Abstract
Objectives
Acute Epstein-Barr virus (EBV) infection is a trigger of Chronic Fatigue (CF) and Chronic Fatigue Syndrome (CFS). The aim of this cross-sectional study was to investigate pain symptoms and pressure pain thresholds in fatigued and non-fatigued adolescents six months after acute EBV-infection, and in healthy controls. This study is part of the CEBA-project (CF following acute EBV infection in adolescents).
Methods
A total of 195 adolescents (12–20 years old) that had undergone an acute EBV infection six months prior to assessment were divided into fatigued (EBV CF+) and non-fatigued (EBV CF−) cases based on questionnaire score. The EBV CF+ cases were further sub-divided according to case definitions of CFS. In addition, a group of seventy healthy controls was included. Symptoms were mapped with questionnaires. Pressure pain thresholds were measured through pressure algometry. One way ANOVA were used for between-group analyses. Linear regression analyses were used to explore associations between Pediatric Quality of Life (dependent variable), pain symptoms and other variables within the EBV (CF+) group.
Results
The EBV CF+ group had significantly higher scores for pain symptoms as compared with the EBV CF− group and healthy controls, but pressure pain threshold did not differ significantly. The number of pain symptoms as well as pain severity were strongly and independently associated with quality of life.
Conclusions
CF and CFS following acute EBV-infection in adolescents is characterized by high pain symptom burden, which in turn is associated with a decline in quality of life. Pain in CF and CFS is of considerable clinical importance, and should be a focal point for further investigation and intervention in these patient groups.
Introduction
Chronic fatigue (CF) is a common health complaint in Western countries [1]. About 20% of female and 6.5% of male adolescents report having been severely fatigued during the last month [2]. If the fatigue remains unexplained, long lasting, disabling and accompanied by other symptoms, the patient may meet the criteria for Chronic Fatigue Syndrome (CFS) [3].
The underlying pathophysiology of CF as well as CFS remains largely unknown, and there is no diagnostic biomarker. A diagnosis of CSF is made by the recognition of typical symptoms. Multiple diagnostic definitions exist; most commonly applied are the Fukuda- and Canada-definitions [4], [5], [6]. Studies suggest a prevalence of CFS at approximately 0.1–1,9% among adolescents, depending on the applied case definitions. More females than males are affected [7], [8].
Both CF and CFS are prevalent after certain viral infections. Particularly well documented is the link to mononucleosis/acute Epstein-Barr virus (EBV) infection [9], [10]. is a comprehensive prospective and cross-sectional cohort study that investigates several clinical and translational aspects of post-infectious CFCFS.consists offatigue predictors [11], [12], [13], [14], [15], [16] report to specifically addressPain is a common symptom in CF and CFS, but been scarcely covered by previous research [17]. Winger and coworkers reported a higher prevalence of severe pain and a lowered pain thresholds among adolescents with CFS [18]. Polli and coworkers found an association between exercise-induced changes in pressure pain thresholds and complement activity in individuals with CFS which was not present among healthy controls, suggesting a potential link between immune system alteration and dysfunctional endogenous pain modulation [19]. Strand and coworkers reported a higher level of pain in patients with CFS, associated with a reduced quality of life and physical functioning level [20]. Corollary, Vassend and coworkers documented a susceptibility to report fatigue symptoms in individuals with musculoskeletal pain [21]. Furthermore, research in other patient groups such as sufferers of cancer, multiple sclerosis and rheumatoid arthritis, points towards a stronger link between pain, fatigue and quality of life than previously realized and accepted [22], [23], [24], [25]. Accordingly, pdocumented commonalities between CF/CFS and chronic fatigue and chronic fatigue syndrome also have some symptoms and diagnostic criteria in common with fibromyalgia, including pain symptoms. These shared traits have been investigated in previous research [26], [27].
Thus, pain deserve increased attention in CF and CFS, and may have a significant impact on functional abilities and quality of life. The aims of the present study were to investigate pain symptoms and pressure pain threshold in CF and CFS, and to explore the relationship between pain, Quality of Life (QoL) and other disease markers. We compared pain symptoms and signs between three groups: Adolescents with CF six months after acute EBV infection (EBV CF+), adolescents without CF six months after EBV infection (EBV CF−), and healthy controls. The relationship between pain and other disease markers was explored in the EBV CF+ group only.
Materials and methods
Study design
The CEBA project (ClinicalTrial ID: NCT02335437) encompasses a prospective cohort of EBV infected adolescents with a total follow-up time of 21 months. The overall design of the CEBA project has been described elsewhere [15]. In this paper, results from the six month follow-up after the infectious event are reported. In addition, a healthy control group is included for reference. Patient inclusion was based on informed consent. Approbation was granted from The Norwegian National Committee for Ethics in Medical Research.
Participants
From March 2015 until November 2016, EBV infected individuals fulfilling the following criteria were assessed for eligibility: (1) A serological pattern indicating acute EBV infection; (2) Age between 12 and 20 years and (3) Living in the Norwegian counties of either Oslo, Akershus or Buskerud. Exclusion criteria were: (1) More than six weeks since onset of symptoms suggesting acute EBV infection; (2) Any chronic disease that needed regular use of medication; (3) Pregnancy.
At the six-month follow-up, study participants were subdivided into CF+ and CF– groups based on a sum score ≥4 or <4, respectively, on a dichotomously scored Chalder Fatigue Questionnaire (CFQ) [28], [29]. Moreover, within the CF+ group, adherence to the Fukuda and Canada definitions of CFS was assessed based upon questionnaire results (cf. below).
Healthy controls were recruited mainly by asking the already included EBV-infected individuals to bring a friend of same age and gender to the six-month follow-up encounter. In addition, a total of ten healthy adolescents were recruited from local schools.
Additional details of the recruitment, screening and inclusion procedures are described elsewhere [15].
Investigational program
Participants were invited to a one-day investigational program at the CEBA study center, Akershus University Hospital, Norway. Appointments with the EBV-infected individuals were scheduled as soon as possible after onsetdebut of symptoms (baseline), with a follow-up visit six months later. Healthy controls were seen only once. The investigational program included a clinical examination, blood sampling, autonomic cardiovascular control assessment, pressure pain threshold assessment, and questionnaire charting, and was followed by activity monitoring. The program was carried out by two researchers, in a fixed sequence for all participants. Further details of the CEBA investigational program have been described elsewhere [15].
Questionnaires
A composite questionnaire used in this study include the following validated instruments: Brief Pain Inventory (BPI), Pediatric Quality of Life (PedsQL), Chalder Fatigue Questionnaire (CFQ), The CDC CFS symptom inventory, and Hospital Anxiety and Depression Scale (HADS). In addition, the questionnaire assessed clinical symptoms of EBV infection (such as fever/chills, sore throat, tender lymphatic nodes), pain symptoms, symptoms pertaining to different case definition of CFS, and demographic background variables.
Brief Pain Inventory (BPI) is a validated questionnaire for assessing pain severity [30]. The scores on four different items using ten-point Likert scales are reported in this study. Additionally, these four items were used to compute a pain severity sum score, ranging from 0 (no pain) to 40 (worst pain).
The Pediatric Quality of Life Inventory (PedsQL) charts quality of life through 23 items scored on five-point Likert scales [31]. It is translated and validated for the Norwegian population. In the present study, the total mean score is applied; range is from 0 (lowest QoL) to 100 (highest QoL).
Chalder Fatigue Questionnaire (CFQ) consists of 11 items, each scored on a Likert scale from 0 to 3, giving a total score range from 0 to 33; higher scores imply more fatigue. [32], [33]. Fatigue caseness was defined as a CFQ total dichotomous score of 4 or higher, where each item was scored 0-0-1-1.
A modified version of the CDC CFS symptom inventory charts 24 fatigue and illness-related symptoms during the preceding month, including all case defining symptoms of CFS; items are score on five-point Likert scales from “never/rarely present” to “present all of the time” [34], [35]. The present study reports scores of post-exertional malaise, headache, muscle pain, multi-joint pain, and abdominal pain, as well as a pain symptom sum score based on the four pain items, ranging from 4 (no pain) to 20 (pain all the time) [36].
The Hospital Anxiety and Depression Scale (HADS) is a validated questionnaire for detecting symptoms of anxiety and depression [37], [38]. It consists of 14 items scored on four-point Likert scales; total sum score ranges from 0 (no symptoms) to 42 (most severe symptoms) [39].
Pressure algometry
Pressure Pain Threshold (PPT) is defined as the minimum intensity of a stimulus that is perceived as painful [40]. It is a reliable test for hyperalgesia [18], [41]. In the present study, PPT was assessed by gradually applying increasing pressure to six predefined areas, using the Commander™ Algometer (JTECH Medical, Midvale, USA). Pressure points were the third finger’s cuticles, trapezius muscle and supraspinatus muscle. Each area was examined on both right and left side. Pressure stimuli were applied twice to each spot. Participants were asked to indicate the first sensation of pain during increasing pressure. Final values are the bilateral average scores across both trials.
Activity monitoring
Daily physical activity was monitored during seven consecutive days using the activPAL accelerometer device (PAL Technologies, Glasgow, Scotland). The accelerometer was attached at the thigh in anterior midline with waterproof, adhesive tape. The activPAL provide reliable data on both steps and position [42].
Biomarkers
EBV load was measured through detection of microbial DNA from EBV performed by real-time polymerase chain reaction in whole blood. Frozen serum samples were used for the high-sensitive C-reactive protein (hsCRP) assay (Cobas c702, Roche Diagnostics, Indianapolis, IN). Plasma norepinephrine was analyzed through high-performance liquid chromatography (Agilent Technologies, Santa Clara, CA) with a reversed-phase C-18 column (Chromsystem, München, Germany) and electrochemical detector (Antec, Leyden Decade II SCC, Zoeterwoude, The Netherlands) using a commercial kit from Chromsystems. Further information on the biomarkers investigated in this study are provided in detail elsewhere [14].
Autonomic cardiovascular assessment
The Task Force Monitor® (Model 3040i, CNSystems Medizintechnic, Graz, Austria) is a combined hardware and software device for noninvasive continuous recording of cardiovascular variables [43].
In the present study, ECG recordings during 5 min supine rest were used to compute heart rate variability (HRV) indices, applying an adaptive autoregressive model [44]. Power was calculated in the Low Frequency (LF) range (0.05 to 0.17 Hz), and High Frequency (HF) range (0.17 to 0.4 Hz); vagal (parasympathetic) autonomic nervous activity is the main contributor to HF variability, whereas both vagal and sympathetic activity contribute to LF variability.
Statistical analyses
Variables are reported with median (interquartile range) or mean (standard deviation) depending on the distribution, and with 95% confidences intervals. Differences between the three groups (EBV CF+, EBV CF−, and healthy controls) were investigated using one-way ANOVA. For p-values<0.1, post hoc comparisons between the EBV CF+ and EBV CF− groups were performed with Student t- test; the final p-values were adjusted for group differences in sex and HADS score applying linear regression analyses.
When comparing the entire EBV CF+ group with the subgroups adhering to the Fukuda and Canada diagnostic criteria, respectively, differences were analyzed by comparing confidence intervals of the central estimates.
For exploration of the relationship between pain, quality of life and other disease markers in the EBV CF+ group, bivariate linear regression analyses followed by multiple linear regression modeling was applied. When appropriate, variables were transformed logarithmically before modeling in order to obtain an approximated normal distribution.
The SPSS statistical software (IBM SPSS 25 inc., Chicago, IL) was used to carry out all statistical analyses. As a general analytic strategy, 5% level of significance was applied. We did not adjust p-values for test multiplicity. considered missing data were not impute.
Results
A total of 895 adolescents were assessed for eligibility in the CEBA project, and a total of 200 were included at baseline [15]. Additional five participants were lost to follow-up during the first six months, leaving 195 cases for analyses in the present sub-study; 91 (47%) of them adhered to the case definition of chronic fatigue (EBV CF+), whereas 104 (53%) were classified as non-fatigue cases (EBV CF−). A total of 26 participants (29%) adhered to the Fukuda-definition of CFS [4], whereas 19 individuals (21%) adhered to the Canada-definition [5]. In addition, 70 healthy adolescents were included for reference.
As compared with the EBV CF− group, the EBV CF+ group contained more females and had higher levels of plasma norepinephrine and serum C-reactive protein (CRP), higher scores for clinical symptoms and lower quality of life (QoL) (Table 1).
Background characteristics.
EBV-group (n=195). 6 months after acute infection | Healthy controls (n=70) | ||||
---|---|---|---|---|---|
EBV (CF+) (n=91) | EBV (CF−) (n=104) | p-Value | |||
Constitutional | |||||
Sex – no. (%) | |||||
Male | 24 (26) | 44 (42) | 0.020 | 26 (37) | |
Female | 67 (74) | 60 (58) | 44 (63) | ||
Age, years – mean (SD) | 17.4 (1.5) | 17.4 (1.7) | 0.780 | 17.0 (1.8) | |
BMI, kg/m2 – mean (SD) | 22.1 (2.8) | 22.2 (2.5) | 0.666 | 21.5 (3.1) | |
Biomarkers | |||||
Epstein-Barr Virus (EBV) load, copies in blood – no. (%) | |||||
Negative (<160) | 44 (51) | 38 (37) | 0.123 | 60 (86) | |
Low (1600 to 2000) | 26 (30) | 35 (34) | 8 (11) | ||
Moderate/high (>2000) | 16 (19) | 29 (28) | 2 (3) | ||
Serum high sensitive CRP, mg/L – median (IQR) | 0.48 (1.25) | 0.43 (0.62) | 0.043 | 0.56 (0.41) | |
Plasma Norepinephrine, pmol/L – mean (SD) | 1420 (692) | 1113 (659) | 0.002 | 1252 (567) | |
LF-RRI, ms2 – median (IQR) | 848 (1138) | 986 (1236) | 0.195 | 779 (871) | |
HF-RRI, ms2 – median (IQR) | 1552 (1877) | 1270 (1924) | 0.855 | 1255 (1492) | |
Clinical symptoms | |||||
Chalder Fatigue Questionnaire (CFQ), total score – median (IQR) | 19.0 (5.0) | 11.0 (2.0) | <0.001 | 11.0 (5.0) | |
Post-exertional malaise, score – mean (SD) | 2.9 (1.1) | 1.6 (0.6) | <0.001 | 1.7 (0.7) | |
Hospital anxiety and depression symptoms (HADS), total score – mean (SD) | 13.4 (6.3) | 8.0 (5.3) | <0.001 | 10.6 (4.6) | |
Function | |||||
Steps per day, number – mean (SD) | 8710 (3872) | 9329 (3019) | 0.293 | 10094 (4149) | |
Pediatric qualilty of life (PedsQL), total score – mean (SD) | 67 (17) | 89 (12) | <0.001 | 85 (10) |
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SD, Standard deviation; IQR, Interquartile range; CF, Chronic fatigue; CRP, C-reactive protein; HF-RRI, High-Frequency Variability of RR-Interval; LF-RRI, Low-Frequency Variability of the RR-Interval.
EBV CF+ individuals reported significantly more pain symptoms in all charted body areas (headache, muscle pain, multi-joint pain and abdominal pain) as well as a higher pain symptoms sum score, compared with the EBV CF− group and healthy controls (Table 2). Also, pain severity sum score and two related subscores (pain average and pain now) were significantly elevated in the EBV CF+ group. Pressure algometry did not reveal any significant differences in pressure pain threshold between the three groups.
Cross-sectional comparison of clinical symptoms and signs across all groups.
EBV (CF+) (n=91) | EBV (CF−) (n=104) | Healthy controls (n=70) | p-value (across all groups) | p-value EBV (CF+) vs EBV (CF-) | Adjusted* p-value EBV (CF+) vs EBV (CF-) | |
---|---|---|---|---|---|---|
Symptoms | ||||||
Headache, score – mean (SD) | 2.9 (1.2) | 1.8 (1.1) | 1.8 (1.0) | <0.001 | <0.001 | <0.001 |
95% Confidence interval | 2.6–3.1 | 1.6–2.0 | 1.6–2.1 | |||
Muscle pain, score – mean (SD) | 2.1 (1.1) | 1.4 (0.7) | 1.5 (0.6) | <0.001 | <0.001 | 0.007 |
95% Confidence interval | 1.8–2.3 | 1.2–1.5 | 1.3–1.7 | |||
Multi-joint pain, score – mean (SD) | 2.0 (1.3) | 1.3 (0.8) | 1.2 (0.4) | <0.001 | <0.001 | 0.034 |
95% Confidence interval | 1.7–2.3 | 1.1–1.4 | 1.1–1.3 | |||
Abdominal pain, score – mean (SD) | 2.2 (1.0) | 1.5 (0.8) | 1.5 (0.7) | <0.001 | <0.001 | 0.009 |
95% Confidence interval | 2.0–2.5 | 1.3–1.7 | 1.3–1.6 | |||
Pain symptoms, sum score – mean (SD) | 9.1 (3.5) | 6.0 (2.3) | 6.0 (1.8) | <0.001 | <0.001 | <0.001 |
95% Confidence interval | 8.3–10.0 | 5.5–6.5 | 5.6–6.4 | |||
Pain worst, score – mean (SD) | 4.7 (2.4) | 3.3 (2.2) | 3.4 (1.7) | <0.001 | <0.001 | 0.061 |
95% Confidence interval | 4.1–5.2 | 2.8–3.7 | 3.0–3.8 | |||
Pain least, score – mean (SD) | 1.6 (1.0) | 1.2 (0.4) | 1.2 (0.5) | 0.004 | 0.008 | 0.155 |
95% Confidence interval | 1.4–1.9 | 1.1–1.3 | 1.0–1.3 | |||
Pain average, score – mean (SD) | 3.2 (1.6) | 2.0 (1.3) | 2.2 (1.2) | <0.001 | <0.001 | 0.004 |
95% Confidence interval | 2.8–3.6 | 1.7–2.3 | 1.9–2.5 | |||
Pain now, score – mean (SD) | 2.1 (1.3) | 1.3 (0.7) | 1.3 (0.7) | <0.001 | <0.001 | 0.016 |
95% Confidence interval | 1.8–2.4 | 1.1–1.4 | 1.1–1.5 | |||
Pain severity, sum score – mean (SD) | 11.6 (5.3) | 7.7 (3.6) | 8.1 (3.2) | <0.001 | <0.001 | 0.005 |
95% Confidence interval | 10.4–12.8 | 6.9–8.5 | 7.3–8.9 | |||
Signs | ||||||
Finger nail, N/cm2 – mean (SD) | 11.8 (6.9) | 10.7 (4.2) | 11.6 (3.5) | 0.277 | ||
95% Confidence interval | 10.3–13.2 | 9.9–11.5 | 10.8–12.5 | |||
Trapezius muscle, N/cm2 – mean (SD) | 5.3 (3.6) | 5.6 (3.0) | 4.8 (2.1) | 0.275 | ||
95% Confidence interval | 4.5–6.0 | 5.0–6.2 | 4.3–5.3 | |||
Supraspinatus muscle, N/cm2 – mean (SD) | 7.4 (4.1) | 7.8 (4.2) | 6.9 (2.9) | 0.537 | ||
95% Confidence interval | 6.5–8.2 | 7.0–8.6 | 6.2–7.6 |
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*Adjusted for group differences in sex and HADS-score at 6 months applying multiple linear regression modeling. P-values≤0.05 in the right column are shown in bold for clarity. Statistical tests across the EBV (CF−) and EBV (CF+) groups (second right column) were only carried out if the p-value across all groups were ≤0.1. A total of 33 statistical tests were performed. According to a Bonferroni correction, the level of significance should be set at p=0.05/33≈0.002. SD, Standard deviation; CF, Chronic fatigue; EBV, Epstein-Barr Virus.Bold numbers indicate a result regarded as significant.
The subgroup of EBV CF+ with a confirmed diagnosis of CFS based on either the Fukuda or Canada diagnostic definitions, displayed higher symptoms scores than the remaining individuals in the EBV CF+ group (Table 3). Also, individuals adhering to the Canada criteria tended to have a slightly lowered pressure pain threshold, as hypothesized at the onset of this study.
Cross-sectional comparison of clinical symptoms and signs across cases of chronic fatigue (EBV (CF+)), cases of chronic fatigue syndrom according to the Fukuda-definition (EBV (CF+ Fu+)), and cases of chronic fatigue syndrome according to the Canada-definition (EBV (CF+Ca+)). Recovered EBV patients (EBV (CF‒)) and healthy controls are shown for comparison.
EBV (CF+) (n=91) | EBV (CF+Fu+) (n=26) | EBV (CF+Ca+) (n=19) | EBV (CF−) (n=104) | Healthy controls (n=70) | |
---|---|---|---|---|---|
Symptoms | |||||
Headache, score – mean (SD) | 2.9 (1.2) | 3.5 (1.2) | 3.7 (1.1) | 1.8 (1.1) | 1.8 (1.0) |
95% Confidence interval | 2.6–3.1 | 3.0–4.0 | 3.1–4.2 | 1.6–2.0 | 1.6–2.1 |
Muscle pain, score – mean (SD) | 2.1 (1.1) | 2.5 (1.1) | 2.6 (1.2) | 1.4 (0.7) | 1.5 (0.6) |
95% Confidence interval | 1.8–2.3 | 2.0–2.9 | 2.0–3.2 | 1.2–1.5 | 1.3–1.7 |
Multi-joint pain, score – mean (SD) | 2.0 (1.3) | 2.7 (1.3) | 2.7 (1.3) | 1.3 (0.8) | 1.2 (0.4) |
95% Confidence interval | 1.7–2.3 | 2.1–3.2 | 2.0–3.3 | 1.1–1.4 | 1.1–1.3 |
Abdominal pain, score – mean (SD) | 2.2 (1.0) | 2.6 (1.0) | 2.7 (1.0) | 1.5 (0.8) | 1.5 (0.7) |
95% Confidence interval | 2.0–2.5 | 2.2–3.1 | 2.2–3.2 | 1.3–1.7 | 1.3–1.6 |
Pain symptoms, sum score – mean (SD) | 9.1 (3.5) | 11.3 (2.7) | 11.6 (2.5) | 6.0 (2.3) | 6.0 (1.8) |
95% Confidence interval | 8.3–10.0 | 10.2–12.4 | 10.4–12.8 | 5.5–6.5 | 5.6–6.4 |
Pain worst, score – mean (SD) | 4.7 (2.4) | 6.2 (1.3) | 6.0 (1.7) | 3.3 (2.2) | 3.4 (1.7) |
95% Confidence interval | 4.1–5.2 | 5.6–6.7 | 5.1–6.9 | 2.8–3.7 | 3.0–3.8 |
Pain least, score – mean (SD) | 1.6 (1.0) | 2.0 (1.3) | 1.9 (1.3) | 1.2 (0.4) | 1.2 (0.5) |
95% Confidence interval | 1.4–1.9 | 1.4–2.5 | 1.3–2.6 | 1.1–1.3 | 1.0–1.3 |
Pain average, score – mean (SD) | 3.2 (1.6) | 4.1 (1.2) | 4.1 (1.3) | 2.0 (1.3) | 2.2 (1.2) |
95% Confidence interval | 2.8–3.6 | 3.6–4.6 | 3.5–4.8 | 1.7–2.3 | 1.9–2.5 |
Pain now, score – mean (SD) | 2.1 (1.3) | 3.1 (1.5) | 3.2 (1.5) | 1.3 (0.7) | 1.3 (0.7) |
95% Confidence interval | 1.8–2.4 | 2.5–3.7 | 2.4–3.9 | 1.1–1.4 | 1.1–1.5 |
Pain severity, sum score – mean (SD) | 11.6 (5.3) | 15.3 (4.0) | 15.2 (4.9) | 7.7 (3.6) | 8.1 (3.2) |
95% Confidence interval | 10.4–12.8 | 13.6–17.0 | 12.8–17.7 | 6.9–8.5 | 7.3–8.9 |
Signs | |||||
Finger nail, N/cm2 – mean (SD) | 11.8 (6.9) | 10.3 (3.8) | 9.5 (3.6) | 10.7 (4.2) | 11.6 (3.5) |
95% Confidence interval | 10.3–13.2 | 8.7–11.8 | 7.8–11.3 | 9.9–11.5 | 10.8–12.5 |
Trapezius muscle, N/cm2 – mean (SD) | 5.3 (3.6) | 4.5 (2.4) | 4.3 (1.9) | 5.6 (3.0) | 4.8 (2.1) |
95% Confidence interval | 4.5–6.0 | 3.6–5.5 | 3.4–5.2 | 5.0–6.2 | 4.3–5.3 |
Supraspinatus muscle, N/cm2 – mean (SD) | 7.4 (4.1) | 6.7 (3.0) | 6.5 (2.9) | 7.8 (4.2) | 6.9 (2.9) |
95% Confidence interval | 6.5–8.2 | 5.5–7.9 | 5.1–7.9 | 7.0–8.6 | 6.2–7.6 |
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SD, Standard deviation; CF, Chronic fatigue; EBV, Epstein-Barr Virus; Fu, Fukuda-definition of Chronic Fatigue Syndrome; Ca, Canada-definition of Chronic Fatigue Syndrome.
Both pain symptoms sum score and pain severity sum score were independently associated with lower quality of life in the EBV CF+ group, and show a stronger impact on quality of life than the symptom of fatigue (Table 4). Relevant biomarkers, known to be affected in EBV CF+ individuals [14], do not impact quality of life.
Linear regression analyses of associations between Pediatric Quality of Life (dependent variable), pain symptoms and other variables within the EBV (CF+) group.
Bivariate linear regression | Multiple linear regression | ||||
---|---|---|---|---|---|
Linear regression coefficient B | p-value | Linear regression coefficient B | p-value | Δ R2 | |
Pain symtoms | |||||
Pain symptoms, sum score | −3.5 | <0.001 | −1.3 | 0.007 | 0.03 |
95% Confidence interval | −4.3 to −2.8 | −2.2 to −0.4 | |||
Pain severity, sum score | −2.2 | <0.001 | −0.6 | 0.031 | 0.02 |
95% Confidence interval | −2.7 to −1.6 | −1.1 to −0.1 | |||
Other clinical symptoms | |||||
Chalder Fatigue Questionnaire (CFQ), total score | −2.0 | <0.001 | 0.05 | 0.877 | <0.01 |
95% Confidence interval | −2.8 to −1.2 | −0.5 to 0.6 | |||
Post-exertional malaise, score | −7.5 | <0.001 | −2.8 | 0.003 | 0.03 |
95% Confidence interval | −9.9 to −5.0 | −4.7 to −1.0 | |||
Hospital anxiety and depression symptoms (HADS), total score | −2.0 | <0.001 | −1.1 | <0.001 | 0.08 |
95% Confidence interval | −2.4 to −1.6 | −1.5 to −0.6 | |||
Constitutional | |||||
Sex | −6.0 | 0.158 | |||
95% Confidence interval | −14.5 to 2.4 | ||||
Age, years | 1.1 | 0.395 | |||
95% Confidence interval | −1.4 to 3.6 | ||||
BMI, kg/m2 | 0.1 | 0.890 | |||
95% Confidence interval | −1.2 to 1.4 | ||||
Biomarkers | |||||
Epstein-Barr Virus (EBV) load, copies in blood | 0.8 | 0.846 | |||
95% Confidence interval | −7.2 to 8.7 | ||||
Serum high sensitive CRP, mg/L | −10.4 | 0.284 | |||
95% Confidence interval | −29.7 to 8.8 | ||||
Plasma Norepinephrine, pmol/L | −0.5 | 0.895 | |||
95% Confidence interval | −7.9 to 6.9 | ||||
LF-RRI, ms2 | 1.6 | 0.403 | |||
95% Confidence interval | −2.2 to 5.3 | ||||
HF-RRI, ms2 | 2.0 | 0.267 | |||
95% Confidence interval | −1.6 to 5.5 | ||||
Explained variance (R 2 ) of multiple regression model | 0.76 |
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Of note, some continuous variables were ln-transformed prior to analyses in order to obtain an approximate normal distribution. Thus, the linear regression coefficient B is not immediately informative of the linear associations between non-transformed variables. The Δ R2-value is the change in explained variance (R2) when a single variable is removed from the model. SD, Standard deviation; CF, Chronic fatigue; CRP, C-reactive protein; HF-RRI, High-Frequency Variability of RR-Interval, LF-RRI, Low-Frequency Variability of the RR-Interval. Bold numbers indicate a result regarded as significant.
Discussion
The most important findings of the present study were: (1) Adolescents with CF following acute EBV-infection experienced more pain symptoms and more severe pain than non-fatigued controls; (2) Pain exerted a strong, negative impact on quality of life among CF sufferers, more than the symptom of fatigue itself. and (3) Patients with CFS tended to have even more severe symptoms, but were otherwise similar to the CF group.
Taken together, these results emphasize the burden of CF and CFS in adolescents.
There is a striking discrepancy between the significantly elevated scores for pain symptoms and pain severity in the EBV CF+ group as compared to the EBV CF− group, and the lack of between-group differences regarding pressure algometry. This observation suggests that the peripheral nociceptors are not overly activated in the EBV CF+ group. Accordingly, the elevated experience of pain likely has a more central origin in CF+ individuals. The discrepancy between subjective clinical symptoms and objective signs in patients with CF, corroborates findings from other areas; for instance, there is an analogous discrepancy between symptoms and signs of inflammation [14]. This phenomenon deserves attention in further research.
In a study of CFS adolescents [18], Winger and co-workers reported a lowered PPT as well as more pain symptom and pain severity in the patient group. [45], [46]In the present study, we did observe slightly lowered PPTs in the subgroup of EBV CF+ participants adhering to the Canada diagnostic criteria of CFS. However, the differences were subtle, and smaller than the ones reported by Winger and co-workersOf note, in the latter study, mean disease duration among the participants was 21 months, whereas the participants in the present study were investigated only six months after the precipitating event (acute EBV infection). Hence, a lowered PPT might be a feature of a long-lasting disease process, eventually related to consequences of chronicity such as inactivity, rather than a primary feature of CFS.
The number of pain symptoms, as well as the pain severity, were both independently associated to a low quality of life in patients with CF after EBV-infection. However, the study design does not allow us to draw causal interferences. Intriguingly, the symptom of fatigue itself did not affect quality of life in the multiple linear regression modeling. One explanation might be that pain symptoms contribute to both a decline in quality of life and increased fatigue. A thirdOther factors associated with poor quality of life include psychological symptoms such as anxiety and depression. Such symptoms may contribute to a spiral of negative thinking, worsening pain symptoms. In turn, this may feed back towards an increase in psychological symptom load [47], [48], [49]. Anyhow, acknowledging the relevance of pain symptoms in a clinical setting may be key in a proper handling of CF and CFS [50].
Selected biomarkers, known to be slightly affected in EBV CF+ individuals [14], show no impact on quality of life. Thus, these biomarkers may not help to explain the lower quality of life in the EBV CF+ group, compared to EBV CF− patients and healthy controls.
Strengths and limitations
Strengths of this study include the large number of participants in the CEBA project, few participants lost to follow up, and well-defined inclusion and exclusion criteria. A selection bias of importance seems unlikely, as exclusion of otherwise eligible participants was mainly due to time limits after onset of symptoms. Therefore, generalization of study results appears reasonable.
The healthy control group mainly consisted of acquaintances of the initial study participants, namely recent EBV-infected individuals. This may have led to a slight selection bias in the control group.
Our only measure of objective pain was through pressure algometry. Other methods of pain tolerance, such as electrical or thermal stimulators, could have been applied for a more thorough assessment. Additionally,.
Most of the participants in the EBV CF+ group did not meet the CFS diagnosis through the Fukuda- or Canada definitions. Thus, our results and conclusions have less power for these subgroups.
Conclusion
CF and CFS following acute EBV-infection in adolescents is characterized by high pain symptom burden, which in turn is associated with a decline in quality of life. Thus, pain in CF and CFS is of considerable clinical importance, and should be a focal point for further investigation and intervention in these patient groups.
Funding source: Health South-East Hospital Trust
Acknowledgments
We thank Stine Andersen Ness, Dept. of Pediatrics and Adolescent Health, Akershus University Hospital for invaluable secretary assistance; Truls Leegaard, Dept. of Microbiology and Infection Control, Akershus University Hospital, Lørenskog, Norway and Trygve Tjade, Fürst Medical Laboratory, Lørenskog, Norway for administering EBV serology analyses; Kristin Godang, Section of Specialized Endocrinology, Dept. of Endocrinology, Oslo University Hospital, Norway, for laboratory analyses of norepinephrine; and Eva Skovlund, Dept. of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway for advices on statistical analyses.
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Research funding: This study was funded by the Health South-East Hospital Trust, Norway.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Conflict of interest: Authors state no conflict of interest.
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Informed consent: Informed consent has been obtained from all individuals included in this study.
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Ethical approval: The research related to human use complies with all the relevant national regulations, institutional policies and was performed in accordance with the tenets of the Helsinki Declaration, and has been approved by the authors’ institutional review board or equivalent committee.
References
1. Pawlikowska, T, Chalder, T, Hirsch, SR, Wallace, P, Wright, DJ, Wessely, SC. Population based study of fatigue and psychological distress. BMJ 1994;308:763–6. https://doi.org/10.1136/bmj.308.6931.763.10.1136/bmj.308.6931.763Search in Google Scholar PubMed PubMed Central
2. Crawley, E. The epidemiology of chronic fatigue syndrome/myalgic encephalitis in children. Arch Dis Child 2014;99:171–4. https://doi.org/10.1136/archdischild-2012-302156.10.1136/archdischild-2012-302156Search in Google Scholar PubMed
3. Medicine. CotDCfMECFSBotHoSPIo. Beyond Myalgic Encephalomyelitis/chronic fatigue syndrome (Redefining an Illness). Washington, DC: The National Academies Press; 2015.Search in Google Scholar
4. Fukuda, K, Straus, SE, Hickie, I, Sharpe, MC, Dobbins, JG, Komaroff, A. The chronic fatigue syndrome: a comprehensive approach to its definition and study. International chronic fatigue syndrome study group. Ann Intern Med 1994;121:953–9. https://doi.org/10.7326/0003-4819-121-12-199412150-00009.10.7326/0003-4819-121-12-199412150-00009Search in Google Scholar PubMed
5. Carruthers, BM, Jain, AK, De Meirleir, KL, Klimas, NG, Lerner, AM, Bested, AC, et al. Myalgic encephalomyelitis/chronic fatigue syndrome: clinical working case definition, diagnostic and treatment protocols. J Chronic Fatigue Syndr 2003;11:7–116. https://doi.org/10.1300/j092v11n01_02.10.1300/J092v11n01_02Search in Google Scholar
6. Sharpe, MC, Archard, LC, Banatvala, JE, Borysiewicz, LK, Clare, AW, David, A, et al. A report--chronic fatigue syndrome: guidelines for research. J R Soc Med 1991;84:118–21.10.1177/014107689108400224Search in Google Scholar PubMed PubMed Central
7. Jordan, KM, Huang, C-F, Jason, LA, Richman, J, Mears, CJ, McCready, W, et al. Pediatric chronic fatigue syndrome in a community-based sample. J Chronic Fatigue Syndr 2006;13:75–8.10.1300/J092v13n02_04Search in Google Scholar
8. Werker, CL, Nijhof, SL, van de Putte, EM. Clinical practice: chronic fatigue syndrome. Eur J Pediatr 2013;172:1293–8. https://doi.org/10.1007/s00431-013-2058-8.10.1007/s00431-013-2058-8Search in Google Scholar PubMed
9. Ian Hickie, TD, Wakefield, D, Vollmer-Conna, U, Cameron, B, Vernon, SD, Reeves, WC, et al. Post-infective and chronic fatigue syndromes precipitated by viral and non-viral pathogens: prospective cohort study. BMJ 2006;333:1–6 https://doi.org/10.1136/bmj.38933.585764.ae.10.1136/bmj.38933.585764.AESearch in Google Scholar PubMed PubMed Central
10. Tobi, M, Ravid, Z, Chowers, I, Feldman-Weiss, V, Michaeli, Y, Ben-Chetrit, E, et al. Prolonged atypical illness associated with serological evidence of persistent Epstein-Barr virus infection. Lancet 1982;1:61–4. https://doi.org/10.1016/s0140-6736(82)90210-0.10.1016/S0140-6736(82)90210-0Search in Google Scholar PubMed
11. Ceba – chronic fatigue following acute Epstein-Barr virus infection on adolescents, Protocol; 2014 https://wwwahusno/seksjon/forskning/Documents/Forskningsgrupper/Barne-%20og%20ungdomsklinikken/Paedia/Forskningsprotokollpdf.Search in Google Scholar
12. Statistical analysis plan – CEBA; 2014. https://wwwahusno/seksjon/forskning/Documents/Forskningsgrupper/Barne-%20og%20ungdomsklinikken/Paedia/Statistisk%20analyseplanpdf [Accessed 16 Jan 2018].Search in Google Scholar
13. Statistical analysis plan – CEBA part 2; 2015. https://wwwahusno/seksjon/forskning/Documents/Forskningsgrupper/Barne-%20og%20ungdomsklinikken/Paedia/Statistisk%20analyseplan%20del%202pdf [Accessed 16 Jan 2018].Search in Google Scholar
14. Kristiansen, MS, Stabursvik, J, O’Leary, EC, Pedersen, M, Asprusten, TT, Leegaard, T, et al. Clinical symptoms and markers of disease mechanisms in adolescent chronic fatigue following Epstein-Barr virus infection: an exploratory cross-sectional study. Brain Behav Immun 2019;80:551–63. https://doi.org/10.1016/j.bbi.2019.04.040.10.1016/j.bbi.2019.04.040Search in Google Scholar PubMed
15. Pedersen, M, Asprusten, TT, Godang, K, Leegaard, TM, Osnes, LT, Skovlund, E, et al. Predictors of chronic fatigue in adolescents six months after acute Epstein-Barr virus infection: a prospective cohort study. Brain Behav Immun 2019;75:94–100. https://doi.org/10.1016/j.bbi.2018.09.023.10.1016/j.bbi.2018.09.023Search in Google Scholar PubMed
16. Pedersen, M, Asprusten, TT, Godang, K, Leegaard, TM, Osnes, LT, Skovlund, E, et al. Fatigue in Epstein-Barr virus infected adolescents and healthy controls: a prospective multifactorial association study. J Psychosom Res 2019;121: 46–59. https://doi.org/10.1016/j.jpsychores.2019.04.008.10.1016/j.jpsychores.2019.04.008Search in Google Scholar PubMed
17. Wyller, VBB. Pain is common in chronic fatigue syndrome – current knowledge and future perspectives. Scand J Pain 2019;19: 5–8.10.1515/sjpain-2018-2007Search in Google Scholar PubMed
18. Winger, A, Kvarstein, G, Wyller, VB, Sulheim, D, Fagermoen, E, Småstuen, MC, et al. Pain and pressure pain thresholds in adolescents with chronic fatigue syndrome and healthy controls: a cross-sectional study. BMJ Open 2014;4:e005920. https://doi.org/10.1136/bmjopen-2014-005920.10.1136/bmjopen-2014-005920Search in Google Scholar PubMed PubMed Central
19. Polli, A, Van Oosterwijck, J, Meeus, M, Lambrecht, L, Nijs, J, Ickmans, K. Exercise-induce hyperalgesia, complement system and elastase activation in myalgic encephalomyelitis/chronic fatigue syndrome – a secondary analysis of experimental comparative studies. Scand J Pain 2019;19:183–92.10.1515/sjpain-2018-0075Search in Google Scholar PubMed
20. Strand, EB, Mengshoel, AM, Sandvik, L, Helland, IB, Abraham, S, Nes, LS. Pain is associated with reduced quality of life and functional status in patients with myalgic encephalomyelitis/chronic fatigue syndrome. Scand J Pain 2019;19:61–72. https://doi.org/10.1515/sjpain-2018-0095.10.1515/sjpain-2018-0095Search in Google Scholar PubMed
21. Vassend, O, Røysamb, E, Nielsen, CS, Czajkowski, NO. Fatigue symptoms in relation to neuroticism, anxiety-depression, and musculoskeletal pain. A longitudinal twin study. PLoS ONE 2018;13:e0198594. https://doi.org/10.1371/journal.pone.0198594.10.1371/journal.pone.0198594Search in Google Scholar PubMed PubMed Central
22. Brown, LF, Kroenke, K. Cancer-related fatigue and its associations with depression and anxiety: a systematic review. Psychosomatics 2009;50:440–7. https://doi.org/10.1016/s0033-3182(09)70835-7.10.1016/S0033-3182(09)70835-7Search in Google Scholar
23. Arewasikporn, A, Turner, AP, Alschuler, KN, Hughes, AJ, Ehde, DM. Cognitive and affective mechanisms of pain and fatigue in multiple sclerosis. Health Psychol 2018;37:544–52. https://doi.org/10.1037/hea0000611.10.1037/hea0000611Search in Google Scholar PubMed PubMed Central
24. Geenen, R, Dures, E. A biopsychosocial network model of fatigue in rheumatoid arthritis: a systematic review. Rheumatology (Oxford) 2019;58:v10–21. https://doi.org/10.1093/rheumatology/kez403.10.1093/rheumatology/kez403Search in Google Scholar PubMed PubMed Central
25. Gold, JI, Mahrer, NE, Yee, J, Palermo, TM. Pain, fatigue, and health-related quality of life in children and adolescents with chronic pain. Clin J Pain 2009;25:407–12. https://doi.org/10.1097/ajp.0b013e318192bfb1.10.1097/AJP.0b013e318192bfb1Search in Google Scholar PubMed PubMed Central
26. Norris, T, Deere, K, Tobias, JH, Crawley, E. Chronic fatigue syndrome and chronic widespread pain in adolescence: population birth cohort study. J Pain 2017;18:285–94. https://doi.org/10.1016/j.jpain.2016.10.016.10.1016/j.jpain.2016.10.016Search in Google Scholar PubMed PubMed Central
27. Clauw, DJ, Chrousos, GP. Chronic pain and fatigue syndromes: overlapping clinical and neuroendocrine features and potential pathogenic mechanisms. Neuroimmunomodulation 1997;4:134–53. https://doi.org/10.1159/000097332.10.1159/000097332Search in Google Scholar PubMed
28. Cella, M, Chalder, T. Measuring fatigue in clinical and community settings. J Psychosom Res 2010;69:17–22. https://doi.org/10.1016/j.jpsychores.2009.10.007.10.1016/j.jpsychores.2009.10.007Search in Google Scholar PubMed
29. White, PD, Goldsmith, KA, Johnson, AL, Potts, L, Walwyn, R, DeCesare, JC, et al. Comparison of adaptive pacing therapy, cognitive behaviour therapy, graded exercise therapy, and specialist medical care for chronic fatigue syndrome (PACE): a randomised trial. Lancet 2011;377:823–36. https://doi.org/10.1016/s0140-6736(11)60096-2.10.1016/S0140-6736(11)60096-2Search in Google Scholar PubMed PubMed Central
30. Klepstad, P, Loge, JH, Borchgrevink, PC, Mendoza, TR, Cleeland, CS, Kaasa, S. The Norwegian brief pain inventory questionnaire: translation and validation in cancer pain patients. J Pain Symptom Manage 2002;24:517–25. https://doi.org/10.1016/s0885-3924(02)00526-2.10.1016/S0885-3924(02)00526-2Search in Google Scholar
31. Reinfjell, T, Diseth, TH, Veenstra, M, Vikan, A. Measuring health-related quality of life in young adolescents: reliability and validity in the Norwegian version of the Pediatric Quality of Life Inventory 4.0 (PedsQL) generic core scales. Health Qual Life Out 2006;4:347–57 https://doi.org/10.1186/1477-7525-4-61.10.1186/1477-7525-4-61Search in Google Scholar PubMed PubMed Central
32. Chalder, T, Berelowitz, G, Pawlikowska, T, Watts, L, Wessely, S, Wright, D, et al. Development of a fatigue scale. J Psychosom Res 1993;37:147–53. https://doi.org/10.1016/0022-3999(93)90081-p.10.1016/0022-3999(93)90081-PSearch in Google Scholar
33. Loge, JH, Ekeberg, O, Kaasa, S. Fatigue in the general Norwegian population: normative data and associations. J Psychosom Res 1998;45:53–65. https://doi.org/10.1016/s0022-3999(97)00291-2.10.1016/S0022-3999(97)00291-2Search in Google Scholar
34. Wagner, D, Nisenbaum, R, Heim, C, Jones, JF, Unger, ER, Reeves, WC. Psychometric properties of the CDC symptom inventory for assessment of chronic fatigue syndrome. Popul Health Metr 2005;3:8 https://doi.org/10.1186/1478-7954-3-8.10.1186/1478-7954-3-8Search in Google Scholar PubMed PubMed Central
35. Sulheim, D, Fagermoen, E, Winger, A, Andersen, AM, Godang, K, Muller, F, et al. Disease mechanisms and clonidine treatment in adolescent chronic fatigue syndrome: a combined cross-sectional and randomized clinical trial. JAMA Pediatr 2014;168:351–60. https://doi.org/10.1001/jamapediatrics.2013.4647.10.1001/jamapediatrics.2013.4647Search in Google Scholar PubMed
36. Asprusten, TT, Fagermoen, E, Sulheim, D, Skovlund, E, Sørensen, Ø, Mollnes, TE, et al. Study findings challenge the content validity of the Canadian consensus criteria for adolescent chronic fatigue syndrome. Acta Paediatr 2015;104:498–503. https://doi.org/10.1111/apa.12950.10.1111/apa.12950Search in Google Scholar PubMed
37. Bjelland, I, Dahl, AA, Haug, TT, Neckelmann, D. The validity of the hospital anxiety and depression scale. An updated literature review. J Psychosom Res 2002;52:69–77. https://doi.org/10.1016/s0022-3999(01)00296-3.10.1016/S0022-3999(01)00296-3Search in Google Scholar PubMed
38. Uljarević, M, Richdale, AL, McConachie, H, Hedley, D, Cai, RY, Merrick, H, et al. The Hospital Anxiety and Depression scale: factor structure and psychometric properties in older adolescents and young adults with autism spectrum disorder. Autism Res 2018;11:258–69. https://doi.org/10.1002/aur.1872.10.1002/aur.1872Search in Google Scholar PubMed
39. Zigmond, AS, Snaith, RP. The hospital anxiety and depression scale. Acta Psychiatr Scand 1983;67:361–70. https://doi.org/10.1111/j.1600-0447.1983.tb09716.x.10.1111/j.1600-0447.1983.tb09716.xSearch in Google Scholar PubMed
40. (IASP) IAftSoP. Classification of chronic pain, descriptions of chronic pain syndromes and definitions of pain terms. Amsterdam: Elsevier; 1986.Search in Google Scholar
41. Rombaut, L, Scheper, M, De Wandele, I, De Vries, J, Meeus, M, Malfait, F, et al. Chronic pain in patients with the hypermobility type of Ehlers-Danlos syndrome: evidence for generalized hyperalgesia. Clin Rheumatol 2015;34:1121–9. https://doi.org/10.1007/s10067-014-2499-0.10.1007/s10067-014-2499-0Search in Google Scholar PubMed
42. Grant, PM, Ryan, CG, Tigbe, WW, Granat, MH. The validation of a novel activity monitor in the measurement of posture and motion during everyday activities. Br J Sports Med 2006;40:992–7. https://doi.org/10.1136/bjsm.2006.030262.10.1136/bjsm.2006.030262Search in Google Scholar PubMed PubMed Central
43. Fortin, J, Habenbacher, W, Heller, A, Hacker, A, Grüllenberger, R, Innerhofer, J, et al. Non-invasive beat-to-beat cardiac output monitoring by an improved method of transthoracic bioimpedance measurement. Comput Biol Med 2006;36:1185–203 https://doi.org/10.1016/j.compbiomed.2005.06.001.10.1016/j.compbiomed.2005.06.001Search in Google Scholar PubMed
44. Bianchi, AM, Mainardi, LT, Meloni, C, Chierchia, S, Cerutti, S. Continuous monitoring of the sympatho-vagal balance through spectral analysis. IEEE Eng Med Biol Mag 1997;16:64–73. https://doi.org/10.1109/51.620497.10.1109/51.620497Search in Google Scholar PubMed
45. Nijs, J, Meeus, M, Van Oosterwijck, J, Ickmans, K, Moorkens, G, Hans, G, et al. In the mind or in the brain? Scientific evidence for central sensitisation in chronic fatigue syndrome. Eur J Clin Invest 2012;42:203–12. https://doi.org/10.1111/j.1365-2362.2011.02575.x.10.1111/j.1365-2362.2011.02575.xSearch in Google Scholar PubMed
46. Bourke, JH, Langfor, RM, White, PD. The common link between functional somatic syndromes may be central sensitisation. J Psychosom Res 2015;78:228–36. https://doi.org/10.1016/j.jpsychores.2015.01.003.10.1016/j.jpsychores.2015.01.003Search in Google Scholar PubMed
47. Gan, GG, Yuen Ling, H. Anxiety, depression and quality of life of medical students in Malaysia. Med J Malaysia 2019;74:57–61.Search in Google Scholar
48. ME, A. Anxiety and depression predicted quality of life among patients with heart failure. J Multidiscip Healthc 2018;11:367–73. https://doi.org/10.2147/JMDH.S170327.10.2147/JMDH.S170327Search in Google Scholar PubMed PubMed Central
49. Lomper, K, Chudiak, A, Uchmanowicz, I, Rosińczuk, J, Jankowska-Polanska, B. Effects of depression and anxiety on asthma-related quality of life. Pneumonol Alergol Pol 2016;84:212–21. https://doi.org/10.5603/piap.2016.0026.10.5603/PiAP.2016.0026Search in Google Scholar PubMed
50. White, PD, Thomas, JM, Sullivan, PF, Buchwald, D. The nosology of sub-acute and chronic fatigue syndromes that follow infectious mononucleosis. Psychol Med 2004;34:499–507. https://doi.org/10.1017/s0033291703001302.10.1017/S0033291703001302Search in Google Scholar
© 2020 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Editorial Comment
- The history of the idea of widespread pain and its relation to fibromyalgia
- Clinical Pain Research
- Pain perception in chronic knee osteoarthritis with varying levels of pain inhibitory control: an exploratory study
- Fibromyalgia 2016 criteria and assessments: comprehensive validation in a Norwegian population
- Development and preliminary validation of the Chronic Pain Acceptance Questionnaire for Clinicians
- Static mechanical allodynia in post-surgical neuropathic pain after breast cancer treatments
- Preoperative quantitative sensory testing and robot-assisted laparoscopic hysterectomy for endometrial cancer: can chronic postoperative pain be predicted?
- Exploring the impact of pain management programme attendance on complex regional pain syndrome (CRPS) patients’ decision making regarding immunosuppressant treatment to manage their chronic pain condition
- Preliminary validity and test–retest reliability of two depression questionnaires compared with a diagnostic interview in 99 patients with chronic pain seeking specialist pain treatment
- Pain acceptance and its impact on function and symptoms in fibromyalgia
- Observational studies
- Cooled radiofrequency for the treatment of sacroiliac joint pain – impact on pain and psychometrics: a retrospective cohort study
- Pain perception during colonoscopy in relation to gender and equipment: a clinical study
- The association between initial opioid type and long-term opioid use after hip fracture surgery in elderly opioid-naïve patients
- Pain in adolescent chronic fatigue following Epstein-Barr virus infection
- Patients with shoulder pain referred to specialist care; treatment, predictors of pain and disability, emotional distress, main symptoms and sick-leave: a cohort study with a six-months follow-up
- Original Experimental
- The effect of periaqueductal gray’s metabotropic glutamate receptor subtype 8 activation on locomotor function following spinal cord injury
- Baseline pain characteristics predict pain reduction after physical therapy in women with chronic pelvic pain. Secondary analysis of data from a randomized controlled trial
- A novel clinical applicable bed-side tool for assessing conditioning pain modulation: proof-of-concept
- The acquisition and generalization of fear of touch
- Associations of neck and shoulder pain with objectively measured physical activity and sedentary time among school-aged children
- Health-related quality of life in burning mouth syndrome – a case-control study
- Stretch-induced hypoalgesia: a pilot study
- Educational Case Report
- Erector spinae plane and intra thecal opioid (ESPITO) analgesia in radical nephrectomy utilising a rooftop incision: novel alternative to thoracic epidural analgesia and systemic morphine: a case series
- Short Communication
- Above and beyond emotional suffering: the unique contribution of compassionate and uncompassionate self-responding in chronic pain
- Letter to the Editor
- Labor pain, birth experience and postpartum depression
- Reply: Response to Letter to the Editor “Labor pain, birth experience and postpartum depression”
- Corrigendum
- Corrigendum to: Are labor pain and birth experience associated with persistent pain and postpartum depression? A prospective cohort study
Articles in the same Issue
- Frontmatter
- Editorial Comment
- The history of the idea of widespread pain and its relation to fibromyalgia
- Clinical Pain Research
- Pain perception in chronic knee osteoarthritis with varying levels of pain inhibitory control: an exploratory study
- Fibromyalgia 2016 criteria and assessments: comprehensive validation in a Norwegian population
- Development and preliminary validation of the Chronic Pain Acceptance Questionnaire for Clinicians
- Static mechanical allodynia in post-surgical neuropathic pain after breast cancer treatments
- Preoperative quantitative sensory testing and robot-assisted laparoscopic hysterectomy for endometrial cancer: can chronic postoperative pain be predicted?
- Exploring the impact of pain management programme attendance on complex regional pain syndrome (CRPS) patients’ decision making regarding immunosuppressant treatment to manage their chronic pain condition
- Preliminary validity and test–retest reliability of two depression questionnaires compared with a diagnostic interview in 99 patients with chronic pain seeking specialist pain treatment
- Pain acceptance and its impact on function and symptoms in fibromyalgia
- Observational studies
- Cooled radiofrequency for the treatment of sacroiliac joint pain – impact on pain and psychometrics: a retrospective cohort study
- Pain perception during colonoscopy in relation to gender and equipment: a clinical study
- The association between initial opioid type and long-term opioid use after hip fracture surgery in elderly opioid-naïve patients
- Pain in adolescent chronic fatigue following Epstein-Barr virus infection
- Patients with shoulder pain referred to specialist care; treatment, predictors of pain and disability, emotional distress, main symptoms and sick-leave: a cohort study with a six-months follow-up
- Original Experimental
- The effect of periaqueductal gray’s metabotropic glutamate receptor subtype 8 activation on locomotor function following spinal cord injury
- Baseline pain characteristics predict pain reduction after physical therapy in women with chronic pelvic pain. Secondary analysis of data from a randomized controlled trial
- A novel clinical applicable bed-side tool for assessing conditioning pain modulation: proof-of-concept
- The acquisition and generalization of fear of touch
- Associations of neck and shoulder pain with objectively measured physical activity and sedentary time among school-aged children
- Health-related quality of life in burning mouth syndrome – a case-control study
- Stretch-induced hypoalgesia: a pilot study
- Educational Case Report
- Erector spinae plane and intra thecal opioid (ESPITO) analgesia in radical nephrectomy utilising a rooftop incision: novel alternative to thoracic epidural analgesia and systemic morphine: a case series
- Short Communication
- Above and beyond emotional suffering: the unique contribution of compassionate and uncompassionate self-responding in chronic pain
- Letter to the Editor
- Labor pain, birth experience and postpartum depression
- Reply: Response to Letter to the Editor “Labor pain, birth experience and postpartum depression”
- Corrigendum
- Corrigendum to: Are labor pain and birth experience associated with persistent pain and postpartum depression? A prospective cohort study