET AL
222
Table 3: Measures of Physical Function, Quality of Life, Psychological Well-Being, and Stress in FM Patients and Healthy Age-Matched Controls Number of Items
Measure (scale) Physical Function
10
Quality of life (SF-36) 1. Physical function 2. Role--physical 3. Bodily pain 4. General health 5. Vitality 6. Social function 7. Role--emotional 8. Mental health 9. Change in health Anxiety (SCL-90) Anxiety (AIMS) Depression (AIMS) Perceived stress (Cohen) Daily stress (DSI) 1, Number of events (FREQ) 2. Total impact (SUM) 3. Average impact (AIR)
36 10 4 2 5 4 2 3 5 1 10 6 6 14 57
Possible Range 0-31
FM Patients (N = 22)
Controls (N = 22)
1,1 (1,0)
0,1 (0,2)
0-1002 0-1002 0-1002 0-1002 0-1002 0-1002 0-1002 0-1002 1-53 14-5 14-6 14-6 05-56
43 (22) 24 (29) 31 (17) 44 (19) 42 (20) 55 (29) 61 (48) 51 (17) 2.9 (1.1) 2.0 (0.5) 5.3 (1.8) 3.6 (2.1) 26 (9)
94 (7) 99 (5) 80 (14) 71 (21) 69 (13) 93 (12) 92 (23) 70 (9) 3.1 (0.6) 1.2 (0.2) 3.0 (1.4) 1.6 (1.0) 16 (6)
05-57 05-399 14+
15 (8) 49 (43) 3.0 (1.4)
10 (8) 16 (14) 1.4 (0.5)
NOTE. The results are expressed as mean and SD. 31 = worst; 1002 = best; 53 = best; 14 = best; 0s = best. Description of measures--refer to "Methods" section. All differences (except "change in health") between FM patients and healthy controls are statistically significant (P < .01 ),
sion, perceived stress, and 2 subscales of daily stress: average impact and total impact. A significant correlation was found between total HRV and 4 of the 9 QOL subscales: physical function, role--physical, bodily pain, and general health. A Table 4: Power Spectral Analysis in FM Patients and Normal Controls
Frequency Domain
Fibromyalgia Patients (n = 22)
Control Group (n = 22)
Absolute (log) power values of the frequency bands: (msec 2) LF HF POWER normalized units LF (%) HF (%) LF/HF Heart Rate (beats/min) Heart rate variability
2.82 (2.6) 2.83 (1.88) 87 (6) 13 (6) 9 (5) 84 (10) 0.08 (0.05)
2.95 (2.79) 2.83 (2.78} 58 (24) 42 (24) 2,2 (1.7) 77 (7) 0.16 (0.1)
NOTE. Results are expressed as mean and SD. All differences are statistically significant (P < ,01 ).
negative association was observed between HR and the physical function subscale of SF-36. There were no significant correlations between HR and physical function (FIQ), 8 of 9 QOL scales, anxiety, depression, perceived stress, and daily stress. Interestingly, age and FM duration were not correlated with any of the PSA parameters. DISCUSSION
Using HRV, we showed a significant reduction in HRV, vagal tone, and augmented sympathetic activity in FM patients at rest, compared with normal age-matched controls. The above reflects a basal autonomic state of hyperactivafion characterized by increased sympathetic and decreased parasympathetic tone. Our findings support those of other researchers who have shown that FM patients have hyperactivity of the sympathetic nervous system (7) and elevated HR (10). Martinez-Lavin et al (10) assessed the sympathetic-parasympathetic balance in patients with FM and its response to orthostatic stress, by PSA of HRV. There was a deranged sympathetic response to orthostatic stress as compared with normal control subjects. Although con-
APPLICATION OF PSA OF HRV
N -r-
223
..... FMS P A T I E N T S ......... CONTROL
E Io
im
ill
U) C~
E
•
•
R
AI
L.
0~
U~ L_
HF
LF
O
0
FREQUENCY (Hz) Fig 1.
Spectral analysis of R-R interval variability in FM patients vhealthy controls.
trols displayed an increased PSD on standing (+0.081-+ 0.217 Hz), the FM patients bad a discordant response ( - 0 . 0 5 7 - 0.097 Hz) (P = .018). In patients with FM, the expected Table 5: Correlation (Pearson's Coefficients) Between Measures of HRV Parameters and Severity of FM Syndromes, and Measures of Tenderness in 22 FM Patients Variable
LF
HF
FM s y m p t o m s Pain
0.11
Fatigue Morning stiffness Depression Anxiety Tenderness Point count TP9 TC4
LF/HF
HRV
Heart Rate
-0.11
0.10
0.44* - 0 . 2
0.4
0,04
0.01
0.31
-0.2
-0.01
0,01
0.06 - 0 , 0 5
-0.3
0.02 0.01
0.04 0,28
-0,3 -0.04
0.28 0.04 -0.12 -0.38
-0.14 0.08
0.14 0.14 0.03 - 0 . 0 3 -0,01 -0.01
0.01 0,01
0.04 - 0 . 0 4
-0.15
-0.3
0.02
NOTE. Results are expressed as correlation coefficients ('/'). LF, low-frequency component (in normalized units); HF, high-frequency component (in normalized units); HRV, heart rate variability (in normalized units); TP9, mean tenderness at 9 tender point sites; TC4, mean tenderness at 4 control sites, * P < .05,
Abbreviations:
0.4
sympathetic surge in response to orthostatic stress was considered impaired. The authors also showed that the sympathetic component is markedly increased in supine patients, as compared with normal subjects in the same posture. After orthostatic stress, this component is decreased in FM patients, whereas the HR is increased. Martinez-Lavin et al (39) reported that patients with FM have diminished 24-hour HRV caused by an increased nocturnal predominance of the lowfrequency band oscillations consistent with an exaggerated sympathetic modulation of the sinus node. Qiao et al (40) measured electrodermal and microcirculatory parameters at baseline and after acoustic stimulation or cold pressor tests, extending the observation of a decreased sympathetic response to diverse stimuli. Vaeroy et al (41) reported that auditory stimulation and cold pressor tests elicited diminished vasoconstrictor response in patients with FM compared with controls. Elam et al (42) recorded muscle sympathetic activity with microneurography (direct measurement of the sympathetic activity from the peroneal nerve) and found less pronounced activation during isometric muscle contraction in patients with FM. These studies support the proposition that such patients have a decreased sympathetic response to stress.
224
COHEN ET AL
Table 6: Correlation (Pearson's Coefficients) Between Measures of HRV Parameters and Physical Function, Quality of Life, Psychological Well-Being and Stress (N = 44) FM S y m p t o m s
LF
HF
Physical function (FIQ) Quality of life (SF-36)
0.44*
1. Physical function 2. Role--physical 3. 4. 5. 6. 7.
Bodily pain General health Vitality Social function Role--emotional
8. Mental health 9. Change in health Anxiety (SCL-90) Anxiety (AIMS) Depression (AIMS) Perceived stress (Cohen) Daily stress t. Number of events 2. Total impact 3, Average impact
LF/HF
HRV
Heart Rate
0.44*
0.64t
-0,08
-0.54t 0.60t
-0.54t -0.60t
- 0.66t -0.67t
0.35~ 0.325
-0.42* 0,26
-0.59t -0.40* -0.41 * 0.51t 0.335
0.59t -0.40* -0.41 * 0.51t -0.335
- 0.61t - 0.38* -0,38" -0.62t -0.40*
0.35~ 0.295 0,19 0,23 0,11
-0.28 -0.15 -0.08 -0.11 0,05
-0.325 0.02 0.49t 0.38* 0.295 0.37*
-0.325 0.02 0.49t 0.38* 0,295 0.37*
-0.29~; 0.03 0.42* 0.40* 0.23 0.34~
0,09 0,01 -0,27 -0,20 -0,11 -0.23
-0.02 0.04 0.23 0.21 0.07 0.12
0,20 0.315 0.43*
0.20 0.315 0.43*
0.15 0.27 0.43*
-0.16 -0.23 -0.24
0,04 0.10 0.06
0.09
NOTE. Results are expressed as correlation coefficients ("r"). Abbreviations: LF, low-frequency component (in normalized units); HF, high-frequency component (in normalized units); HRV, heart rate variability (in normalized units). * P < .01. tP < .001. ~:P< .05.
There is evidence that patients suffering from certain psychiatric disorders, such as posttraumatic stress disorder (PTSD) (43, 44) and panic disorder (45) (both related strongly to anxiety and associated with depressive symptoms), show inordinately high/hyperactive sympathetic baseline parameters and low sympathetic system responses to stress. Thus, our findings of sympathetic hyperactivity at rest may not be contradictory to the dysfunctional response to stress. Because anxiety and depression are prevalent in FM, it will be interesting to see whether assessment of HRV at rest and in response to a stress paradigm in patients with FM (as done in PTSD and panic disorder [43, 44]) will elicit patterns similar to those reported by others. If so, it will be compatible with the results just presented, showing an attenuated stress response. One may speculate that the diminished or absent sympathetic response to stress in patients with FM results from chronic autonomic overstimulation at rest, preventing further response. Conversely, the disparity in sympathetic response in the different
studies in response to stress may be the result of limitations of the tool--that is, a ceiling effect. Thus, patients with FM showed autonomic dysregulation, expressed as an increased sympathetic tone, with concomitant decreased vagal tone at rest. This appears to reflect dysfunction of autonomic neuroregulation, as proposed by Martinez-Lavin et al (10). We postulate that sympathetic autonomic system overactivity at rest could be related, in part, to symptoms such as fatigue, sleep disturbances, paresthesias, and irritable bowel syndrome. The abnormal autonomic response to sympathetic challenges or physiological (tilt test) or psychological stress could explain findings such as low muscle tissue oxygen (46), abnormal muscle phosphate metabolism (47), decreased threshold for pain, and increased fatigue (48) in patients with FM. Because respiration can affect the reliability of HRV assessment, it is important to note that in our sample there were no changes in the respiratory rate (13 to 15 cyclic/rain) either in patients or
APPLICATION OF PSA OF HRV
225
controls at all stages. This implies that hemodynamic changes, which might affect I-IF recording, are equivalent in both settings, so that any significant difference in HF can be reliably attributed to changes in parasympathetic tone. PSA parameters correlated with physical func. tion, quality of life, anxiety, depression, and perceived stress. Interestingly, no significant associations were observed between HRV parameters and the severity of FM and measures of tenderness in patients, except pain and HRV. Reduction in parasympathetic tone was found at rest in some HRV studies of panic disorder patients (49), generalized anxiety disorder (50), depression (51), and PTSD (43, 44). Perhaps our findings are characteristic of anxiety disorders or depression in general and are not sPecific:for FM; that is, our findings may reflect a nonspecific anxiety-related response pattern in patients with FM. Experimental and clinical studies show that cardiovascular autono~c regulation plays an important role in cardiac morbidity and mortality (5254)~ Previous smdies indicate that decreased vagal activity, defined in terms: of a low HRV and low HF, is associated with several disease states and in-
creased risk of mortality, including sudden cardiac death (54, 55). The possible limitations of our study are (1) The study group is small (as in other trials), and the investigation should be repeated in larger patient populations; and (2) There is no consensus on the association between LF and sympathetic nervous system activity. The Task Force (21), Winchell and Hoyt (56), Amadi et al (57), and others, regard LF as reflecting sympathetic activity directly, whereas Sloan et al (58) and Skyschally et al (59) demonstrate no association between serum epinephrine levels and LF power. In summary, the findings of this study indicate a new aspect of autonomic dysfunction in FM. At rest, F M patients exhibit sympathetic hyperactivity and concomitantly reduced parasympathetic activity, Accordingly, analysis of HRV may be relevant for the assessment of autonomic dysregutadon in other disorders. Because changes in HRV are risk factors for cardiovascular morbidity, followrup studies are necessary to determine the course and effect of autonomic dysregulation in patients with FM.
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