Central sensitization and functioning in patients with chronic low back pain: A cross-sectional and longitudinal study

Abstract

BACKGROUND:

Central sensitization (CS) is present in a subgroup of patients with chronic low back pain (CLBP). Studies on the relationship between CS and functioning have limited operationalizations of CS and functioning.

OBJECTIVE:

To determine whether CS was related to functioning in patients with CLBP (cross-sectional); and to determine whether changes in CS were related to changes in functioning (longitudinal).

METHODS:

An observational prospective cohort study with data collected at baseline and discharge of an interdisciplinary pain rehabilitation program was executed. CS indicators: CS Inventory part A (CSI-A), quantitative sensory testing (QST), root mean square of successive differences of heart-rate variability (RMSSD). Functioning measures: lifting capacity, physical functioning subscale of Rand36 (Rand36-PF), Work Ability Score (WAS), Pain Disability Index (PDI). Main analyses included correlation and multiple regression controlling for confounders; cross-sectional with baseline data and longitudinal with deltas ( $\Delta$ ).

RESULTS:

76 patients with primary CLBP participated at baseline and 56 at discharge. Most associations were weak (cross-sectional $r_{\textit{partial}}=$ $-$ 0.30–0.24; longitudinal $r_{\textit{partial}}=$ $-$ 0.37–0.44). Cross-sectional multiple regression significant associations: mechanical pain threshold-QST and lifting capacity ( $r_{\textit{partial}}=$ $-$ 0.39), parasympathetic/vagal tone-RMSSD and physical functioning–Rand36-PF ( $r_{\textit{partial}}=$ 0.26). Longitudinal multiple regression significant associations: $\Delta$ parasympathetic/vagal tone-RMSSD and $\Delta$ lifting capacity ( $r_{\textit{partial}}=$ 0.48), $\Delta$ CSI-A and $\Delta$ disability-PDI ( $r_{\textit{partial}}=$ 0.36). Cross-sectional and longitudinal final regression models explained 24.0%–58.3% and 13.3%–38.0% of total variance.

CONCLUSION:

CS was weakly related to functioning, and decreases in CS were weakly-moderately related to increases in functioning.

Keywords

Hyperalgesia lifting physical functioning disability work ability

1. Introduction

Worldwide, chronic low back pain (CLBP) is the leading condition of years lived with disability [1]. The functioning of individuals with CLBP can be limited in daily live activities [2, 3]. Patients with limited functioning are more likely to utilize healthcare [4], but treatment outcomes are only moderate [5]. An important strategy to improve treatment efficacy is to better understand the mechanisms associated with functioning limitations in patients with CLBP.

A mechanism underlying the pain experience in patients with CLBP is central sensitization (CS). CS reflects a hypersensitive state of the central nervous system due to: an increase in the signaling of neuronal responsiveness to nociceptive stimuli in firing frequency and intensity, a decrease in nociceptive activation threshold, a reduction in nociceptive inhibition mechanisms, and a reduced vagal nerve activity [6, 7, 8, 9]. These indicators have most frequently been assessed with the Central Sensitization Inventory (CSI) –a screener questionnaire–, the quantitative sensory testing (QST) –threshold determination and stimulus-response assessments of sensory processing–, and the heart-rate variability (HRV) –autonomous nervous system function assessment, including vagal activity.

CS can be present in a subgroup of patients with CLBP [10]. Because pain experience is enhanced if CS is present, and because pain is consistently related to limitations in functioning in patients with CLBP [11], the presence and/or more CS indicators in patients with CLBP may be expected to be associated with lower functioning. Consequently, if this association exists, a decrease in the presence of CS indicators could be associated with improved functioning.

There is some evidence of the association between CS and limited functioning [12, 13, 14, 15, 16, 17, 18, 19, 20], however, these studies utilized limited and diverse CS indicators and functioning measures. Specifically, more self-reported CS-related symptoms [12, 13, 18, 20], decreased parasympathetic/vagal activity [14, 15] , or altered somatosensory responses [16, 17, 19], were associated with higher self-reported pain-related disability and/or lower physical function. But the indicators of CS varied in the associations; also if somatosensory responses were assessed the associations varied per body site of testing, stimuli and type of tests performed; and functioning was mostly measured with self-reported measures. The combined use of different methods to assess CS will give complementary information and a more comprehensive overview of CS phenomenon. Similarly, a comprehensive overview of the functioning status of the individual is better obtained with performance and self-reported measures combined [21, 22]. To our knowledge, no study has been performed where a comprehensive set of methods to assess CS and functioning were used.

One of the main objectives of pain rehabilitation is to help patients to improve their functioning and resume to their usual daily living, including work. Better understanding of factors associated with functioning limitations in CLBP is needed to improve effectiveness of pain rehabilitation. The aim of the present study was to analyze the association between CS indicators and functioning in patients with CLBP, cross-sectional and longitudinally. The research questions were: 1) Is CS associated to functioning in patients with CLBP? It was hypothesized that a stronger presence of CS indicators would be inversely associated to functioning measures; 2) Are changes in CS associated to changes in functioning in patients with CLBP? The hypothesis was that a decrease in the presence of CS indicators would be associated to increases in functioning measures.

2. Materials and methods

2.1 Design

An observational prospective cohort study was conducted from September 2017 to September 2019 in the center for rehabilitation of a university medical center in the Netherlands. This study is part of a larger project, Dutch national trial register (NTR7167/NL6980), and a detailed description of the study protocol is published elsewhere [23].

Ethical approval was obtained (METc 2016/702), and the study procedures followed the ethical standards of the Declaration of Helsinki of 1975, revised in 2013 [24]. The STROBE statement was used for the report of observational studies [25] (Appendix 1).

2.2 Participants

Consecutive patients between 18 and 65 years referred to the Pain Rehabilitation Department because of primary CLBP ( $\geqslant$ 3 months; ICD-11 code MG30.02) [26]. Main exclusion criteria, based on patient’s file, were: (suspicion of) a specific diagnosis that would better account for the symptoms (e.g. cancer, osteoporosis and/or spinal fractures), neuralgia or radicular pain in the legs, major disorder or comorbidity substantially interfering with functioning (e.g. affecting their physical and/or mental functioning such as severe psychiatric disorders or severe cardiopulmonary problems), or pregnancy. Exclusion criteria belonging to specific tests, were: for the lifting test hypertension ( $\geqslant$ 100/160 mmHg) [27]; for the QST the presence of nerve or tissue damage affecting the measurement locations, or a blood vessel disorder such as Raynaud’s disorder; and for the HRV the use of medication (for example beta blockers) or a cardiac disease that could influence heart-rate. All participants provided written informed consent.

2.3 Measurements

The assessment of patients was part of care as usual during baseline and discharge of an interdisciplinary pain rehabilitation program. This is a personalized outpatient program that lasts on average 12 weeks with 2 visits per week. For the assessments a biopsychosocial framework is used and patients actively participate in the content and planning of their treatment. The assessments and program are delivered by a team specialized in pain rehabilitation, consisting of physical therapists, occupational therapists and psychologists working together.

2.3.1 Functioning

Lifting capacity was assessed with the floor-to-waist lifting test [28]. Patients were asked to lift a crate with standardized weights from a shelf at 75 cm to the floor and vice versa. The weight in the crate is progressively increased every five repetitions until patients reach the endpoint. The maximum weight lifted patient-reported and clinician-observed efforts with Borg’s category ratio scale (CR-10; 0–10) [29, 30] were recorded. The lifting test has acceptable test–retest in patients with CLBP [31] and predictive ability in work participation [32].

Physical functioning was measured with the subscale of the Rand36 (Rand36-PF) [33]. The subscale assesses the health-related limitations patients experience during daily activities. A higher total mean score (0–100) is associated with fewer limitations in performing daily activities. Dutch translation of Rand36 has acceptable psychometric qualities in the general population [34].

Disability was measured with the Pain Disability Index (PDI). The PDI consists of seven questions which assess the interference of pain during several daily activities: family/home responsibilities, recreation, social activity, occupation, sexual behavior, self-care and life-support activity [35]. A higher total sum score (0–70) is associated with higher interference in daily life activities. The Dutch language version has acceptable psychometric qualities in patients with musculoskeletal pain including CLBP [36].

Work ability was measured with the Work Ability Score (WAS), a single-item question from the Work Ability Index (WAI). The WAS assesses the current work ability compared to the lifetime best (0–10) The WAS is highly correlated to the full WAI questionnaire [37, 38, 39].

2.3.2 Central sensitization

CSI part A (CSI-A) is a questionnaire designed to estimate the severity of the symptoms related to CS. The presence of CS-related somatic and emotional symptoms are scored on a five-point Likert-scale (from 0 (never) to 4 (always)). A higher total sum score (0–100) is associated with more severe symptomatology [40]. The Dutch version of CSI has good psychometric qualities in controls and in patients with chronic musculoskeletal pain [41].

QST has a battery of standardized sensory tests to quantify the function of the somatosensory system. The QST consisted of five tests based on the German Research Network on Neuropathic Pain (DFNS) protocol [42]: sharp cutaneous pain sensation (mechanical pain threshold-MPT), blunt pressure pain sensation (pressure pain threshold-PPT), allodynia (dynamic mechanical allodynia-DMA), touch sensation (mechanical detection threshold-MDT) and temporal summation (wind-up ratio-WUR). These five tests were assessed in six body locations (most painful location in the low back, mirror to the most painful location, ipsi-and contralateral muscle trapezius and ipsi-and contralateral rectus femoris of muscle quadriceps) after being acquainted with the tests in a training location [23]. Additionally, the descending pain modulation (conditioned pain modulation–CPM) was tested according the Nijmegen-Aalborg Screening QST (NASQ) protocol [43]. The detailed description of the QST assessment is presented in Appendix 2.

HRV is a non-invasive assessment to measure the function and balance of the sympathetic tone and the parasympathetic/vagal tone of the autonomic nervous system [44, 45]. The HRV was performed by trained assessors and followed the five minute protocol [45]. HRV was assessed with an ear pulse sensor, while patients were seated and breathing normally [46]. The HRV time and frequency domain data was recorded with emWave PC software (emWave ${}^{\@setsize{\scriptsize}{8pt}{\viipt}{\@viipt}\textregistered}$ , HeartMath Inc., USA), and was processed by an experienced clinician to eliminate potential noise if needed. The parasympathetic/vagal tone in individuals with chronic pain is low. In HRV, the parasympathetic/vagal tone is reflected by both root mean square of successive differences (RMSSD) and high frequency (HF, 0.15–0.40 Hz); although RMSSD is preferred because it is less influenced by respiratory rates [47].

2.3.3 Participants’ characteristics

Age, sex, height, weight, pain duration, use of pain medication, educational level, occupation, and work status data were collected with a questionnaire developed for the study.

Clinical data was collected: pain intensity with the Visual Analogue Scale (VAS pain, 0–10) [48]; catastrophizing with the Pain Catastrophyzing Scale (PCS, 0–52) [49, 50]; injustice with the Injustice Experience Questionnaire (IEQ, 0–48) [51, 52]; and distress with the Brief Symptom Inventory (BSI, global severity index $t$ -score (GSIT), 0–100) [53, 54]. All these questionnaires have sufficient test-retest reliability ( $r$ or ICC 0.71–0.94) [48, 50, 52, 53].

2.4 Statistical analyses

Data was prepared for analyses. Body mass index was calculated. Occupation was converted into work physical demands categories per the Dictionary of Occupational Titles (DOT) [55]. Means of each QST test (MPT, PPT, DMA, MDT and WUR) were calculated from the body locations, with the exception of the training location and provided that a minimum of four locations had data. The mean DMA was calculated from the DMAs whose stimulus (brush swipe) was felt and subsequently categorized into: no DMA, DMA pain score 0–1, and DMA pain score 1–100 [56]. For variables entering longitudinal analyses deltas ( $\Delta$ ) were computed, expressed as the percentage change from baseline: $\Delta=$ [(Discharge–Baseline)/Baseline]*100; if a score of 0 was at baseline, delta was alternatively computed as: $\Delta=$ (Discharge–Baseline)*100. Higher values of $\Delta$ indicate greater differences from baseline; and positive $\Delta$ s mean higher values at discharge compared to baseline.

Descriptive statistics were performed and data distribution was assessed. Missing data of main measures (functioning and CS) were inspected and sensitivity analyses comparing patients were performed when $>$ 10% was missing. Sensitivity analyses were also performed to ensure that the characteristics of the group measured at baseline and at discharge (patients ceasing participation) did not differ from the group measured at baseline only. The sensitivity analyses were performed on dependent variables and participants’ characteristics: lifting capacity, physical functioning, disability, work ability, age, sex, physical work demands, and pain intensity. Continuous variables with independent $t$ -tests–or Mann-Whitney U if not normally distributed – and categorical variables with chi-squared tests.

For research question 1, cross-sectional analyses with baseline data were performed. First, Spearman partial correlation analyses were performed, corrected for sex and age due to known differences in lifting capacity, HRV and QST [47, 57, 58]. Second, multiple regression analyses were performed, with each functioning measurement separately as dependent variable, one variable representative of each CS indicator as fixed independent variables, and participants’ characteristics as potential confounders (including the correction for age and sex). The variables representative of CS indicators were: CSI-A, the QST test with the highest correlation coefficient (per first step), and RMSSD for HRV. Confounders with a correlation coefficient $\geqslant$ 0.1 (from the first step) were entered to the regression model one at a time in a descending order until the model was fit (10 cases per variable [59]). Confounders were retained if their addition was significant ( $p<$ 0.05).

For research question 2, longitudinal analyses with $\Delta$ s were executed. Correlation analyses were performed; Pearson if data was normally distributed and Spearman otherwise. Multiple regression analyses were performed anew for each functioning measurement, with one variable representative of each CS indicator as independent variables, and participants’ characteristics as potential confounders. CS indicators entering these models were again CSI-A, the QST test with the highest correlation coefficient (per first step), and RMSSD for HRV. Confounders entered regression models in a descending order, from highest to lowest coefficient of correlation, if $r\geqslant$ 0.1, and until the model was fit [59]. Confounders were retained if their addition was significant ( $p<$ 0.05).

Table 1
Participants’ demographic characteristics at baseline

	$n$	Median	IQR (25–75) or %
Age (years)	76	40.0	(31.3–50.8)
Sex	76
Men	31		40.8%
Women	45		59.2%
Body mass index (kg/m ${}^{2}$ )	76	26.7	(24.2–30.6)
Pain duration (years)	76	2.2	(1.3–4.2)
Use of medication	74
Use pain medication	55		74.3%
No use of pain medication	19		25.7%
Educational level	71
Primary	2		2.8%
Secondary	41		57.7%
Bachelor or higher	28		39.4%
Physical work demands (DOT)	76
Sedentary	18		23.7%
Light	33		43.4%
Medium	21		27.6%
Heavy	4		5.3%
Working status	76
Working	28		36.8%
Reduced/Adapted work	17		22.4%
Sick-leave	9		11.8%
Disability pension	8		10.5%
Not working	10		13.2%
Other	4		5.3%

Abbreviations: DOT, Dictionary of Occupational Titles.

Correlations were interpreted as weak if $<$ 0.3, moderate if 0.3–0.5, and strong if $>$ 0.5 [60]. The significance level for multiple correlation and sensitivity analyses was established at $p<$ 0.01, to account for the risk of type I errors. Results from multiple regression analyses were considered significant if $p<$ 0.05. The regression assumptions were checked and results were expressed in unstandardized betas and 95% confidence intervals, partial correlations, p-values and adjusted explained variance. All correlation and regression analyses were performed with pairwise deletion. SPSS software version 22.0 (IBM Corp., NY) was used.

3. Results

Patients’ demographic characteristics are presented in Table 1. Seventy-six patients participated, mean age 40.6 years (SD:12.2), 59% were women, 40% used pain medication regularly and another 34% on demand. Of them, 73 performed the lifting capacity, 75 filled in the physical functioning and work ability questionnaires, and 73 the disability questionnaire. Sensitivity analyses for missing data was needed in only one variable, WUR (from QST), due to its computation (see Appendix 2).The characteristics of participants with missing data in the variable WUR showed no significant differences ( $p>$ 0.157) from participants without missing data in it.

Table 2
Participants’ functioning, CS and clinical characteristics from baseline, discharge and deltas

	Baseline			Discharge			Delta
	$n$	Median IQR (25–75)		$n$	Median IQR (25–75)		$n$	Median IQR (25–75)
Functioning
Lifting capacity (kg)	73	13.5	(7.4–19.3)	52	16.3	(9.0–22.5)	52	13.6	( $-$ 16.1–38.3)
Patient’s reported exertion (CR-10, 0–10) ${}^{{\dagger}}$	73	6.1 $\pm$ 1.9		52	5.4 $\pm$ 1.6		52	0.0	( $-$ 32.5–25.0)
Assessor’s observed exertion (CR-10, 0–10) ${}^{{\dagger}}$	72	5.5 $\pm$ 2.1		52	5.3 $\pm$ 1.8		51	0.0	( $-$ 28.6–60.0)
Physical functioning (Rand36-PF, 0–100) ${}^{{\dagger}}$	75	50.9 $\pm$ 19.5		52	64.4 $\pm$ 22.4		51	20.0	(0.0–50.0)
Disability (PDI, 0–70) ${}^{{\dagger}}$	73	36.9 $\pm$ 12.0		53	23.1 $\pm$ 14.7		51	$-$ 42.0	( $-$ 61.8–15.6)
Work ability (WAS, 0–10) ${}^{{\dagger}}$	75	4.6 $\pm$ 2.4		52	5.8 $\pm$ 2.1		51	0.0	(0.0–66.7)
CS
CSI
CS-related symptoms (CSI-A, 0–100)	73	40.0	(31.0–49.8)	46	33.0	(27.8–45.0)	45	$-$ 12.1	( $-$ 30.3–5.9)
QST
Sharp cutaneous pain sensation (MPT, mN)	71	72.0	(32.0–186.7)	53	77.3	(44.0–213.3)	53	8.3	( $-$ 43.2–123.8)
Blunt pressure pain sensation (PPT, N)	71	53.3	(41.2–72.6)	53	60.1	(43.2–82.5)	53	8.0	( $-$ 7.3–23.3)
Allodynia (DMA)	70	0.0%		53	1.9%
Touch sensation (MDT, mN)	71	3.3	(1.6–8.0)	53	3.5	(1.5–8.7)	53	9.1	( $-$ 45.8–97.1)
Temporal summation (WUR, ratio)	60	2.4	(1.8–3.2)	44	2.6	(1.9–3.2)	41	3.7	( $-$ 35.2–40.2)
Descending pain modulation (CPM, %)	70	6.9	( $-$ 4.3–23.1)	52	6.2	( $-$ 7.2–16.2)	52	$-$ 80.7	( $-$ 171.5–6.6)
HRV
Parasympathetic/vagal tone (RMSSD, ms)	70	40.7	(30.6–54.3)	52	42.8	(30.6–61.5)	52	8.1	( $-$ 18.2–41.4)
Parasympathetic/vagal tone (HF, ms ${}^{2}$ /Hz)	70	101.4	(61.5–192.5)	52	127.6	(54.9–243.2)	52	6.0	( $-$ 45.8–122.3)
Mean inter-beat time interval (R-R interval, ms)	70	816.7	(748.7–917.5)	52	840.3	(770.0–905.9)	52	$-$ 0.2	( $-$ 6.0–9.7)
Standard deviation of R-R intervals (SDNN, ms)	70	56.8	(42.0–71.8)	52	72.4	(45.4–90.6)	52	21.7	( $-$ 6.6–63.4)
Clinical characteristics
Pain intensity (VAS pain, 0–10)	75	5.1	(2.7–6.6)	52	3.2	(1.9–4.6)	51	$-$ 23.7	( $-$ 56.9–18.9)
Catastrophyzing (PCS, 0–52)	66	18.0	(11.0 – 27.0)	44	8.0	(5.0–14.0)	43	$-$ 54.5	( $-$ 73.7—20.4)
Injustice (IEQ, 0–48)	71	16.0	(10.0–23.0)	42	11.0	(5.0–15.3)	41	$-$ 29.4	( $-$ 55.8—4.8)
Distress (BSI-GSIT, 0–100)	66	38.1	(33.0–45.8)	42	33.8	(30.6–40.2)	41	$-$ 7.2	( $-$ 15.7–3.8)

†: variable normally distributed, mean and standard deviation ( $\pm$ SD) are shown. Abbreviations: BSI-GSIT, Brief Symptom Inventory Global Severity Index T-score; CPM, Conditioned Pain Modulation; CR, Category Ratio; CS, Central Sensitization; CSI-A, Central Sensitization Inventory part A; DMA, Dynamic Mechanical Allodynia; HF, High-Frequency; HRV, Heart-Rate Variability; IEQ, Injustice Experience Questionnaire; MDT, Mechanical Detection Threshold; MPT, Mechanical Pain Threshold; PCS, Pain Catastrophyzing Scale; PDI, Pain Disability Index; PF, subscale Physical Functioning; PPT, Pressure Pain Threshold; QST, Quantitative Sensory Testing; RMSSD, Root Mean Square of Successive Differences; SDNN, Standard Deviation of Normal-to-Normal range; VAS, Visual Analogue Scale; WAS, Work Ability Score; WUR, Wind-Up Ratio.

A total of 56 patients were measured again at discharge. Of the initial sample, 13 patients did not follow the rehabilitation program, three did not show for discharge and four cancelled participation in the study. Patients’ functioning, CS indicators and clinical characteristics at baseline, discharge and deltas are presented in Table 2. Improvements were observed in lifting capacity, physical functioning and disability; but not in work ability. Improvements were also observed in CSI-A, QST thresholds (MPT, PPT and MDT) and parasympathetic/vagal tone (RMSSD and HF); but the dynamic measures of QST (WUR and CPM) did not improve. In the sensitivity analyses, the characteristics of participants measured at both time points was not different ( $p>$ 0.012) from those measured at baseline only.

Cross-sectional associations between CS indicators and functioning measurements were weak ( $r_{\textit{partial}}=$ $-$ 0.30–0.24) and none was significant (Appendix 3).

The regression models of lifting capacity, physical functioning and disability included seven variables, whereas work ability six (Table 3). The model with the most total variance explained was lifting capacity ( $r^{2}=$ 58.3%; $p<$ 0.001), followed by physical functioning ( $r^{2}=$ 41.7%; $p<$ 0.001), disability ( $r^{2}=$ 34.8%; $p<$ 0.001) and work ability ( $r^{2}=$ 24.0%; $p=$ 0.003). MPT was significantly associated with lifting capacity ( $r_{\textit{partial}}=$ $-$ 0.39), and RMSSD with physical functioning ( $r_{\textit{partial}}=$ 0.26). No other CS measurements were associated with functioning. The residuals of the lifting capacity model were not normally distributed; consequently, the model was rerun with the square root of the lifting capacity (sq_lifting) as dependent variable. Both models were similar; no changes in the significance occurred after the transformation with the exception of age, which became significantly associated. Based on the results from sq_lifting and provided data of each of the variables included in the model is known, the lifting capacity (kg) can be calculated by squaring the outcome coefficient (see Appendix 4 for an example).

Longitudinal associations between CS and functioning measurements were mostly weak and largely not significant (Appendix 5). Moderate significant associations were observed between: $\Delta$ lifting capacity and $\Delta$ RMSSD ( $r=$ 0.41); and $\Delta$ disability and $\Delta$ CSI-A ( $r=$ 0.44). All other associations were weak ( $r_{\textit{partial}}=$ $-$ 0.37–0.32) and not significant.

Regression models were partial; lifting capacity, disability and work ability models did not fulfill the assumption of normality in the distribution of residuals. Therefore, the results of the regression analyses should be considered as exploratory. The models included four variables, with the exception of disability which included three (Table 4). $\Delta$ Lifting capacity was the model with the most total variance explained ( $r^{2}=$ 38.0%; $p<$ 0.001), followed by $\Delta$ work ability ( $r^{2}=$ 25.0%; $p=$ 0.005), $\Delta$ physical functioning ( $r^{2}=$ 17.3%; $p=$ 0.027) and $\Delta$ disability ( $r^{2}=$ 13.3%; $p=$ 0.068). Of the CS measurements only $\Delta$ RMSSD and $\Delta$ CSI-A remained significantly associated respectively with $\Delta$ lifting capacity ( $r_{\textit{partial}}=$ 0.48) and $\Delta$ disability ( $r_{\textit{partial}}=$ 0.36).

4. Discussion

Some weak-to-moderate and heterogeneous associations were identified between CS indicators and functioning. In the cross-sectional analyses, CS indicators were associated weakly with functioning in patients with CLBP; and after correcting for confounders, MPT was associated with lifting capacity and RMSSD with physical functioning. In the longitudinal analyses, decreases in CS indicators were associated weakly-moderately to increases in functioning; and after correcting for confounders, $\Delta$ RMSSD was associated with $\Delta$ lifting capacity, and $\Delta$ CSI-A with $\Delta$ disability. Knowledge on the associations of factors related to functioning and on changes in those associations overtime, can assist in better personalization of the rehabilitation programs. Previous research has identified biopsychosocial factors contributing to the functioning of patients with CLBP [61]. Our study has been able to analyze the contribution of CS indicators to functioning measures beyond biopsychosocial factors, not only cross-sectionally but also longitudinally.

CLBP is multifaceted, patients suffering from it form a heterogeneous group, and have been reported to have contradictory results in the outcome measures of the assessment of the presence of CS [62]. Also, patient’s state or situation is dynamic, continuously evolving, which would affect their perceptions and functioning as well as the factors associated with them. And, their coping strategy to pain is diverse, ranging from an avoiding behavior to a persisting/enduring behavior [63], where mixed and changing strategies may also be present. Therefore, even if the associations found in this study are weak and not unequivocal, they may be representative of the complex and individualized nature of pain and the adaptive strategies of patients with CLBP. In clinical practice, the inclusion of CS indicators along with known biopsychosocial factors contributing to the functioning of patients with CLBP during the initial evaluation, the rehabilitation program, as well as the

Table 3
Results of multiple regression analyses (cross-sectional)

Lifting capacity (

n=

66)

{}^{{\dagger}}

Physical functioning (

n=

66)

Disability (

n=

66)

Work ability (

n=

56)

[95% CI]

r_{\textit{partial}}

[95% CI]

r_{\textit{partial}}

[95% CI]

r_{\textit{partial}}

[95% CI]

r_{\textit{partial}}

(Constant)

4.22

[2.80, 5.65]

56.67

[30.23, 85.11]

34.50

[15.99, 53.01]

1.04

[

-

3.12, 5.20]

CSI

CS-related symptoms (CSI-A)

0.00

[

-

0.02, 0.02]

0.00

0.11

[

-

0.19, 0.42]

0.10

0.12

[

-

0.08, 0.32]

0.15

-

0.02

[

-

0.06, 0.03]

-

0.11

QST

Sharp cutaneous pain sensation (MPT)

-

0.00

[

-

0.00,

-

0.00]

-

0.39**

–

Touch sensation (MDT)

–

0.34

[0.01, 0.69]

0.25

–

Temporal summation (WUR)

–

0.26

[

-

0.11 , 0.63]

0.20

Descending pain inhibition (CPM)

–

-

0.11

[

-

0.23 , 0.01]

-

0.23

–

HRV

Parasympathetic/ vagal tone (RMSSD)

-

0.00

[

-

0.01 , 0.01]

-

0.02

0.19

[0.01, 0.37]

0.26*

0.06

[

-

0.06, 0.18]

0.12

-

0.01

[

-

0.04, 0.02]

-

0.11

Age

-

0.02

[

-

0.04,

-

0.00]

-

0.28*

-

0.21

[

-

0.52, 0.11]

-

0.17

-

0.01

[

-

0.22, 0.20]

-

0.01

0.02

[

-

0.03, 0.07]

0.10

Sex: Women

-

1.10

[

-

1.53,

-

0.67]

-

0.56***

-

1.04

[

-

8.59, 6.51]

-

0.04

-

0.71

[

-

5.63, 4.22]

-

0.04

-

0.02

[

-

1.17, 1.13]

-

0.01

Assessor’s observed exertion (CR-10)

0.31

[0.21, 0.42]

0.63***

–

Pain intensity (VAS pain)

-

0.12

[

-

0.22,

-

0.03]

-

0.32*

–

1.36

[0.18 , 2.54]

0.29*

–

Disability (PDI)

–

-

0.62

[

-

0.96,

-

0.27]

-

0.42**

–

Work ability (WAS)

–

2.86

[1.17, 4.55]

0.40**

–

Physical functioning (Rand36-PF)

–

-

0.25

[

-

0.39,

-

0.11]

-

0.42**

0.07

[0.04 , 0.10]

0.52***

†: the model uses the square root of lifting performance (sq_lifting) as dependent variable. –: not tested. Significance level of the introduced variables in the final regression models: *, $p<$ 0.05; **, $p<$ 0.01; *** $p<$ 0.001. Abbreviations: CPM, Conditioned Pain Modulation; CR, Category Ratio; CS, Central Sensitization; CSI-A, Central Sensitization Inventory part A; HRV, Heart Rate Variability; MDT, Mechanical Detection Threshold; MPT, Mechanical Pain Threshold; PDI, Pain Disability Index; PF, subscale Physical Functioning; QST, Quantitative Sensory Testing; RMSSD, Root Mean Square of Successive Differences; VAS, Visual Analogue Scale; WUR, Wind-Up Ratio.

Table 4

Results of multiple regression analyses (longitudinal)

	$\Delta$ Lifting capacity ( $n=$ 42) ${}^{{\dagger}}$			$\Delta$ Physical functioning ( $n=$ 40)			$\Delta$ Disability ( $n=$ 32) ${}^{{\dagger}}$			$\Delta$ Work ability ( $n=$ 41) ${}^{{\dagger}}$
	B	[95% CI]	$r_{\textit{partial}}$	B	[95% CI]	$r_{\textit{partial}}$	B	[95% CI]	$r_{\textit{partial}}$	B	[95% CI]	$r_{\textit{partial}}$
(Constant)	13.81	[ $-$ 10.32, 37.93]		12.73	[ $-$ 3.18, 28.63]		$-$ 18.70	[ $-$ 40.13, 2.74]		13.36	[ $-$ 31.07, 57.80]
CSI
$\Delta$ CS-related symptoms (CSI-A)	$-$ 0.26	[ $-$ 1.10, 0.58]	$-$ 0.10	$-$ 0.15	[ $-$ 0.73, 0.43]	$-$ 0.09	0.77	[0.01, 1.53]	0.36*	$-$ 1.46	[ $-$ 2.99, 0.08]	$-$ 0.30
QST
$\Delta$ Sharp cutaneous pain sensation (MPT)	$-$ 0.03	[ $-$ 0.13, 0.07]	$-$ 0.11		–			–			–
$\Delta$ Blunt pressure pain sensation (PPT)		–			–			–		1.31	[ $-$ 0.51, 3.13]	0.23
$\Delta$ Touch sensation (MDT)		–		$-$ 0.01	[ $-$ 0.10, 0.08]	$-$ 0.03		–			–
$\Delta$ Temporal summation (WUR)		–			–		$-$ 0.21	[ $-$ 0.53, 0.10]	$-$ 0.25		–
HRV
$\Delta$ Parasympathetic/ vagal tone (RMSSD)	0.60	[0.24, 0.96]	0.48**	$-$ 0.02	[ $-$ 0.22, 0.19]	$-$ 0.03	$-$ 0.07	[ $-$ 0.37, 0.24]	$-$ 0.08	$-$ 0.57	[ $-$ 1.32, 0.18]	$-$ 0.25
$\Delta$ Assessor’s observed exertion (CR-10)	0.37	[0.00, 0.73]	0.32*		–			–			–
$\Delta$ Catastrophizing (PCS)		–		$-$ 0.42	[ $-$ 0.76, $-$ 0.07]	$-$ 0.38*		–			–
$\Delta$ Lifting capacity		–			–			–		0.75	[0.16, 1.35]	0.39*

${}^{{\dagger}}$ : the model does not fulfill all the regression assumptions. –: not tested. Significance level of the introduced variables in the final regression models: *, $p<$ 0.05; **, $p<$ 0.01; *** $p<$ 0.001. Abbreviations: CS, Central Sensitization; CSI-A, Central Sensitization Inventory part A; HRV, Heart Rate Variability; MDT, Mechanical Detection Threshold; MPT, Mechanical Pain Threshold; PCS, Pain Catastrophizing Scale; PPT, Pressure Pain Threshold; QST, Quantitative Sensory Testing; RMSSD, Root Mean Square of Successive Differences; WAS, Work Ability Score; WUR, Wind-Up Ratio.

regular follow-ups, is encouraged. It may be beneficial for better personalizing and regularly adjusting goal settings and treatment approaches, which would lead to improved treatment efficacy.

This research is the first of its kind as it has been performed with a comprehensive set of methods to assess CS phenomenon and functioning in patients with CLBP, both cross-sectionally and longitudinally. The measurements are implemented within the usual care and CS indicators are assessed with state of the art methods-considered best available. Additionally, the functioning assessment in this study included a lifting test to complement the self-report outcomes, thus, better resembling usual care. The selection of one QST test (per highest correlation coefficient) to enter the regression models as representative, was a choice made to suit better the functioning outcome, although results could not be compared to other studies [16]. Nevertheless, the most informative somatosensory measure for each functioning measure was obtained and, seeing the heterogeneity in the models, it is assumed the loss of comparability is outweighed.

There are some limitations to consider in this study. The amount of patients participating was not sufficient to include confounders to the regression models for longitudinal analyses. The study had two measurement points which was insufficient for insights on the evolution of the association between CS and functioning. Delta calculation is vulnerable to regression to the mean; other options are available but have shortcomings as well. Three longitudinal models did not fulfill all the assumptions for regression analyses; although results are less robust, valuable insights on the diversity of the associations are obtained.

Future research can build on the strengths and overcome the limitations of this study, to replicate and assist in the ongoing unravelling of the relation between CS and functioning. It is recommended that studies do not rely on a single CS indicator or functioning measure, and use both self-report and performance-based. Studies should consider prospective cohort designs with more measurement points and larger study samples, whereby it might be possible to distinguish subgroups in patients with CLBP for whom different treatment approaches may be needed and different evolutions can be expected.

5. Conclusion

Some CS indicators were related to functioning in patients with CLBP and associations were weak-to-moderate and heterogeneous; they differed between CS indicators and functioning measures and from cross-sectional to longitudinal analyses. Because of this, the rehabilitation evaluation should include the assessment of underlying pain mechanisms, and the program goals may need regular adjustments to the current state of the patient.

Funding

Internal funding from the Rehabilitation Department UMCG was obtained for this study.

Supplementary materials

The appendices are available from https://dx-doi-org-s.web.bisu.edu.cn/ 10.3233/BMR-210322.

Footnotes

Acknowledgments

The authors wish to express their gratitude to the Pain Rehabilitation Team of the Center for Rehabilitation of the University Medical Center Groningen for their collaboration in the planning and assessments of the participants of this study, and to P.U. Dijkstra for the statistical support provided.

Conflict of interest

The authors declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

References

Rice

Smith

Blyth

. Pain and the global burden of disease. Pain [Internet]. 2016; 157(4): 791-6. Available from: http://content.wkhealth.com/linkback/openurl?sid=WKPTLP:landingpage&an=00006396-201604000-00006.

Waddell

. The Back Pain Revolution. Second. Edinburgh: Churchill Livingstone; 2004.

Vachalathiti

Sakulsriprasert

Kingcha

. Decreased Functional Capacity in Individuals with Chronic Non-Specific Low Back Pain: A Cross-Sectional Comparative Study. J Pain Res [Internet]. 2020; 13: 1979-86. Available from: http://www.ncbi.nlm.nih.gov/pubmed/32801853.

Ferreira

Machado

Latimer

Maher

Ferreira

Smeets

. Factors defining care-seeking in low back pain – A meta-analysis of population based surveys. Eur J Pain [Internet]. 2010; 14(7): 747. e1-747.e7. doi: 10.1016/j.ejpain.2009.11.005.

Foster

Anema

Cherkin

Chou

Cohen

Gross

, et al. Prevention and treatment of low back pain: evidence, challenges, and promising directions. Lancet [Internet]. 2018 Jun; 391(10137): 2368-83. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0140673618304896.

Woolf

. Central sensitization: implications for the diagnosis and treatment of pain. Pain [Internet]. 2011; 152(3 Suppl): S2-15. Available from: http://www.ncbi.nlm.nih.gov/pubmed/20961685.

den Boer

Dries

Terluin

van der Wouden

Blankenstein

van Wilgen

, et al. Central sensitization in chronic pain and medically unexplained symptom research: A systematic review of definitions, operationalizations and measurement instruments. J Psychosom Res [Internet]. 2019; 117: 32-40. Available from: doi: 10.1016/j.jpsychores.2018.12.010.

de Couck

Nijs

Gidron

. You May Need a Nerve to Treat Pain: The Neurobiological Rationale for Vagal Nerve Activation in Pain Management. Clin J Pain [Internet]. 2014; 30(12): 1099-105. Available from: http://content.wkhealth.com/linkback/openurl?sid=WKPTLP:landingpage&an=00002508-201412000-00012.

Martínez-Martínez

L-A

Mora

Vargas

Fuentes-Iniestra

Martínez-Lavín

. Sympathetic Nervous System Dysfunction in Fibromyalgia, Chronic Fatigue Syndrome, Irritable Bowel Syndrome, and Interstitial Cystitis. JCR J Clin Rheumatol [Internet]. 2014; 20(3): 146-50. Available from: http://content.wkhealth.com/linkback/openurl?sid=WKPTLP:landingpage&an=00124743-201404000-00007.

10.

Giesecke

Gracely

Grant

MAB

Nachemson

Petzke

Williams

, et al. Evidence of augmented central pain processing in idiopathic chronic low back pain. Arthritis Rheum [Internet]. 2004; 50(2): 613-23. Available from: doi: 10.1002/art.20063.

11.

Schiphorst Preuper

Boonstra

Wever

Heuts

PHTG

Dekker

JHM

Smeets

RJEM

, et al. Differences in the Relationship Between Psychosocial Distress and Self-Reported Disability in Patients With Chronic Low Back Pain in Six Pain Rehabilitation Centers in the Netherlands. Spine (Phila Pa 1976) [Internet]. 2011; 36(12). Available from: https://pubmed.ncbi.nlm.nih.gov/21192290/?from_single_result=Differences+in+the+relationship+between+psychosocial+distress+and+self-reported+disability+in+patients+with+chronic+low+back+pain+in+six+pain+rehabilitation+centers+in+the+Netherlands&expanded_s.

12.

Kregel

Schumacher

Dolphens

Malfliet

Goubert

Lenoir

, et al. Convergent Validity of the Dutch Central Sensitization Inventory: Associations with Psychophysical Pain Measures, Quality of Life, Disability, and Pain Cognitions in Patients with Chronic Spinal Pain. Pain Pract [Internet]. 2018; 18(6): 777-87. Available from: doi: 10.1111/papr.12672.

13.

Huysmans

Ickmans

Van Dyck

Nijs

Gidron

Roussel

, et al. Association Between Symptoms of Central Sensitization and Cognitive Behavioral Factors in People With Chronic Nonspecific Low Back Pain: A Cross-sectional Study. J Manipulative Physiol Ther [Internet]. 2018; 41(2): 92-101. Available from: doi: 10.1016/j.jmpt.2017.08.007.

14.

Cohen

Neumann

Shore

Amir

Cassuto

Buskila

. Autonomic dysfunction in patients with fibromyalgia: Application of power spectral analysis of heart rate variability. Semin Arthritis Rheum [Internet]. 2000; 29(4): 217-27. Available from: https://www-sciencedirect-com-443.web.bisu.edu.cn/science/article/pii/S0049017200800104?via%3Dihub.

15.

Gockel

Lindholm

Niemistö

Hurri

. Perceived disability but not pain is connected with autonomic nervous function among patients with chronic low back pain. J Rehabil Med [Internet]. 2008; 40(5): 355-8. Available from: https://medicaljournals.se/jrm/content/abstract/10.2340/16501977-0172.

16.

Hübscher

Moloney

Leaver

Rebbeck

McAuley

Refshauge

. Relationship between quantitative sensory testing and pain or disability in people with spinal pain – A systematic review and meta-analysis. Pain [Internet]. 2013 Sep; 154(9): 1497-504. Available from: http://content.wkhealth.com/linkback/openurl?sid=WKPTLP:landingpage&an=00006396-201309000-00006.

17.

Georgopoulos

Akin-Akinyosoye

Zhang

McWilliams

Hendrick

Walsh

. Quantitative sensory testing and predicting outcomes for musculoskeletal pain, disability, and negative affect. Vol. 160, Pain. 2019. pp. 1920-1932.

18.

Tanaka

Murata

Nishigami

Mibu

Manfuku

Shinohara

, et al. The central sensitization inventory predicts pain-related disability for musculoskeletal disorders in the primary care setting. Eur J Pain [Internet]. 2019; 23(9): 1640-8. Available from: doi: 10.1002/ejp.1443.

19.

Uddin

Woznowski-Vu

Flegg

Aternali

Wickens

Wideman

. Evaluating the novel added value of neurophysiological pain sensitivity within the fear-avoidance model of pain. Eur J Pain. 2019; 23(5): 957-72.

20.

Ansuategui Echeita

van der Wurff

Killen

Dijkhof

Grootenboer

Reneman

. Lifting capacity is associated with central sensitization and non-organic signs in patients with chronic back pain. Disabil Rehabil [Internet]. 2020; 0(0): 1-5. Available from: doi: 10.1080/09638288.2020.1752318.

21.

Brouwer

Dijkstra

Stewart

Göeken

LNH

Groothoff

Geertzen

JHB

. Comparing self-report, clinical examination and functional testing in the assessment of work-related limitations in patients with chronic low back pain. Disabil Rehabil [Internet]. 2005; 27(17): 999-1005. Available from: doi: 10.1080/09638280500052823.

22.

Reneman

Jorritsma

Schellekens

JMH

Göeken

LNH

. Concurrent validity of questionnaire and performance-based disability measurements in patients with chronic nonspecific low back pain. J Occup Rehabil [Internet]. 2002; 12(3): 119-29. Available from: http://www.ncbi.nlm.nih.gov/pubmed/12228943.

23.

Ansuategui Echeita

Schiphorst Preuper

Dekker

Stuive

Timmerman

Wolff

, et al. Central Sensitisation and functioning in patients with chronic low back pain: protocol for a cross-sectional and cohort study. BMJ Open [Internet]. 2020; 10(3): e031592. Available from: doi: 10.1136/bmjopen-2019-031592.

24.

General Assembly of the World Medical Association. World Medical Association Declaration of Helsinki: Ethical principles for medical research involving human subjects. J Am Coll Dent [Internet]. 2014; 81(3): 14-8. Available from: http://www.ncbi.nlm.nih.gov/pubmed/25951678.

25.

von Elm

Altman

Egger

Pocock

Gøtzsche

Vandenbroucke

. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: Guidelines for Reporting Observational Studies. Ann Intern Med [Internet]. 2007; 147(8): 573. Available from: doi: 10.7326/0003-4819-147-8-200710160-00010.

26.

World Health Organization. ICD-11 – Mortality and Morbidity Statistics [Internet]. 2019; [cited 2019 Oct 16]. Available from: https://icd.who.int/browse11/l-m/en#/http://id.who.int/icd/entity/1236923870.

27.

Matheson

Mooney

Grant

Affleck

Hall

Melles

, et al. A Test to Measure Lift Capacity of Physically Impaired Adults Part 1 – Development and Reliability Testing. Spine (Phila Pa 1976) [Internet]. 1995 Oct; 20(19): 2119-29. Available from: http://journals.lww.com/00007632-199510000-00010.

28.

Isernhagen

. Functional capacity evaluation: Rationale, procedure, utility of the kinesiophysical approach. J Occup Rehabil [Internet]. 1992 Sep; 2(3): 157-68. Available from: doi: 10.1007/BF01077187.

29.

Borg

. Borg’s perceived exertion and pain scales. [Internet]. Champaign, IL, US: Human Kinetics; 1998. Available from: http://psycnet.apa.org/record/1998-07179-000.

30.

Reneman

Fokkens

Dijkstra

Geertzen

JHB

Groothoff

. Testing Lifting Capacity: Validity of Determining Effort Level by Means of Observation. Spine (Phila Pa 1976) [Internet]. 2005; 30(2): E40-6. Available from: https://insights.ovid.com/crossref?an=00007632-200501150-00020.

31.

Brouwer

Reneman

Dijkstra

Groothoff

Schellekens

JMH

Göeken

LNH

. Test-Retest Reliability of the Isernhagen Work Systems Functional Capacity Evaluation in Patients with Chronic Low Back Pain. J Occup Rehabil [Internet]. 2003; 13(4): 207-18. Available from: doi: 10.1023/A1026264519996.

32.

Kuijer

PPFM

Gouttebarge

Brouwer

Reneman

Frings-Dresen

MHW

. Are performance-based measures predictive of work participation in patients with musculoskeletal disorders? A systematic review. Int Arch Occup Environ Health [Internet]. 2012 Feb 10; 85(2): 109-23. Available from: doi: 10.1007/s00420-011-0659-y.

33.

Hays

Morales

. The RAND-36 measure of health-related quality of life. Ann Med. 2001; 33(5): 350-7.

34.

van der Zee

Sanderman

. RAND-36. umcgnl. [Internet]. Available from: https://www.umcg.nl/SiteCollectionDocuments/research/institutes/SHARE/assessmenttools/handleiding_rand36_2e_druk.pdf.

35.

Tait

Chibnall

Krause

. The Pain Disability Index: psychometric properties. Pain [Internet]. 1990; 40: 171-82. Available from: https://www-sciencedirect-com-443.web.bisu.edu.cn/science/article/pii/030439599090068O.

36.

Soer

Köke

AJA

Vroomen

PCAJ

Stegeman

Smeets

RJEM

Coppes

, et al. Extensive Validation of the Pain Disability Index in 3 Groups of Patients With Musculoskeletal Pain. Spine (Phila Pa 1976) [Internet]. 2013; 38(9): E562-8. Available from: http://content.wkhealth.com/linkback/openurl?sid=WKPTLP:landingpage&an=00007632-201304200-00022.

37.

El Fassi

Bocquet

Majery

Lair

Couffignal

Mairiaux

. Work ability assessment in a worker population: comparison and determinants of Work Ability Index and Work Ability score. BMC Public Health [Internet]. 2013; 13: 305-14. Available from: http://www.ncbi.nlm.nih.gov/pubmed/23565883.

38.

Ahlstrom

Grimby-Ekman

Hagberg

Dellve

. The work ability index and single-item question: associations with sick leave, symptoms, and health – A prospective study of women on long-term sick leave. Scand J Work Environ Heal [Internet]. 2010; 36(5): 404-12. Available from: https://www-jstor-org.web.bisu.edu.cn/stable/40967876.

39.

Kinnunen

Nätti

. Work ability score and future work ability as predictors of register-based disability pension and long-term sickness absence: A three-year follow-up study. Scand J Public Health [Internet]. 2018; 46(3): 321-30. Available from: doi: 10.1177/1403494817745190.

40.

Mayer

Neblett

Cohen

Howard

Choi

Williams

, et al. The development and psychometric validation of the central sensitization inventory. Pain Pract [Internet]. 2012; 12(4): 276-85. Available from: http://www.ncbi.nlm.nih.gov/pubmed/21951710.

41.

Kregel

Vuijk

Descheemaeker

Keizer

van der Noord

Nijs

, et al. The Dutch Central Sensitization Inventory (CSI) Factor Analysis, Discriminative Power, and Test-Retest Reliability. Clin J Pain [Internet]. 2016; 32(7): 624-30. Available from: https://insights.ovid.com/pubmed?pmid=26418360.

42.

Rolke

Baron

Maier

Tölle

Treede

R-D

Beyer

, et al. Quantitative sensory testing in the German Research Network on Neuropathic Pain (DFNS): Standardized protocol and reference values. Pain [Internet]. 2006; 123(3): 231-43. Available from: https://www-sciencedirect-com-443.web.bisu.edu.cn/science/article/pii/S0304395906001527.

43.

Wilder-Smith

. A paradigm-shift in pain medicine: implementing a systematic approach to altered pain processing in everyday clinical practice based on quantitative sensory testing [Internet]. Aalborg University; 2013. Available from: http://vbn.aau.dk/files/103432008/DoctoralThesis_Oliver_Wilder_Smith.pdf.

44.

McCraty

Shaffer

. Heart Rate Variability: New Perspectives on Physiological Mechanisms, Assessment of Self-regulatory Capacity, and Health Risk. Glob Adv Heal Med [Internet]. 2015; 4(1): 46-61. Available from: doi: 10.7453/gahmj.2014.073.

45.

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 [Internet]. 1996; 93(5): 1043-65. Available from: https://ci.nii.ac.jp/naid/10005435343/.

46.

HeartMath Inc. emWave Pro Plus Assessments [Internet]. 2018 [cited 2019 Feb 27]. Available from: https://heartcloud.com/library/asmts.html.

47.

Laborde

Mosley

Thayer

. Heart Rate Variability and Cardiac Vagal Tone in Psychophysiological Research – Recommendations for Experiment Planning, Data Analysis, and Data Reporting. Front Psychol [Internet]. 2017; 8(213). Available from: http://journal.frontiersin.org/article/10.3389/fpsyg.2017.00213/full.

48.

Hawker

Mian

Kendzerska

French

. Measures of adult pain: Visual Analog Scale for Pain (VAS Pain), Numeric Rating Scale for Pain (NRS Pain), McGill Pain Questionnaire (MPQ), Short-Form McGill Pain Questionnaire (SF-MPQ), Chronic Pain Grade Scale (CPGS), Short Form-36 Bodily Pain Scale (SF. Arthritis Care Res [Internet]. 2011; 63(S11): S240-52. Available from: doi: 10.1002/acr.20543.

49.

Crombez

Vlaeyen

JWS

. Pain Catastrophizing Scale (PCS) – Dutch Version (PCS-DV) [Internet]. 1996, Available from: https://meetinstrumentenzorg.blob.core.windows.net/test-documents/Instrument197/197_3_N.pdf.

50.

van Damme

Crombez

Vlaeyen

JWS

Goubert

van den Broeck

van Houdenhove

. De Pain Catastrophizing Scale: Psychometrische karakteristieken en normering. Gedragstherapie [Internet]. 2000; 33: 209-20. Available from: https://hdl-handle-net.web.bisu.edu.cn/1854/LU-132608.

51.

van Wilgen

Nijs

Don

Vuijk

. The Injustice Experience Questionnaire: Nederlandstalige consensusvertaling [Internet]. 2014, Available from: http://www.paininmotion.be/storage/app/media//materials/IEQ-Dutch.pdf.

52.

Rodero

Luciano

Montero-Marín

Casanueva

Palacin

Gili

, et al. Perceived injustice in fibromyalgia: Psychometric characteristics of the Injustice Experience Questionnaire and relationship with pain catastrophising and pain acceptance. J Psychosom Res [Internet]. 2012; 73(2): 86-91. Available from: https://www-sciencedirect-com-443.web.bisu.edu.cn/science/article/pii/S0022399912001493.

53.

de Beurs

Zitman

. The Brief Symptom Inventory (BSI): Reliability and validity of a practical alternative to SCL-90. Maandbl Geestelijke Volksgezond [Internet]. 2006; (61): 120-41. Available from: https://www.researchgate.net/publication/284679116_The_Brief_Symptom_Inventory_BSI_Reliability_and_validity_of_a_practical_alternative_to_SCL-90.

54.

Derogatis

. BSI brief symptom inventory: Administration, Scoring, and Procedure Manual [Internet]. 4th ed. Minneapolis MN: National Computer Systems. 1993. Available from: https://hazards.colorado.edu/nhcdata/chernobyl/ChData/ScalesInstruments/Scales and Indices/Scale Construction Instructions/BSI.pdf%0Ahttp://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:Brief+Symptom+Inventory#0.

55.

U.S. Department of Labor E and TA. Dictionary of Occupational Titles. 4th ed. Washington; 1991.

56.

Baron

Maier

Attal

Binder

Bouhassira

Cruccu

, et al. Peripheral neuropathic pain: a mechanism-related organizing principle based on sensory profiles. Pain [Internet]. 2017 Feb; 158(2): 261-72. Available from: doi: 10.1097/j.pain.0000000000000753.

57.

Ansuategui Echeita

Bethge

van Holland

Gross

Kool

Oesch

, et al. Functional Capacity Evaluation in Different Societal Contexts: Results of a Multicountry Study. J Occup Rehabil [Internet]. 2018; 29(1): 222-36. Available from: doi: 10.1007/s10926-018-9782-x.

58.

Magerl

Krumova

Baron

Tölle

Treede

R-D

Maier

. Reference data for quantitative sensory testing (QST): Refined stratification for age and a novel method for statistical comparison of group data. Pain. 2010 Dec; 151(3): 598-605. Available from: http://content.wkhealth.com/linkback/openurl?sid=WKPTLP:landingpage&an=00006396-201012000-00011.

59.

Peduzzi

Concato

Feinstein

Holford

. Importance of events per independent variable in proportional hazards regression analysis. II. Accuracy and precision of regression estimates. J Clin Epidemiol [Internet]. 1995; 48(12): 1503-10. Available from: http://www.ncbi.nlm.nih.gov/pubmed/8543964.

60.

Cohen

. Statistical Power Analysis for the Behavioral Sciences [Internet]. 2nd ed. Hillsdale, NJ: Lawrence Erlbaum Associates; 1988. 567 p. Available from: https://www-taylorfrancis-com-443.web.bisu.edu.cn/books/9780203771587.

61.

Hartvigsen

Hancock

Kongsted

Louw

Ferreira

Genevay

, et al. What low back pain is and why we need to pay attention. Lancet [Internet]. 2018; 391(10137): 2356-67. Available from: http://www.ncbi.nlm.nih.gov/pubmed/29573870.

62.

Bid

Soni

Rathod

. Central sensitization in chronic low back pain: a narrative review. NJIRM [Internet]. 2016; 7(3): 114-23. Available from: https://www.researchgate.net/profile/Dibyendunarayan_Bid/publication/305604391_Central_Sensitization_In_Chronic_Low_Back_Pain_A_Narrative_Review/links/5794fc3908ae33e89f9a91d0/Central-Sensitization-In-Chronic-Low-Back-Pain-A-Narrative-Review.pdf.

63.

Andrews

Strong

Meredith

. Activity Pacing, Avoidance, Endurance, and Associations With Patient Functioning in Chronic Pain: A Systematic Review and Meta-Analysis. Arch Phys Med Rehabil [Internet]. 2012; 93(11): 2109-21. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0003999312004273.

Central sensitization and functioning in patients with chronic low back pain: A cross-sectional and longitudinal study

Abstract

BACKGROUND:

OBJECTIVE:

METHODS:

RESULTS:

CONCLUSION:

Keywords

1. Introduction

2. Materials and methods

2.1 Design

2.2 Participants

2.3 Measurements

2.3.1 Functioning

2.3.2 Central sensitization

2.3.3 Participants’ characteristics

2.4 Statistical analyses

Table 1 Participants’ demographic characteristics at baseline

Table 2 Participants’ functioning, CS and clinical characteristics from baseline, discharge and deltas

Table 3 Results of multiple regression analyses (cross-sectional)

Funding

Supplementary materials

Footnotes

Acknowledgments

Conflict of interest

References

Table 1
Participants’ demographic characteristics at baseline

Table 2
Participants’ functioning, CS and clinical characteristics from baseline, discharge and deltas

Table 3
Results of multiple regression analyses (cross-sectional)