ORIGINAL ARTICLE

Chronic Pain and Heart Rate Variability in a Cross-Sectional Occupational Sample Evidence for Impaired Vagal Control Julian Koenig, Dr. sc. hum.,* Adrian Loerbroks, PD Dr. sc. hum.,w Marc N. Jarczok, Dr. sc. hum.,z Joachim E. Fischer, MD, MSc,z and Julian F. Thayer, PhD*

Objectives: The vagus nerve influences the modulation of pain. Chronic pain is associated with disturbance of the descendent inhibitory pathway (DIP). Heart rate variability (HRV) is a proxy measure for vagal activity and may reflect dysfunction of the DIP. We aimed to investigate the association of HRV and pain in individuals with and without chronic pain. Materials and Methods: Drawing on cross-sectional data from 647 individuals, the present study explores the association of HRV and pain. The root mean square of successive differences (RMSSD), corresponding to parasympathetic regulation of the heart, was derived from 24-hour electrocardiogram recordings. Pain, demographic data, and health behaviors were assessed by self-administered questionnaires. Blood pressure was measured and inflammatory markers (white blood cell count, C-reactive protein, and fibrinogen) were analyzed from fasting blood samples. Results: Those with chronic pain reported lower RMSSD. Results revealed a negative correlation of HRV and pain in multivariateadjusted analysis only in respondents without chronic pain. Discussion: Our results suggest that the DIP indexed by vagal activity operationalized as RMSSD is disturbed in persons with chronic pain. Furthermore, the correlations between RMSSD and pain are different between those without and those with chronic pain. The findings are discussed, emphasizing changes in brain activity and the comorbid dysregulation of emotion in patients with chronic pain, to provide implications for the treatment of chronic pain. Key Words: chronic pain, vagus nerve, heart rate variability, inflammation

(Clin J Pain 2016;32:218–225)

Received for publication August 28, 2014; revised May 10, 2015; accepted April 7, 2015. From the *Emotions and Quantitative Psychophysiology Laboratory, Department of Psychology, The Ohio State University, Columbus, OH; wCenter for Health and Society, Institute of Occupational and Social Medicine, Faculty of Medicine, University of Du¨sseldorf, Du¨sseldorf; and zMannheim Institute of Public Health, Social and Preventive Medicine, Mannheim Medical Faculty, University of Heidelberg, Heidelberg, Germany. Support for the study was provided, in part, by the Federal Institute of Technology, Zurich, Switzerland, and the European Aeronautic Defence and Space Company (EADS), Germany (J.E.F.). The authors declare no conflict of interest. Reprints: Julian Koenig, Emotions and Quantitative Psychophysiology Laboratory, Department of Psychology, The Ohio State University, 175 Psychology Building, 1835 Neil Avenue, Columbus, OH 43210 (e-mail: [email protected]). Supplemental Digital Content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Website, www.clinicalpain.com. Copyright r 2015 Wolters Kluwer Health, Inc. All rights reserved. DOI: 10.1097/AJP.0000000000000242

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eripheral and central systems regulating cardiovascular function show interactions with the neural structures involved in pain sensation.1–4 Vagal-nociceptive networks have been extensively studied by chemical, electrical, or physiological manipulation of vagal afferents that affect nociception. These vagal afferents are capable to either inhibit or enhance noxious responses.5 The nucleus tractus solitarius (NTS) has been considered an interface between the autonomic and the sensory systems underlying vagalnociceptive interactions. The NTS receives major input from the vagus nerves and thus represents the initial relay for vagally mediated nociceptive effects. In addition to ascending pathways, this bidirectional network involves descending inhibitory pathways (DIPs) from cerebral structures to the dorsal horn, which suppress or potentiate the processing of nociceptive information.6 Related to the autonomic outflow, sympathetic and parasympathetic preganglionic nuclei in the spinal cord receive input from DIPs, and there is evidence that these influence pain thresholds and modify autonomic outflow by baroceptormediated changes in arterial pressure, leading to alterations in nociception of acute painful stimuli.6 The heart rate (HR) is under tonic inhibitory control (parasympathetic dominance over sympathetic influences).7 Thus, the characteristic beat-to-beat variability in the HR time series—the heart rate variability (HRV)—is a proxy measure for vagal activity, and may reflect activity of the DIP. On the basis of group comparisons in small samples with clinical pain conditions8–17 research has shown that HRV is reduced in patients with pain and related to extended pain-related sick leave.18 Although it is commonly known that chronic pain is associated with high sympathetic activation and low parasympathetic tone, the underlying mechanisms have not yet been addressed within larger nonclinical samples,19 using a measure of vagal activity (HRV). If chronic pain is associated with disrupted DIPs while assuming that HRV indexes DIPs, we hypothesize that those with chronic pain should show an attenuated association between pain and HRV. This represents the first report to investigate impaired vagal control, operationalized by measures of HRV, and pain in individuals with and without chronic pain. In addition, inflammatory processes that are usually considered mechanisms underlying several chronic pain conditions are modulated by the parasympathetic nervous system20,21 and have been linked to HRV.22–27 To our knowledge, no study has previously investigated a potential association of vagal control indexed by HRV and inflammatory markers beyond experimental manipulation in patients with chronic pain. Thus, we aimed to test for such a relationship.

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MATERIALS AND METHODS Study Population and General Procedure The study population consisted of employees from an airplane manufacturer located at multiple production sites in Southern Germany. This occupational cohort was initiated in 2000 with additional recruitment and follow-ups in 2002, 2003/ 2004, and 2007. For this analysis, we used cross-sectional data from September 2003 and February 2004, because HRV data were available only for the sample recruited during this period of time. In 2003/2004, questionnaire data were collected and medical examinations were carried out. The study was approved by the institutional review board of the Federal Institute of Technology, Zurich, Switzerland. All participants signed informed consent before any examination. Data from 657 individuals that participated in medical examinations including a 24-hour electrocardiogram (ECG) recording were available for the present analysis. We excluded 10 individuals from this sample due to ECG recording failures. Participants were scheduled for a fasting blood draw followed by a medical examination. All participants underwent medical examination between 9 and 11 AM on a typical work day. Blood pressure was measured 3 times with 15-minute intermediate resting periods while staying seated. Mean systolic (SBP) and diastolic blood pressures (DBP) were calculated as the mean of the second and the third measurement.

Questionnaire Data Questionnaires and other information were partly derived from the Nurses’ Health Study28 and from the MONICA study.29 These included a questionnaire for the assessment of demographic data, occupational status (eg, job position in the company), and information on chronic diseases, symptoms, and health behaviors. The average cigarettes smoked per day were assessed, as well as alcohol consumption as the cumulative number of alcoholic beverages (specified in equivalent units: eg, bottle or can of beer 0.5 L/unit; red or white wine 0.2 L/unit; liquor 50 mL/ glass) taken on average (response categories: not at all; 1 to 3/mo; 1/wk; 2 to 4/wk; 5 to 6/wk; 1/d; 2 to 3/d; 4 to 5/d; Z6/d). Alcohol intake was converted into average consumption in g/day and classified at the median below (abstinent or low) or above (moderate to high) the median split (11.2 g/d) for descriptive analysis. For the sake of descriptive analysis, current smokers were defined as those who reported to smoke at least 1 cigarette per day. The German version of the Short Form-12 Health Survey (SF-12) was used to assess health-related quality of life. The SF-12 is internationally and widely used short form developed from the original Short Form-36 Health Survey.30–34 It has proved to be a psychometrically robust and practical instrument in the outcome evaluation of subjective health functioning across different countries and populations.33,35 For the present analysis, the SF-12 physical and the mental summary scores were calculated following the algorithm outlined in the manual, yielding scores with a mean of 50 and a SD of 10 with lower scores indicating lower self-reported health-related quality of life in the respective domain. The Jenkins sleep score36 was used for the assessment of sleep problems. The questionnaire comprises 4 items rated on a 5-point Likert scale, which add to a total scale score of 0 to 20 with greater scores indicating more sleep problems. Copyright

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Pain-related Variables Pain was assessed by self-administered questionnaires. Items on pain at 8 individual sites were presented within a series of items on the frequency on various somatic complaints. The introductory question was: “Throughout the last year, to what extent did you suffer from the following complaints?.” Response categories for each item were “not at all,” “barely,” “moderately,” “severely.” The items relating to pain sites covered: pain in hip, pain in knee, pain in feet, (sharp) pain in chest/thorax, headache, pain in (lower) back, neck/shoulder pain, and pain in arms and hands. In addition to the analyses of individual pain items, we constructed a summary pain measure, by assigning a score to each response option (0 = “not at all” to 3 = “severely”) for each item and summing the score across all items. The resulting pain summary score had thus a potential range from 0 to 24 with higher scores indicating greater pain interference in more locations. The summary pain measure was computed only for individuals with complete information on all individual pain items (n = 624 of 647). Further, patients were asked to indicate (yes/no/don’t know) if they had chronic pain: “Within the last two years, did you consult medical help because of chronic pain?.”

HRV and Inflammatory Markers HRV was recorded as interbeat intervals (IBI) using a Mini-Vitaport ECG logger (Becker Medical Systems, Karlsruhe, Germany), sampling at a rate of 400 Hz. Study participants were instrumented with the ambulatory ECG recorders between 9 and 12 AM and were monitored until the next morning. After instrumentation with the ambulatory ECG recorder, individuals proceeded with their usual daily work routine until 3.30 PM and then continued with their usual leisure and sleep activities. The next morning between 7:15 and 8:00 AM, the ECG monitors were disconnected. Raw ECG data were processed according to the Task Force Guidelines.37 IBIs were calculated as the time between successive R-spikes. IBIs that corresponded to a mean HR < 30 or >200 as well as IBI changes of over 30% were excluded (artifact correction). The root mean square of successive differences (RMSSD), which is considered a time domain–based index corresponding to parasympathetic regulation of the heart, was used as the HRV measure. The RMSSD is less affected by breathing and is therefore a suitable outcome measure in ambulatory studies.38 Physical activity was assessed during the 24-hour ECG recording by means of an inbuilt 3D-accelerometer. The morning of returning the ECG monitors fasting blood samples were collected. Blood samples were immediately transported to a commercial laboratory (Synlab, Augsburg, Germany), where they were analyzed within 6 hours of sample collection. Plasma fibrinogen levels were determined by a routine clotting assay following the Clauss method.39 White blood cell count (WBC, leukocytes) was determined on a Sysmex SE-9000 automated analyser (Sysmex, Nordestadt, Germany). C-reactive protein (CRP40) was measured with a high-sensitivity assay (Dade Behring, Schwalbach, Germany). CRP is an acute phase protein produced by hepatocytes in response to inflammation or trauma.

Statistical Analyses All statistical analyses were carried out using SAS. Results were considered statistically significant at the P < 0.05 level. Descriptive data are presented as means and SD. Differences on all included variables between patients with and

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without chronic pain were investigated using analysis of variance or the w2 test for categorical variables, respectively. Next, Spearman correlation coefficients and multivariate-adjusted partial correlation coefficients (PCCs) relating each individual pain item as well as the pain summary score to RMSSD were calculated. The associations of pain (summary score), RMSSD, and inflammatory markers were analyzed in the same manner, further comparing individuals with chronic pain and those without chronic pain. PCCs adjusted for age (continuous) and sex were estimated followed by additional adjustment for the number of cigarettes smoked per day (continuous), alcohol in g/day (continuous), estimated physical activity per kg body weight (continuous), sleep quality (continuous), and job position in the company (categories: senior manager, foremen; qualified workers, unskilled workers, trainee). Information on these confounders was extracted from the questionnaire, except for physical activity. To examine whether a putative association between RMSSD and pain is specific to the vagus nerve, we further estimated PCCs for pain in relation to the mean IBI (derived from the 24-h HRV recordings), SBP, and DBP, respectively. Differences between correlations coefficients were calculated 1-sided using STATISTICA 7 to compare correlation strengths between individuals with chronic pain and those without chronic pain. None of the variables included in the analysis was significantly skewed or kurtotic, thus no further transformation was performed.



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RESULTS Characteristics of the study population are depicted in Table 1. The mean age was 41.6 (SD = 11.5) and 88.7% of the population was male. All socioeconomic positions were represented with the majority being qualified workers. With regard to lifestyle variables, this occupational middle-aged population showed a rather normal profile. The mean summary pain score and mean RMSSD were 7.6 (4.7) and 38.9 (14.4), respectively. A total of 75 (11.6%) individuals reported chronic pain within the last 2 years. Participants who did not clearly indicate whether they had chronic pain or not (don’t know, n = 43, 6.6%) were excluded from group comparisons. Individuals with chronic pain significantly differed from those without chronic pain with respect to age (F1,592 = 10.138, P = 0.0015), the number of days absent from work per year (F1,424 = 29.623, P < 0.0001), sleep quality (F1,597 = 35.490, P < 0.0001), the SF-12 physical summary score (F1,576 = 161.924, P < 0.0001), the SF-12 mental summary score (F1,576 = 9.966, P = 0.0017), and RMSSD (F1,602 = 5.646, P = 0.0178). The SF-12 mental summary score showed no significant correlation with RMSSD (r = 0.003, P = 0.946). The correlation did not significantly differ between those with (r = 0.082, P = 0.612) and without chronic pain (r = 0.010, P = 0.812). Differences on the long-term inflammatory markers (CRP and fibrinogen), although in the expected direction of higher values for those with chronic pain, were not significant between the groups (Fig. 1).

TABLE 1. Characteristics of the Study Population by Group (Without Chronic Pain versus with Chronic Pain)

Characteristics

Entire Sample

n 647 Age (mean [SD]) 41.56 (11.48) Sex (n [%]) Male 574 (88.7) Female 73 (11.3) Position (n [%]) Senior manager 28 (4.4) Foremen 77 (11.9) Qualified workers 500 (77.8) Unskilled workers 13 (2.0) Trainees 25 (3.9) No. days absent from work per year (mean [SD]) 12.51 (16.71) Current smoking (n [%]) No 469 (72.9) Yes 174 (27.1) Mean alcohol intake (n [%])* Abstinent or low 311 (48.82) Moderate to high 326 (51.18) Estimated physical activity per kg body weightw 4.11 (5.29) (mean [SD]) Jenkins’s sleep quality indexz (mean [SD]) 5.60 (4.17) SF-12 physical summary score (mean [SD]) 50.08 (8.22) SF-12 mental summary score (mean [SD]) 47.43 (10.01) Summary pain score (mean [SD])y 7.64 (4.66) RMSSD (mean [SD]) 38.94 (14.43) C-reactive protein (mean [SD]) 0.20 (0.38) White blood cell count (mean [SD]) 5.84 (1.61) Fibrinogen (mean [SD]) 293.72 (61.59)

Without Chronic Pain

With Chronic Pain

529 40.91 (11.50)

75 45.40 (10.83)

471 (89.0) 58 (11.0)

Chronic Pain Versus Without Chronic Pain (P) 0.0015 0.3455

64 (85.33) 11 (14.67) 0.17

26 65 404 8 24 10.61

(4.9) (12.3) (76.7) (1.5) (4.6) (14.28)

387 (73.4) 140 (26.6)

1 8 63 2 0 22.24

(1.35) (10.81) (85.14) (2.70) (0.00) (20.74)

< 0.0001 0.6817

56 (75.68) 18 (24.32) 0.0651

265 (50.48) 260 (49.52) 4.17 (5.42) 5.12 51.82 48.06 6.77 39.72 0.20 5.84 292.40

(3.96) (6.66) (9.71) (4.29) (14.70) (0.37) (1.61) (60.69)

28 (38.89) 44 (61.11) 3.59 (4.40) 8.09 40.29 44.13 12.04 35.48 0.26 5.66 304.60

(4.45) (10.20) (10.94) (4.12) (12.82) (0.50) (1.59) (72.54)

0.2981 < 0.0001 < 0.0001 0.0017 < 0.0001 0.0178 0.3414 0.3727 0.1686

Bold values highlight significant differences between groups. *Alcohol intake was classified at the median below (abstinent or low) or above (moderate to high) the median split (11.2 g/d). wPhysical activity was assessed during the 24-hour ECG recording by means of an inbuilt 3D-accelerometer. z4-item scale with a possible range from 4 to 24 points. Higher scores indicate poorer sleep quality. ySummary pain score combines the individual 8 pain items; potential score range 0 to 24 with higher scores indicating greater pain interference in multiple locations throughout the last year. RMSSD indicates root mean square of successive differences in milliseconds.

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Chronic Pain and Impaired Vagal Control

FIGURE 1. Root mean square of successive differences (RMSSD), fibrinogen, white blood cell count (WBC), and C-reactive protein (CRP) in participants with chronic pain and without chronic pain. *Significant difference on the 0.05 level.

Pain, regardless of its location, was very common in the study population (Table S1, Supplemental Digital Content 1, http://links.lww.com/CJP/A179). Back pain was most frequently followed by pain in neck/shoulder and headaches: only 13.5%, 26.8%, and 31.0% of the study participants reported to have not at all having (lower) back pain, pain in neck/shoulder and headache, respectively, throughout the year preceding the questionnaire. Pain in the hip was least common; however, moderate or severe degrees of hip pain were still reported by 16.7% of the sample. The mean RMSSD declined with increasing pain severity at each location. While RMSSD and the pain summary score were inversely associated in the entire sample (r =  0.18, P < 0.0001), and in those without chronic pain (r =  0.14, P < 0.01), this relationship was no longer present in those reporting chronic pain (r = 0.01, P = 0.96, Table 2). The proportion of shared variance between RMSSD and pain in the entire sample is 3.24% (R2 = 0.0324), 1.96% in individuals reporting no chronic pain (R2 = 0.0196), and 0.01% in individuals with chronic pain (R2 = 0.0001). Pain showed positive associations with markers of inflammation independently of the sample studied. Although not significant, the association of pain and inflammatory markers was 3 times larger in individuals with chronic pain compared with those without. These patterns were robust when controlling for age and sex, and in multivariate-adjusted models. RMSSD was inversely related to CRP, WBC, and fibrinogen in the entire sample and in those without chronic pain. In those with chronic pain, the same pattern was observed in unadjusted models, except for a positive association of RMSSD and WBC. The association of RMSSD and fibrinogen was 2 times larger in those with chronic pain within fully adjusted models. Again, all associations between RMSSD and any marker of inflammation in individuals with chronic pain were of similar magnitude as found in those without chronic pain but were not significant due to a lack of power. In unadjusted analyses (Table S2, Supplemental Digital Content 1, http://links.lww.com/CJP/A179), each individual pain item showed a significant inverse correlation with RMSSD. All associations of pain and RMSSD were attenuated by adjustment for age and sex. As a result, RMSSD only remained significantly related to hip pain (r = 0.09, P = 0.02), and neck/shoulder pain (r = 0.11, Copyright

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P < 0.01) and the summary pain score (r = 0.11, P = 0.01). When running models controlling only for either age or sex in post hoc analyses, we observed that by far most of the attenuation was due to age rather than sex. Multivariate-adjusted models yielded a similar pattern of associations as the age-adjusted and sex-adjusted models. In contrast to RMSSD, the mean IBI as well as SBP were not significantly associated with pain after multivariate adjustment (Table S3, Supplemental Digital Content 1, http://links.lww.com/CJP/A179 and Table S4, Supplemental Digital Content 1, http://links.lww.com/CJP/ A179, respectively). DBP was positively related to headache (r = 0.12, P < 0.01), but not to any other pain location or the summary pain score (Table S3, Supplemental Digital Content 1, http://links.lww.com/CJP/A179).

DISCUSSION This is the first study linking vagally mediated HRV, self-reported pain, and inflammatory markers in a large cross-sectional occupational sample, comparing individuals with chronic pain and those without. The study has several significant findings. First, for the first time we report a negative correlation between HRV and pain even in multivariate-adjusted analysis. Second, this association is no longer present in individuals with chronic pain (Table 2), and the correlations between RMSSD and pain are different between those without and those with chronic pain. Our results suggest, that the DIP indexed by vagal function operationalized as RMSSD is disturbed in persons with chronic pain, as pain is no longer related to vagal tone in individuals with chronic pain, even when controlling for a large variety of covariates. The effects reported in the present study are of potential clinical relevance. Whereas the amount of variance accounted for may appear small, small effect sizes may be associated with clinically significant effects. For example, in the Physicians’ Health Study, the amount of variance accounted for by low-dose aspirin use was 0.0011% but this translated to a 3.4% decrease in heart attacks. In the present study, the magnitude of the difference in RMSSD between those with chronic pain and those without chronic pain is 4.42 ms. Antelmi et al41 reported that RMSSD decreases 3.6 ms per decade. Thus, the difference in RMSSD

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Entire Sample Pain

r

With Chronic Pain

WBC

Fibrinogen

Pain

CRP

WBC

Fibrinogen

Pain

CRP

WBC

 0.18 < 0.0001

0.16 < 0.0001

0.17 < 0.0001

 0.14 < 0.01

 0.18 < 0.0001

 0.19 < 0.0001

0.17 < 0.0001

0.01 0.96

0.16 0.16

0.07 0.54

0.16 0.17

0.11 0.01

0.05 0.22

0.11 0.01

0.23 0.06

0.00 0.99

0.25 0.03

0.34 < 0.0001

0.55 < 0.0001

0.11 < 0.01

0.05 0.25 0.33 < 0.0001

0.13 < 0.01 0.56 < 0.0001 0.21 < 0.0001

 0.14 0.001

0.18 < 0.0001

0.07 0.12

0.04 0.32

0.05 0.28

0.33 < 0.0001

0.52 < 0.0001

0.09 < 0.05

0.21 < 0.0001

 0.08z 0.09

 0.16 < 0.0001

 0.21 < 0.0001

0.08 0.10

0.05 0.31

0.05 0.31

0.33 < 0.0001

0.54 < 0.0001

0.21 < 0.0001

0.12 < 0.01

0.07 0.09

0.03 0.44

0.02 0.63

0.02 0.70

0.31 < 0.0001

0.52 < 0.0001

0.10 < 0.05

0.08 0.51

0.15z 0.26

0.12 0.36

0.07 0.58

0.11 0.39

0.17 0.21

0.01 0.96

0.19 0.14

0.38 < 0.01

0.21 < 0.0001

 0.07z 0.11

 0.12 < 0.01

 0.15 < 0.01

0.07 0.12

0.05 0.33

0.03 0.55

0.02 0.67

0.31 < 0.0001

0.53 < 0.0001

0.53 < 0.0001

0.50 < 0.0001 0.09 0.48

0.15z 0.27

0.14 0.31

0.09 0.52

0.12 0.38

0.08 0.58

 0.08 0.55

0.13 0.35

0.34 < 0.01

0.49 < 0.0001



 0.12 < 0.01

0.36 < 0.01

Fibrinogen

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0.16 < 0.0001

0.16 < 0.0001

0.08 0.54

n for unadjusted models in the entire sample ranging from 619 to 645, in those without chronic pain ranging from 508 to 529, in those with chronic pain ranging from 71 to 75, n = 556 (entire sample), n = 462 in those without chronic pain, and n = 58 in those with chronic pain, respectively within age and sex-adjusted models; n = 538 (entire sample), n = 450 in those without chronic pain, and n = 49 in those with chronic pain, respectively within fully adjusted models. *The summary pain score combines the 8 individual pain items. wPartial Spearman correlation coefficient adjusted for age and sex. zCorrelations between RMSSD and pain are different on one tailed tests between those without and those with chronic pain (age and sex adjusted P = 0.05; fully adjusted P = 0.07). yPartial Spearman correlation coefficient adjusted for age (continuous), sex, number of cigarettes smoked per day (continuous), alcohol in g/d (continuous), estimated physical activity per kg body weight (continuous), Jenkins sleep index (continuous), position in the company (categories: senior manager, foremen; qualified workers, unskilled workers, trainee). CRP indicates C-reactive protein; RMSSD, root mean square of successive differences; WBC, white blood cell count.

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Unadjusted RMSSD r  0.18 P < 0.0001 Pain* r P CRP r P WBC r P Age and sexw RMSSD r  0.11 P 0.01 Pain r P CRP r P WBC r P Multivariabley RMSSD r  0.11 P 0.01 Painw r P CRP r P WBC r P

Without Chronic Pain

CRP

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TABLE 2. Spearman Correlations on RMSSD, Pain, and Inflammatory Markers in the Entire Sample and Subgroups

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between our pain groups is associated with a difference of > 10 years in age. Similarly, for back pain (the most common pain complaint), the difference in RMSSD between those reporting no pain to those reporting severe pain is 3.7 ms (the difference is 7.62 ms for the next most common complaint of neck/shoulder pain and 6.59 ms for headache; Table 1, Supplemental Digital Content 1, http://links.lww.com/CJP/A179). We have previously shown that an RMSSD difference of this magnitude is comparable to the effect of smoking versus not smoking.42 Therefore, we feel that our results are not just statistically significant but clinically meaningful as well. However, vagal modulation is just one of many factors that shape individual variation in the experience of pain. Consistent with previous findings individuals with chronic pain in our sample were older,43 reported more absenteeism,44,45 poorer sleep quality,46,47 as well as poorer physical and mental health.48 Although lower HRV is associated with a broad variety of these factors, we found a unique association of HRV and pain within multivariateadjusted models (Table 2), controlling for these covariates. In line with previous clinical research,8,10,13,15–17,49 we found lower HRV and greater inflammation (although not significant) in individuals with chronic pain. Furthermore, we observed a larger association between pain and inflammation in those with chronic pain, as well as inverse relationships between HRV and CRP, and fibrinogen.23,24 Besides the ascending pathways involved in transducing noxious stimuli to the central branches (presynaptic terminals in the spinal cord), DIPs inhibit pain transmission. This downward inhibition is relayed via the NTS— at least in pain-free individuals. Our results suggest that the capability of the DIP is disrupted as a consequence of impaired vagal control, indexed by changes in HRV. It is well known, that decreased activity in the DIP within the spinal cord dorsal horn contributes to the central sensitization in chronic pain that involves an increase in the excitability of neurons in the central nervous system.50 Decreased vagal activity results in greater somatic and visceral input via the spinothalamic track, which in turn provides a mechanism for decreased pain threshold and increased pain sensitivity in those with chronic pain. As recent research provides evidence for a shift in brain activity with the transition to chronic pain,51 the alteration of vagal activity is likely due to changes in brain areas involved in the control of vagal activity and emotion.52 These findings have major implications for the treatment of chronic pain, as it highlights the vagus as a potential target for therapeutic interventions. An important area involved in descending inhibitory modulation of pain is the periaqueductal gray (PAG). Recent research has shown that ventral PAG stimulation increases HRV and decreases pain in humans with chronic pain.53 This pathway is distinct from dorsal PAG deep brain stimulation, suggesting that analgesia with deep brain stimulation in chronic pain is associated with increased vagal parasympathetic activity.53 Considering these anatomic connections, our results provide further evidence for the prominent role of the vagus nerve in pain processing, and a rational for therapeutic vagus nerve stimulation in patients with chronic pain,11,54–59 with HRV as an additional outcome measure.60 Secondary findings of our study highlight that the relationship of HRV with various specific pain locations is consistent in unadjusted models. Except for the association between DBP and headache, pain was not related to other measures of autonomic outflow such as IBI, DBP, or SBP. Copyright

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Again, this supports the notion that the vagus nerve (reflected by RMSSD) has a specific relation to pain. Linking our findings to psychosomatic research, HRV has been proposed to serve as index of the degree to which the organism provides flexible, adaptive regulation within a model of Neurovisceral Integration.52,61,62 HRV serves as an index of regulation and dysregulation of emotion.61,63 As mentioned earlier, a shift to emotion-related circuit activity in the brain can be observed in chronic pain.51 Research highlights that efficacy in emotion regulation is related to quality of life and reduced negative affect in people with chronic pain.64 Thus, pain has also been discussed as a specific emotion that reflects homeostatic behavioral drive, similar to temperature, itch, hunger, and thirst65,66 challenging the organism to adapt. Resting HRV may provide an index of the integrity of central-peripheral feedback that is necessary for effective emotion regulation including effective regulation of pain. Our results provide evidence that the continuous excitation of the autonomic nervous system (ANS) as a product of nociceptive processing (ongoing experience of pain) might result in a dysfunction of the shared neural networks52,67 and DIPs incorporating the different components (eg, emotional, sensory) of pain perception that are further involved in providing the organism with the ability to integrate signals from inside and outside the body and adaptively regulate cognition, perception, action, and physiology.49 A shift to emotion-related circuit activity in those with chronic pain might therefore represent a loss of sensory integration due to decreased vagal activity. Greater affective processing of nociceptive information results in overstraining adaptive capabilities, which are further reflected by literature linking HRV to emotion,68–70 and depression,71–73 as well as cognition62,74 and executive function. In return ANS dysfunction—in particular higher cardiac sympathetic regulation75 and lower vagal tone— due to the continuous experience of pain might partly explain associated health issues, like poorer sleep quality46,47 found in patients with chronic pain (Table 1). In particular, we show that the association between RMSSD and pain is specific to the vagus nerve and no longer present in respondents with chronic pain, supporting a psychophysiological pathway by which emotional and cognitive dysfunction in patients with chronic pain may be mediated. The present study has several limitations that should be addressed. First, we used pain reports concerning the last year (summary score over different pain locations). The pain score calculated represents interference of pain in multiple locations that is not necessarily related to the severity, intensity, or frequency of (clinically relevant) pain symptoms. The assessment of chronic pain was based on the consultation for medical help due to chronic pain within the last 2 years. Thus, we cannot rule out that people who responded yes were chronic pain patients at the time of the questionnaire completion, and that those indicated “no” were not chronic pain patients. Furthermore, we were not able to distinguish different clinical chronic pain conditions, and individuals with chronic pain who did not consult medical help in the past several years. This misclassification is likely nondifferential (thus, not linked to HRV) and thus our estimates likely underestimate the true association. Clinical studies based on diagnostic criteria, incorporating an extensive pain examination are needed to address these issues. Because of the cross-sectional design of our study causal directions or temporal associations between HRV and pain cannot be

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concluded. Longitudinal studies to investigate the potential temporal sequence between reductions of vagal control, disruptions of DIPs, and changes in pain processing are strongly encouraged. Second, due to the cross-sectional design of our study and the occupational sample from an industry cohort studied, we were not able to explore possible sex differences, reported in the literature.76 Third, the present analysis did not control for other medical conditions, comorbidities, or medication intake. Future studies are necessary to address these limitations. In conclusion, we report for the first time that the experience of pain—in particular the degree of pain interference in multiple locations—is inversely associated with vagally mediated HRV in a nonclinical working cohort and that this relation is no longer present in those that reported chronic pain within the last 2 years. This suggests that ANS function—in particular the DIP, indexed by vagally mediated HRV—is disturbed in those with chronic pain due to impaired vagal control. We suggest, that autonomic dysfunction in individuals with chronic pain is vagally mediated, as demonstrated by decreased RMSSD. HRV may provide insights to study the time course of ANS changes mediated by the continuous experience of pain.77 It further serves as an integrative index of psychological phenomena related to the experience of pain, relevant to health-related perception and behaviors and offers new insights into pain regulatory processes.

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Chronic Pain and Heart Rate Variability in a Cross-Sectional Occupational Sample: Evidence for Impaired Vagal Control.

The vagus nerve influences the modulation of pain. Chronic pain is associated with disturbance of the descendent inhibitory pathway (DIP). Heart rate ...
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