Chronic low back pain is highly individualised: patterns of classification across three unidimensional subgrouping analyses

Effectiveness of simultaneous bilateral visual diaphragm biofeedback under low back pain: influence of age and sex

Introduction: The aim of the present study was to determine the effectiveness of simultaneous bilateral visual diaphragm biofeedback (BFB) from ultrasonography in conjunction with inspiratory muscle training (IMT) on diaphragmatic thickness during normal breathing and respiratory and clinical outcomes in patients with non-specific low back pain (NSLBP) and determine the influence of age and sex. Methods: A single-blind randomized clinical trial was carried out (NCT04582812). A total sample of 96 patients with NSLBP was recruited and randomized by sex-based stratification into IMT (n = 48) and BFB + IMT (n = 48) interventions over 8 weeks. Bilateral diaphragmatic thickness at maximum inspiration (Tins) and expiration (Texp), respiratory pressures, lung function, pain intensity, bilateral pressure pain threshold (PPT), disability, and quality of life were measured at baseline and after 8 weeks. Results: The BFB + IMT group showed significant differences (p < 0.05) with increased left hemidiaphragm thickness at Tins and Tins-exp (d = 0.38-053), and right and left PPT (d = 0.71-0.74) versus the IMT group. The interaction with sex was statistically significant (p = 0.007; F(1,81) = 7.756; ηp 2 = 0.087) and higher left hemidiaphragm thickness at Tins was predicted by the BFB + IMT group (R 2 = 0.099; β = 0.050; F(1,82) = 8.997; p = 0.004) and male sex (R 2 = 0.079; β = 0.045; F(1,81) = 7.756;p = 0.007). Furthermore, greater left hemidiaphragm thickness at Tins-exp was predicted by younger age (R 2 = 0.052; β = -0.001; F(1,82) = 4.540; p = 0.036). Discussion: The simultaneous bilateral visual diaphragm biofeedback by ultrasonography in conjunction with IMT was effective in both increasing the left diaphragmatic thickness during inspiration, which was positively influenced and predicted by male sex and younger age, and increasing the bilateral PPT of the paraspinal muscles in patients with NSLBP.

Musculoskeletal spine modeling in large patient cohorts: how morphological individualization affects lumbar load estimation

Introduction: Achieving an adequate level of detail is a crucial part of any modeling process. Thus, oversimplification of complex systems can lead to overestimation, underestimation, and general bias of effects, while elaborate models run the risk of losing validity due to the uncontrolled interaction of multiple influencing factors and error propagation. Methods: We used a validated pipeline for the automated generation of multi-body models of the trunk to create 279 models based on CT data from 93 patients to investigate how different degrees of individualization affect the observed effects of different morphological characteristics on lumbar loads. Specifically, individual parameters related to spinal morphology (thoracic kyphosis (TK), lumbar lordosis (LL), and torso height (TH)), as well as torso weight (TW) and distribution, were fully or partly considered in the respective models according to their degree of individualization, and the effect strengths of these parameters on spinal loading were compared between semi- and highly individualized models. T-distributed stochastic neighbor embedding (T-SNE) analysis was performed for overarching pattern recognition and multiple regression analyses to evaluate changes in occurring effects and significance. Results: We were able to identify significant effects (p < 0.05) of various morphological parameters on lumbar loads in models with different degrees of individualization. Torso weight and lumbar lordosis showed the strongest effects on compression (β ≈ 0.9) and anterior-posterior shear forces (β ≈ 0.7), respectively. We could further show that the effect strength of individual parameters tended to decrease if more individual characteristics were included in the models. Discussion: The induced variability due to model individualization could only partly be explained by simple morphological parameters. Our study shows that model simplification can lead to an emphasis on individual effects, which needs to be critically assessed with regard to in vivo complexity. At the same time, we demonstrated that individualized models representing a population-based cohort are still able to identify relevant influences on spinal loading while considering a variety of influencing factors and their interactions.

A Secondary Analysis of Gender Respiratory Features for Ultrasonography Bilateral Diaphragm Thickness, Respiratory Pressures, and Pulmonary Function in Low Back Pain

The aim of the present study was to determine the gender respiratory differences of bilateral diaphragm thickness, respiratory pressures, and pulmonary function in patients with low back pain (LBP). A sample of 90 participants with nonspecific LBP was recruited and matched paired by sex (45 women and 45 men). Respiratory outcomes included bilateral diaphragm thickness by ultrasonography, respiratory muscle strength by maximum inspiratory (MIP) and expiratory (MEP) pressures, and pulmonary function by forced expiratory volume during 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC spirometry parameters. The comparison of respiratory outcomes presented significant differences (p < 0.001), with a large effect size (d = 1.26-1.58) showing means differences (95% CI) for MIP of -32.26 (-42.99, -21.53) cm H2O, MEP of -50.66 (-64.08, -37.25) cm H2O, FEV1 of -0.92 (-1.18, -0.65) L, and FVC of -1.00 (-1.32, -0.69) L, with lower values for females versus males. Gender-based respiratory differences were presented for maximum respiratory pressures and pulmonary function in patients with nonspecific LBP. Women presented greater inspiratory and expiratory muscle weakness as well as worse lung function, although these differences were not linked to diaphragm thickness during normal breathing.

Societal beliefs about pain may be more balanced than previously thought. Results of the Guernsey pain survey

BACKGROUND

Musculoskeletal pain is multidimensional and associated with significant societal impact. Persistent or chronic pain is a public health priority. A step towards high-value care is a contemporary understanding of pain. While pain-related knowledge has been examined in specific conditions (e.g. neck pain) knowledge of the public's broader understanding regarding musculoskeletal pain per se, warrants investigation. This study examined the public's knowledge and beliefs regarding musculoskeletal pain and pain management.

METHODS

This observational cohort study was conducted in Guernsey (January 2019-February 2020). Participants (n = 1656; 76.0% female) completed an online questionnaire capturing: demographics, pain experience, work absenteeism, understanding of pain and pain management, multidimensional influences, physical activity, pain catastrophising and healthcare decision-making. Statements were deemed true/false/equivocal and mapped to biopsychosocial/biomedical/neutral perspectives based upon contemporary literature. Descriptive statistics were analysed for each statement. Participants' responses were examined for alignment to a contemporary viewpoint and themes within responses derived using a semi-quantitative approach modelled on direct content analysis. Comparisons between participants with/without pain were examined (χ2-squared/Wilcoxon Rank Sum test).

RESULTS

Within the cohort 83.6% reported currently experiencing pain. The overarching theme was perspectives that reflected both biomedical and contemporary, multidimensional understandings of pain. Sub-themes included uncertainty about pain persistence and evidence-based means to reduce recurrence, and reliance upon healthcare professionals for guiding decision-making. Compared to those with pain, those without had a greater belief that psychological interventions may help and lower pain catastrophising.

CONCLUSIONS

Participants' understanding of pain demonstrated both biomedical and multidimensional pain understanding consistent with elements of a contemporary understanding of pain.

Association of meeting 24-hour movement guidelines with low back pain among adults

Background

According to recently published 24-hour movement guidelines, adults should spend: ≥150 minutes/week in moderate-to-vigorous physical activity (MVPA); <8 hours/day in sedentary behaviour (SB); and 7-9 hours/day sleeping.

Objective

We explored the association between meeting these recommendations and low back pain (LBP)-the most common musculoskeletal disorder.

Methods

We collected self-reported data from 2333 adults about: MVPA, SB and sleep duration; frequency and intensity of LBP; and sociodemographic and lifestyle characteristics.

Results

Meeting a combination of SB and sleep recommendations was associated with lower odds of LBP in the past week and past month (adjusted odds ratio [OR]: 0.64 and 0.52, respectively; p < 0.05 for both). Among LBP sufferers, meeting any combination of recommendations that includes sleep was associated with lower odds of frequent (OR range: 0.49-0.61; p < 0.05 for all) and intense (OR range: 0.39-0.66; p < 0.05 for all) LBP in the past week, while meeting a combination of SB and sleep recommendations or all three recommendations was associated with lower odds of intense LBP in the past month and past year (OR range: 0.50-0.68; p < 0.05 for all). The likelihood of experiencing higher frequency and intensity of LBP decreased with the number of recommendations met (p for linear trend < 0.05).

Conclusion

Meeting the SB and sleep recommendations in combination is associated with a lower likelihood of LBP, while adhering to the overall 24-hour movement guidelines or any combination of recommendations that includes sleep is associated with lower frequency and intensity of LBP among LBP sufferers.

Towards data-driven biopsychosocial classification of non-specific chronic low back pain: a pilot study

The classification of non-specific chronic low back pain (CLBP) according to multidimensional data could guide clinical management; yet recent systematic reviews show this has not been attempted. This was a prospective cross-sectional study of participants with CLBP (n = 21) and age-, sex- and height-matched pain-free controls (n = 21). Nervous system, lumbar spinal tissue and psychosocial factors were collected. Dimensionality reduction was followed by fuzzy c-means clustering to determine sub-groups. Machine learning models (Support Vector Machine, k-Nearest Neighbour, Naïve Bayes and Random Forest) were used to determine the accuracy of classification to sub-groups. The primary analysis showed that four factors (cognitive function, depressive symptoms, general self-efficacy and anxiety symptoms) and two clusters (normal versus impaired psychosocial profiles) optimally classified participants. The error rates in classification models ranged from 4.2 to 14.2% when only CLBP patients were considered and increased to 24.2 to 37.5% when pain-free controls were added. This data-driven pilot study classified participants with CLBP into sub-groups, primarily based on psychosocial factors. This contributes to the literature as it was the first study to evaluate data-driven machine learning CLBP classification based on nervous system, lumbar spinal tissue and psychosocial factors. Future studies with larger sample sizes should validate these findings.

Interaction analyses: Enhancing understanding of chronic low back pain

BACKGROUND

Chronic low back pain (CLBP) is complex. Statistical examination of influences of exposures (e.g. characteristics) upon outcomes (e.g. pain) facilitates understanding of complexity and personalized care. Psychological factors may be associated with higher disability following exercise in CLBP. Examining interactions of psychological variables with exercise on disability might further understanding of CLBP.

OBJECTIVES

Secondary analysis of data from a CLBP cohort evaluating interactions between psychological variables and exercise on disability.

DESIGN

Longitudinal cohort study.

METHOD

Variables from a published prognostic model for disability: disability (baseline/one-year follow-up), psychological principal component scores (principal component score two (PC2) - Fear-avoidance beliefs, pain catastrophizing, pain self-efficacy; principal component score three (PC3) - thought suppression, behavioral endurance), exercise (during follow-up), forward-bending time, punishing significant other responses. Differences between exercisers and non-exercisers were assessed using Chi-Squared/Mann-Whitney tests. Multivariable linear regression models for follow-up disability included a term examining interaction between principal component scores and exercise.

RESULTS

Exercisers had significantly different scores for PC2 (p = .02) and PC3 (p = .03), lower baseline (p = .005) and follow-up pain intensity (p < .001), follow-up disability (p < .001) and faster forward-bend times (p = .014). There was no significant interaction between exercise and PC2 (p = .92) or PC3 (p = .75).

CONCLUSIONS

This study showed no interaction between psychological factors and exercise on disability at follow-up. These findings suggest that the disability outcome of people with CLBP who undertake exercise as an intervention does not differ from those who do not undertake exercise, irrespective of their baseline psychological status.

An Exploration of the Influence of Non-Biomechanical Factors on Lifting-Related LBP

Objective: The primary objective was to compare non-biomechanical factors between manual workers with and without a history of LBP related to lifting. A secondary objective was to investigate associations between the change in pain intensity during repeated lifting (termed pain ramp) and non-biomechanical factors tested in the LBP group. Methods: Manual workers currently in lifting occupations with and without a history of lifting-related LBP were recruited (21 LBP and 20 noLBP) and took part in a repeated (100) lift task. A series of non-biomechanical factors, including psychological, work-related, lifestyle, whole health and psychophysical factors, were collected. Psychophysical factors (pressure pain thresholds (PPTs) and fatigue) were also measured at different time points. Associations between pain ramp during lifting and non-biomechanical factors were investigated with linear regression. Results: The LBP group reported worse perceived sleep quality, more musculoskeletal pain sites other than LBP and greater symptoms related to gastrointestinal complaints and pseudo-neurology compared to the group with no history of LBP. The group with LBP were also slightly more worried about the lifting task and felt more fatigued at the end of the lifting task. The feeling of fatigue during lifting was positively associated with pain ramp in the LBP group. Anxiety and gastrointestinal complaints were weakly negatively associated with pain ramp during lifting. Conclusions: The group differences of poorer perceived sleep, greater non-specific health complaints, slightly more worry about the lifting task and more perceived fatigue in the LBP group highlight the complex and multi-factorial nature of LBP related to lifting. The feeling of fatigue was positively associated with pain ramp in the LBP group, suggesting a close relationship with pain and fatigue during lifting that requires further exploration.

Chronic back pain sub-grouped via psychosocial, brain and physical factors using machine learning

Chronic back pain (CBP) is heterogenous and identifying sub-groups could improve clinical decision making. Machine learning can build upon prior sub-grouping approaches by using a data-driven approach to overcome clinician subjectivity, however, only binary classification of pain versus no-pain has been attempted to date. In our cross-sectional study, age- and sex-matched participants with CBP (n = 4156) and pain-free controls (n = 14,927) from the UkBioBank were included. We included variables of body mass index, depression, loneliness/social isolation, grip strength, brain grey matter volumes and functional connectivity. We used fuzzy c-means clustering to derive CBP sub-groups and Support Vector Machine (SVM), Naïve Bayes, k-Nearest Neighbour (kNN) and Random Forest classifiers to determine classification accuracy. We showed that two variables (loneliness/social isolation and depression) and five clusters were optimal for creating sub-groups of CBP individuals. Classification accuracy was greater than 95% for when CBP sub-groups were assessed only, while misclassification in CBP sub-groups increased to 35-53% across classifiers when pain-free controls were added. We showed that individuals with CBP could sub-grouped and accurately classified. Future research should optimise variables by including specific spinal, psychosocial and nervous system measures associated with CBP to create more robust sub-groups that are discernible from pain-free controls.

The effectiveness of post-professional physical therapist training in the treatment of chronic low back pain using a propensity score approach with machine learning

RATIONALE

Low back pain (LBP) is a leading cause of disability in the United States creating substantial hardships through negative social, financial, and health effects. Chronic low back pain (CLBP) accounted for above half of patients treated in physical therapy (PT) clinics for LBP. However, research shows small benefit from PT in CLBP treatment. Preliminary evidence suggests clinician-level training variables may affect outcomes, but requires further investigation to determine whether patients with CLBP benefit from treatment by providers with post-professional training. This study examined the relationship between clinician training levels and patient-reported outcomes in CLBP treatment.

METHODS

Physical therapies were surveyed using a large patient outcome assessment system to determine and categorise them by level of post-professional education. To account for the possibility that clinicians with higher levels of training are referred more-complex patients, a machine learning approach was used to identify predictive variables for clinician group, then to construct propensity scores to account for differences between groups. Differences in functional status score change among pooled data were analysed using linear models adjusted for propensity scores.

RESULTS

There were no clinically meaningful differences in patient outcomes when comparing clinician post-professional training level. The propensity score method proved to be a valuable way to account for differences at baseline between groups.

CONCLUSION

Post-professional training does not appear to contribute to improved patient outcomes in the treatment of CLBP. This study demonstrates that propensity score analysis can be used to ensure that differences observed are true and not due to differences at baseline.

Back pain treatment: a new perspective

This article aims to provide new perspectives for the treatment of low back pain (LBP). A narrative literature review highlights the treatment strategies currently anchored in the guidelines as well as the extensive attempts to identify subgroups within the non-specific low back pain (NSLBP) classification. A variety of multimodal approaches exist for both diagnostic assessments and therapy approaches. Nonetheless, there are often gaps in the classification systems as well as in published treatment concepts with regard to the implementation of musculoskeletal functional disorders. Indeed, a growing body of evidence shows that more holistic and flexible approaches are needed to individually diagnose and target the complexity of LBP. As an example, both a diagnostic and a (independently developed) therapeutic LBP concept will be presented and discussed. Ultimately, guidelines and subgroup classification systems can only reflect the complexity of LBP, if they capture its entire multidimensional and biopsychosocial character in both the diagnostic and therapeutic processes. Furthermore, the expansion of the pain definition to include the nociplastic pain mechanism, as an important driver of LBP, has the potential to provide important impulses for further necessary research. In conclusion, the implementation of a functional musculoskeletal approach along with the emerging nociceptive pain concept in individually targeted holistic approaches seems to be the successful way to deal with the complexity of LBP.

Development and content validity of a rating scale for the pain and disability drivers management model

Background

Establishing the biopsychosocial profile of patients with low back pain (LBP) is essential to personalized care. The Pain and Disability Drivers Management model (PDDM) has been suggested as a useful framework to help clinicians establish this biopsychosocial profile. Yet, there is no tool to facilitate its integration into clinical practice. Thus, the aim of this study is to develop a rating scale and validate its content, to rapidly establish the patient’s biopsychosocial profile, based on the five domains of the PDDM.

Methods

The tool was developed in accordance with the principles of the COSMIN methodology. We conducted three steps: 1) item generation from a comprehensive review, 2) refinement of the scale with clinicians’ feedback, and 3) statistical analyses to assess content validity.

To validate the item assessing with Likert scales, we performed Item level-Content Validity Index (I-CVI) analyses on three criteria (clarity, presentation and clinical applicability) with an a priori threshold of > 0.78. We conducted Average-Content Validity Index (Ave-CVI) analyses to validate the overall scale with a threshold of > 0.9.

Results

In accordance with the PDDM, we developed a 5-item rating scale (1 per domain) with 4 score options. We selected clinical instruments to screen for the presence or absence of problematic issues within each category of the 5 domains. Forty-two participants provided feedback to refine the scale’s clarity, presentation, and clinical applicability. The statistical analysis of the latest version presented I-CVI above the threshold for each item (I-CVI ranged between 0.94 and 1). Analysis of the overall scale supported its validation (Ave-CVI = 0.96 [0.93;0.98]).

Conclusion

From the 51 biopsychosocial elements contained within the 5 domains of the PDDM, we developed a rating scale that allows to rapidly screen for problematic issues within each category of the PDDM’s 5 domains. Involving clinicians in the process allowed us to validate the content of the first scale to establish the patient’s biopsychosocial profile for people with low back pain. Future steps will be necessary to continue the psychometric properties analysis of this rating scale.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40945-022-00137-2.

"I Don't Know Why I've Got this Pain!" Allostasis as a Possible Explanatory Model

Explaining the onset and maintenance of pain can be challenging in many clinical presentations. Allostasis encompasses the mechanisms through which humans adapt to stressors to maintain physiological stability. Due to related neuro-endocrine-immune system effects, allostasis and allostatic load (the cumulative effects on the brain and body that develop through the maintenance of physiological stability) offer the potential to explain the development and maintenance of musculoskeletal pain in certain cases. This paper outlines the concept of allostatic load, highlights the evidence for allostatic load in musculoskeletal pain conditions to date, and discusses mechanisms through which allostatic load influences pain, with particular focus on hypothalamic-pituitary-adrenal axis and sympathetic nervous system function and central, brain-driven governance of these systems. Finally, through case examples, consideration is given as to how allostatic load can be integrated into clinical reasoning and how it can be used to help explain pain to individuals and guide clinical decision-making.

IMPACT

Awareness of the concept of allostatic load, and subsequent assessment of physical and psychological stressors potentially contributing to allostatic load, may facilitate a broader understanding of the multidimensional presentations of many people with pain, both acute and persistent. This may facilitate discussion between clinicians and their patients regarding broader influences on their presentations and drive more targeted and inclusive pain management strategies.

Profiling and Association over Time between Disability and Pain Features in Patients with Chronic Nonspecific Neck Pain: A Longitudinal Study

OBJECTIVES

To longitudinally investigate the relationships between neck/arm disability and pain profile measures in individuals with chronic nonspecific neck pain (NSNP) at baseline, one month, and six months after a standardized physiotherapy intervention. A secondary aim was to compare pain sensitivity of individuals with chronic NSNP at baseline to healthy controls.

METHODS

A total of sixty-eight individuals with chronic NSNP and healthy controls were recruited. Neck disability index (NDI), the 11-item disabilities of the arm, shoulder, and hand questionnaire (QuickDASH), temporal summation (TS), pressure pain thresholds (PPTs), pain intensity and pain extent were assessed in individuals with chronic NSNP. For the cross-sectional assessment, TS and PPTs were compared to healthy controls.

RESULTS

After following a standardized physiotherapy intervention, local and distal PPTs to the neck region decreased at one and six month follow-ups, respectively. Pain extent decreased at one and six months. Furthermore, a positive correlation between neck/arm disability and pain intensity was found at baseline, whereas moderate positive correlations (e.g., between NDI and pain extent) at baseline, one and six month follow-ups and negative correlations at six months (e.g., between arm disability and PPTs) were found.

DISCUSSION

Overall, these findings indicate that pain sensitivity can worsen following treatment despite reduced pain extent and unchanged neck disability and pain intensity scores over a six-month period in individuals with chronic NSNP.

Classification Approaches for Treating Low Back Pain Have Small Effects That Are Not Clinically Meaningful: A Systematic Review With Meta-analysis

OBJECTIVE

To determine whether classification systems improve patient-reported outcomes for people with low back pain (LBP).

DESIGN

Systematic review with meta-analysis.

LITERATURE SEARCH

The MEDLINE, Embase, CINAHL, Web of Science Core Collection, and Cochrane Central Register of Controlled Trials databases were searched from inception to June 21, 2021. Reference lists of prior systematic reviews and included trials were screened.

STUDY SELECTION CRITERIA

We included randomized trials comparing a classification system (eg, the McKenzie method or the STarT Back Tool) to any comparator. Studies evaluating participants with specific spinal conditions (eg, fractures or tumors) were excluded.

DATA SYNTHESIS

Outcomes were patient-reported LBP intensity, leg pain intensity, and disability. We used the revised Cochrane Collaboration Risk of Bias Tool to assess risk of bias, and the Grading of Recommendations Assessment, Development and Evaluation approach to judge the certainty of evidence. We used random-effects meta-analysis, with the Hartung-Knapp-Sidik- Jonkman adjustment, to estimate the standardized mean difference (SMD; Hedges' g) and 95% confidence interval (CI). Subgroup analyses explored classification system, comparator type, pain type, and pain duration.

RESULTS

Twenty-four trials assessing classification systems and 34 assessing subclasses were included. There was low certainty of a small effect at the end of intervention for LBP intensity (SMD, -0.31; 95% CI: -0.54, -0.07; P = .014, n = 4416, n = 21 trials) and disability (SMD, -0.27; 95% CI: -0.46, -0.07; P = .011, n = 4809, n = 24 trials), favoring classified treatments compared to generalized interventions, but not for leg pain intensity. At the end of intervention, no specific type of classification system was superior to generalized interventions for improving pain intensity and disability. None of the estimates exceeded the effect size that one would consider clinically meaningful.

CONCLUSION

For patient-reported pain intensity and disability, there is insufficient evidence supporting the use of classification systems over generalized interventions when managing LBP. J Orthop Sports Phys Ther 2022;52(2):67-84. Epub 15 Nov 2021. doi:10.2519/jospt.2022.10761.

Significant other interactions in people with chronic low back pain: Subgrouping and multidimensional profiles

Background: Back pain is complex. Social support and significant other interactions influence the pain experience. Purpose: To statistically derive subgroups of people with chronic low back pain based upon their interactions with significant others, and profile subgroups across multidimensional variables. Research Design: Longitudinal cohort study. Study Sample: People with chronic axial low back pain ( n = 262). Data Collection and Analysis: Latent class analysis of significant other interaction data was used to derive subgroups of people with chronic low back pain. Subgroups were profiled across baseline multidimensional variables and one-year follow-up pain intensity, disability and bothersomeness. Results: Three clusters were identified: Cluster 1 (7.6%) characterised by the lowest distracting, punishing and solicitous interactions. Cluster 2 (16.0%) characterised by the highest distracting and solicitous responses and social support. Cluster 3 (76.3%) characterised by the highest punishing and lowest social support. Cluster 1 reported less disability than Clusters 2 and 3. Mindfulness was significantly different across all subgroups with Cluster 1 being most mindful and Cluster 3 least mindful. Depression, anxiety and stress were significantly higher in Cluster 3 than Cluster 1. Pain catastrophising was higher for Cluster 2 than Clusters 1 and 3. Cluster 2 had lower pressure pain threshold than Clusters 1 and 3. Conclusions: These results support the association between significant other interactions and the experience of back pain. Considering significant other interactions in clinical practice may be important for managing some people’s presentation.

Pain and Disability in Low Back Pain Can be Reduced Despite No Significant Improvements in Mechanistic Pain Biomarkers

OBJECTIVE

Altered balance in nociception in response to noxious stimuli is commonly reported in chronic low back pain (LBP). However, it is unclear whether an improvement in the clinical presentation is contingent on a reduction in pain sensitivity. This study investigated whether the quantitative sensory testing (QST) profile changes in people undergoing rehabilitation for LBP.

DESIGN

A prospective, observational case-control study.

METHODS

Forty males and females, 18 to 40 years' old (20 with LBP) participated in 2 sessions. QST was performed at baseline and after discharge from rehabilitation (LBP) or after 3 to 8 weeks (controls). The QST battery consisted of determining pressure-pain thresholds at the low back and shoulder, temporal summation of pain, and conditioned pain modulation. Questionnaire data was used to determine pain (Numeric Rating Scale [NRS]), disability (Roland-Morris Questionnaire [RMQ]), Fear Avoidance Beliefs (FABQ), and The Örebro Musculoskeletal Pain Screening Questionnaire (ÖMPSQ) at baseline and discharge. The treatment effect was determined by calculating the Cohen d.

RESULTS

No significant group×time interactions or main factor effect was found for any of the QST measures. The LBP group reported a significant reduction in NRS (P<0.0002, d=1.23), RMQ (P<0.0001, d=1.58), FABQ (P<0.001, d=0.87), and in the ÖMPSQ (P<0.00001, d=1.44).

CONCLUSIONS

The results indicate that an improvement of clinical LBP is not contingent upon changes in the pain sensory profile. The value of screening pain sensitivity in LBP patients in primary care, needs to be investigated further, due to the patient population heterogeneity and the sensitivity of assessment methods.

Do chronic low back pain subgroups derived from dynamic quantitative sensory testing exhibit differing multidimensional profiles?

OBJECTIVES

The relationship of pain sensitivity with pain and disability in low back pain (LBP) is complicated. It has been suggested increased understanding of dynamic quantitative sensory testing (QST) might be useful in increasing understanding of these relationships. This study aimed to create subgroups based on participant responses to dynamic QST, profile these subgroups based on multidimensional variables (including clinical measures of pain and disability, psychological and lifestyle variables and static QST), and investigate the association of subgroup membership with levels of pain intensity, LBP-related disability and disability risk at 12-month follow up.

METHODS

Participants (n=273) with dominant axial chronic non-specific LBP with duration of pain >3 months were included in this study. At baseline, eligible participants completed a self-report questionnaire to collect demographic, clinical, psychological and lifestyle data prior to dynamic and static QST. Dynamic QST measures were conditioned pain modulation (CPM) and temporal summation (TS). At 12-months follow up, clinical data were collected, including pain intensity and LBP-related disability. Sub-groups were formed by cross-tabulation. Analysis was undertaken to profile dynamic QST subgroup on demographic, clinical, psychological, lifestyle and static QST measures. Associations between dynamic QST subgroups and follow-up clinical variables were examined.

RESULTS

Based on dynamic QST, participants were allocated into four subgroups; normal CPM and normal TS (n=34, 12.5%); normal CPM and facilitated TS (n=6, 2.2%); impaired CPM and normal TS (n=186, 68.1%); impaired CPM and facilitated TS (n=47, 17.2%). At baseline no differences were demonstrated between subgroups across most clinical variables, or any psychological or lifestyle measures. The two subgroups with impaired CPM were more likely to have a higher number of painful body areas. Cold pain sensitivity was heightened in both the subgroups with facilitated TS. Subgroups did not differ across pain intensity, LBP-related disability and disability risk stratification at follow-up.

CONCLUSIONS

The profiles of people with axial LBP did not vary significantly across dynamic QST subgroups, save for those in groups with impaired CPM being more likely to have more widespread symptoms and those with facilitated TS having heightened cold pain sensitivity. Further, subgroup membership was not related to future pain and disability. The role of dynamic QST profiles in LBP remains unclear. Further work is required to understand the role of pain sensitivity in LBP. The utility of dynamic QST subgrouping might not be in determining of future disability. Future research might focus on treatment modifying effects of dynamic QST subgroups.

Endurance and avoidance response patterns in pain patients: Application of action control theory in pain research

BACKGROUND

Identifying pain-related response patterns and understanding functional mechanisms of symptom formation and recovery are important for improving treatment.

OBJECTIVES

We aimed to replicate pain-related avoidance-endurance response patterns associated with the Fear-Avoidance Model, and its extension, the Avoidance-Endurance Model, and examined their differences in secondary measures of stress, action control (i.e., dispositional action vs. state orientation), coping, and health.

METHODS

Latent profile analysis (LPA) was conducted on self-report data from 536 patients with chronic non-specific low back pain at the beginning of an inpatient rehabilitation program. Measures of stress (i.e., pain, life stress) and action control were analyzed as covariates regarding their influence on the formation of different pain response profiles. Measures of coping and health were examined as dependent variables.

RESULTS

Partially in line with our assumptions, we found three pain response profiles of distress-avoidance, eustress-endurance, and low-endurance responses that are depending on the level of perceived stress and action control. Distress-avoidance responders emerged as the most burdened, dysfunctional patient group concerning measures of stress, action control, maladaptive coping, and health. Eustress-endurance responders showed one of the highest levels of action versus state orientation, as well as the highest levels of adaptive coping and physical activity. Low-endurance responders reported lower levels of stress as well as equal levels of action versus state orientation, maladaptive coping, and health compared to eustress-endurance responders; however, equally low levels of adaptive coping and physical activity compared to distress-avoidance responders.

CONCLUSIONS

Apart from the partially supported assumptions of the Fear-Avoidance and Avoidance-Endurance Model, perceived stress and dispositional action versus state orientation may play a crucial role in the formation of pain-related avoidance-endurance response patterns that vary in degree of adaptiveness. Results suggest tailoring interventions based on behavioral and functional analysis of pain responses in order to more effectively improve patients quality of life.

Relationship between psychological factors and spinal motor behaviour in low back pain: a systematic review and meta-analysis

ABSTRACT

This meta-analysis investigated whether more negative psychological factors are associated with less spinal amplitude of movement and higher trunk muscle activity in individuals with low back pain. Furthermore, it examined whether pain intensity was a confounding factor in this relationship. We included studies that provided at least 1 correlation coefficient between psychological (pain-related fear, catastrophizing, depression, anxiety, and self-efficacy) and spinal motor behaviour (spinal amplitude and trunk muscle activity) measures. In total, 52 studies (3949 participants) were included. The pooled correlation coefficients (95% confidence interval; number of participants) were -0.13 (-0.18 to -0.09; 2832) for pain-related fear, -0.16 (-0.23 to -0.09; 756) for catastrophizing, -0.08 (-0.13 to -0.03; 1570) for depression, -0.08 (-0.30 to 0.14; 336) for anxiety, and -0.06 (-0.46 to 0.36; 66) for self-efficacy. The results indicated that higher levels of pain-related fear, catastrophizing, and depression are significantly associated with reduced amplitudes of movement and larger muscle activity and were consistent across subgroup and moderation analyses. Pain intensity did not significantly affect the association between these psychological factors and spinal motor behaviour and had a very small independent association with spinal motor behaviour. In conclusion, the very small effect sizes found in the meta-analyses question the role of psychological factors as major causes of spinal movement avoidance in low back pain. Experimental studies with more specific and individualized measures of psychological factors, pain intensity, and spinal motor behaviour are recommended.

'You’re the best liar in the world’: a grounded theory study of rowing athletes’ experience of low back pain

Objectives

Low back pain (LBP) is common in rowers and leads to considerable disability and even retirement. The athlete voice can help clinicians to better understand sport-related pain disorders. We aimed to capture the lived experience of LBP in rowers.

Methods

Cross-sectional qualitative study using a grounded theory approach. Adult competitive rowers with a rowing-related LBP history were recruited in Australia and Ireland. Data were collected through interviews that explored: context around the time of onset of their LBP and their subsequent journey, experiences of management/treatment, perspectives around present beliefs, fears, barriers and expectations for the future.

Results

The 25 rowers (12 women/13 men) who participated were aged 18–50 years; they had a mean 12.1 years of rowing experience. They discussed a culture of concealment of pain from coaches and teammates, and fear of being judged as ‘weak’ because of the limitations caused by LBP. They reported fear and isolation as a result of their pain. They felt that the culture within rowing supported this. They reported inconsistent messages regarding management from medical staff. Some rowers reported being in a system where openness was encouraged—they regarded this a leading to better outcomes and influencing their LBP experience.

Conclusions

Rowers’ lived experience of LBP was influenced by a pervasive culture of secrecy around symptoms. Rowers and support staff should be educated regarding the benefits of early disclosure and rowers should be supported to do so without judgement.

Six things you need to know about low back pain

Low back pain (LBP) is the leading contributor to years lived with disability, and imposes an enormous burden on individuals and on health-care systems. General practitioners and physiotherapists are generally the front-line health professionals dealing with patients with LBP, and have a key role in minimising its effect. Here we review six key issues associated with LBP including its effects, diagnosis and management in primary care, and highlight the importance of the biopsychosocial model and matched care for patients with LBP.

Adding Physical Impairment to Risk Stratification Improved Outcome Prediction in Low Back Pain

OBJECTIVE

Identifying subgroups of low back pain (LBP) has the potential to improve prediction of clinical outcomes. Risk stratification is one such strategy that identifies similar characteristics indicative of a common clinical outcome trajectory. The purpose of this study was to determine if an empirically derived subgrouping approach based on physical impairment measures improves information provided from the STarT Back Tool (SBT).

METHODS

At baseline in this secondary analysis of a cohort study, patients (N = 144) receiving physical therapy for LBP completed the SBT and tests (active lumbar flexion, extension, lateral bending, and passive straight-leg raise) from a validated physical impairment index. Clinical outcomes were assessed at 4 weeks and included the Numerical Pain Rating Scale and Oswestry Disability Index. Exploratory hierarchical agglomerative cluster analysis identified empirically derived subgroups based on physical impairment measures. Independent samples t testing and chi-square analysis were used to assess baseline subgroup differences in demographic and clinical measures. Spearman rho correlation coefficient was used to assess baseline SBT risk and impairment subgroup relationships, and a 3-way mixed-model ANOVA was used to assessed SBT risk and impairment subgroup relationships with clinical outcomes at 4 weeks.

RESULTS

Two physical impairment-based subgroups emerged from cluster analysis: (1) low-risk impairment (n = 119, 81.5%), characterized by greater lumbar mobility; and (2) high-risk impairment (n = 25, 17.1%), characterized by less lumbar mobility. A weak, positive relationship was observed between baseline SBT risk and impairment subgroups (rs = .170). An impairment-by-SBT risk-by-time interaction effect was observed for Oswestry Disability Index scores but not for Numerical Pain Rating Scale scores at 4 weeks.

CONCLUSIONS

Physical impairment subgroups were not redundant with SBT risk categories and could improve prediction of 4-week LBP disability outcomes. Physical impairment subgroups did not improve the prediction of 4-week pain intensity scores.

IMPACT

Subgroups based on physical impairment and psychosocial risk could lead to better prediction of LBP disability outcomes and eventually allow for treatment options tailored to physical and psychosocial risk.

Understanding and managing pelvic girdle pain from a person-centred biopsychosocial perspective

INTRODUCTION

Clinicians need support to effectively implement a biopsychosocial approach to people with pelvic girdle pain disorders.

PURPOSE

A practical clinical framework aligned with a contemporary biopsychosocial approach is provided to help guide clinician's management of pelvic girdle pain. This approach is consistent with current pain science which helps to explain potential mechanistic links with co/multi-morbid conditions related to pelvic girdle pain. Further, this approach also aligns with the Common-Sense Model of Illness and provides insight into how an individual's illness perceptions can influence their emotional and behavioural response to their pain disorder. Communication is critical to supporting recovery and facilitating behaviour change within the biopsychosocial context and in this context, the patient interview is central to exploring the multidimensional nature of a persons' presentation. Focusing the biopsychosocial framework on targeted cognitive-functional therapy as a key component of care can help an individual with pelvic girdle pain make sense of their pain, build confidence and self-efficacy and facilitate positive behaviour and lifestyle change. There is growing evidence of the efficacy for this broader integrative approach, although large scale effectiveness trials are still needed. An in-depth case study provides guidance for clinicians, showing 'how to' implement these concepts into their own practice within a coherent practical framework.

IMPLICATIONS

This framework can give clinicians more confidence in understanding and managing pelvic girdle pain. The framework provides practical strategies to assist clinicians with implementation; assisting the transition from knowing to doing in an evidence-informed manner that resonates with real world practice.

Artificial intelligence to improve back pain outcomes and lessons learnt from clinical classification approaches: three systematic reviews

Artificial intelligence and machine learning (AI/ML) could enhance the ability to detect patterns of clinical characteristics in low-back pain (LBP) and guide treatment. We conducted three systematic reviews to address the following aims: (a) review the status of AI/ML research in LBP, (b) compare its status to that of two established LBP classification systems (STarT Back, McKenzie). AI/ML in LBP is in its infancy: 45 of 48 studies assessed sample sizes <1000 people, 19 of 48 studies used ≤5 parameters in models, 13 of 48 studies applied multiple models and attained high accuracy, 25 of 48 studies assessed the binary classification of LBP versus no-LBP only. Beyond the 48 studies using AI/ML for LBP classification, no studies examined use of AI/ML in prognosis prediction of specific sub-groups, and AI/ML techniques are yet to be implemented in guiding LBP treatment. In contrast, the STarT Back tool has been assessed for internal consistency, test-retest reliability, validity, pain and disability prognosis, and influence on pain and disability treatment outcomes. McKenzie has been assessed for inter- and intra-tester reliability, prognosis, and impact on pain and disability outcomes relative to other treatments. For AI/ML methods to contribute to the refinement of LBP (sub-)classification and guide treatment allocation, large data sets containing known and exploratory clinical features should be examined. There is also a need to establish reliability, validity, and prognostic capacity of AI/ML techniques in LBP as well as its ability to inform treatment allocation for improved patient outcomes and/or reduced healthcare costs.

Pain can be conditioned to voluntary movements through associative learning: an experimental study in healthy participants

Experimental data suggest that associative learning can influence defensive avoidance behavior and pain perception in humans. However, whether voluntary movements can become conditioned stimuli (CSs) and influence pain responses is yet to be evaluated. Forty healthy volunteers participated in this study. Electrocutaneous stimuli applied to the shoulder at pain threshold level (US) and at pain tolerance level (US) were determined before a movement-conditioning paradigm. First, reaching movements to visual cues shown on one side of a computer screen were associated with the US (CS+ movements) on 80% of trials, whereas reaching movements to visual stimuli shown on the other side were never associated with the nociceptive-US (CS- movements). Next, participants underwent a test phase in which movements to visual cues on both sides were paired with the US on 50% of trials. During the test phase, participants were asked to evaluate whether the movement was painful (yes/no) and to rate pain intensity after each trial. Movement onset and duration as well as skin conductance responses were collected. The US stimuli were more likely to be perceived as painful and were also rated as more painful during CS+ movements. Movement onset latency and skin conductance responses were significantly higher in anticipation of the CS+ movement as compared to the CS- movement. These findings suggest that pain can be conditioned to voluntary movements.

Identifying non-specific low back pain clinical subgroups from sitting and standing repositioning posture tasks using a novel Cardiff Dempster-Shafer Theory Classifier

BACKGROUND

Low back pain (LBP) classification systems are used to deliver targeted treatments matched to an individual profile, however, distinguishing between different subsets of LBP remains a clinical challenge.

METHODS

A novel application of the Cardiff Dempster-Shafer Theory Classifier was employed to identify clinical subgroups of LBP on the basis of repositioning accuracy for subjects performing a sitting and standing posture task. 87 LBP subjects, clinically subclassified into flexion (n = 50), passive extension (n = 14), and active extension (n = 23) motor control impairment subgroups and 31 subjects with no LBP were recruited. Thoracic, lumbar and pelvic repositioning errors were quantified. The Classifier then transformed the error variables from each subject into a set of three belief values: (i) consistent with no LBP, (ii) consistent with LBP, (iii) indicating either LBP or no LBP.

FINDINGS

In discriminating LBP from no LBP the Classifier accuracy was 96.61%. From no-LBP, subsets of flexion LBP, active extension and passive extension achieved 93.83, 98.15% and 97.62% accuracy, respectively. Classification accuracies of 96.8%, 87.7% and 70.27% were found when discriminating flexion from passive extension, flexion from active extension and active from passive extension subsets, respectively. Sitting lumbar error magnitude best discriminated LBP from no LBP (92.4% accuracy) and the flexion subset from no-LBP (90.1% accuracy). Standing lumbar error best discriminated active and passive extension from no LBP (94.4% and 95.2% accuracy, respectively).

INTERPRETATION

Using repositioning accuracy, the Cardiff Dempster-Shafer Theory Classifier distinguishes between subsets of LBP and could assist decision making for targeted exercise in LBP management.