An exploration of familial associations of two movement pattern-derived subgroups of chronic disabling low back pain; a cross-sectional cohort study

© 2016 Elsevier Ltd. Background: Altered movement patterns with pain have been demonstrated in children, adolescents and adults with chronic disabling low back pain (CDLBP). A previously developed classification system has identified different subgroups including active extension and multidirectional patterns in patients with CDLBP. While familial associations have been identified for certain spinal postures in standing, it is unknown whether a familial relationship might exist between movement pattern-derived subgroups in families with CDLBP. Objectives: This study explored whether familial associations in movement pattern-derived subgroups within and between members of families with CDLBP existed. Design: Cross-sectional cohort study. Method: 33 parents and 28 children with CDLBP were classified into two subgroups based on clinical analysis of video footage of postures and functional movements, combined with aggravating factors obtained from Oswestry Disability Questionnaire. Prevalence of subgroups within family members was determined, associations between parent and child's subgroup membership was evaluated using Fisher's exact test, and spearman's correlation coefficient was used to determine the strength of association between familial dyads. Results: The majority of parents were classified as active extenders, sons predominately multidirectional and daughters were evenly distributed between the two subgroups. No significant association was found when comparing subgroups in nine parent-child relationships. Conclusions: The exploration of a small cohort of family dyads in this study demonstrated that children's movement pattern-derived subgroups could not be explained by their parents' subgroup membership. These results cannot be generalised to the CLBP population due to this study's small sample. Larger sample studies are needed to further elucidate this issue

Physiotherapists implicitly evaluate bending and lifting with a round back as dangerous

© 2018 Elsevier Ltd. Background: Beliefs can be assessed using explicit measures (e.g. questionnaires) that rely on information of which the person is ‘aware’ and willing to disclose. Conversely, implicit measures evaluate beliefs using computer-based tasks that allow reduced time for introspection thus reflecting ‘automatic’ associations. Thus far, physiotherapists’ beliefs about back posture and safety have not been evaluated with implicit measures. Objectives: (1) Evaluate implicit associations between bending lifting back posture (straight-back vs round-back) and safety (safe vs danger); (2) Explore correlations between implicit and explicit measures of beliefs towards vulnerability of the back. Design: Exploratory cross-sectional quantitative study. Methods: 47 musculoskeletal physiotherapists completed explicit measures of fear of movement (TSK-HC), back beliefs (BackPAQDanger) and beliefs related to bending and lifting back posture and safety (BSB). An Implicit Association Test (IAT) was used to assess implicit associations between (i) images of people bending/lifting with a ‘round-back’ or with a ‘straight-back’ posture, and (ii) words representing ‘safety’ and ‘danger’. A one-sample t-test assessed the degree and direction of the sample's IAT score. Cohen's d provided an effect size of the estimated bias. Correlation between IAT and each explicit measure was assessed using Pearson's coefficient. Results: The sample displayed an implicit association between ‘round-back’ and ‘danger’ (µ = 0.213, 95% CI [0.075-0.350], p =.003), with an effect size magnitude of 0.45. There were fair to moderate correlations between IAT and BSB (r = 0.320, 95% CI [0.036-0.556], p =.029) and, IAT and BackPAQDanger (r = 0.413, 95%CI [0.143-0.626], p =.004). Conclusions: Physiotherapists displayed an implicit bias towards bending and lifting with a round-back as dangerous

Human activity recognition for people with knee osteoarthritis—A proof‐of‐concept

Clinicians lack objective means for monitoring if their knee osteoarthritis patients are improving outside of the clinic (e.g., at home). Previous human activity recognition (HAR) models using wearable sensor data have only used data from healthy people and such models are typically imprecise for people who have medical conditions affecting movement. HAR models designed for people with knee osteoarthritis have classified rehabilitation exercises but not the clinically relevant activities of transitioning from a chair, negotiating stairs and walking, which are commonly monitored for improvement during therapy for this condition. Therefore, it is unknown if a HAR model trained on data from people who have knee osteoarthritis can be accurate in classifying these three clinically relevant activities. Therefore, we collected inertial measurement unit (IMU) data from 18 participants with knee osteoarthritis and trained convolutional neural network models to identify chair, stairs and walking activities, and phases. The model accuracy was 85% at the first level of classification (activity), 89–97% at the second (direction of movement) and 60–67% at the third level (phase). This study is the first proof‐of‐concept that an accurate HAR system can be developed using IMU data from people with knee osteoarthritis to classify activities and phases of activities

Optical coherence tomography-based contact indentation for diaphragm mechanics in a mouse model of transforming growth factor alpha induced lung disease

This study tested the utility of optical coherence tomography (OCT)-based indentation to assess mechanical properties of respiratory tissues in disease. Using OCT-based indentation, the elastic modulus of mouse diaphragm was measured from changes in diaphragm thickness in response to an applied force provided by an indenter. We used a transgenic mouse model of chronic lung disease induced by the overexpression of transforming growth factor-alpha (TGF-a), established by the presence of pleural and peribronchial fibrosis and impaired lung mechanics determined by the forced oscillation technique and plethysmography. Diaphragm elastic modulus assessed by OCT-based indentation was reduced by TGF-a at both left and right lateral locations (p < 0.05). Diaphragm elastic modulus at left and right lateral locations were correlated within mice (r = 0.67, p < 0.01) suggesting that measurements were representative of tissue beyond the indenter field. Co-localised images of diaphragm after TGF-a overexpression revealed a layered fibrotic appearance. Maximum diaphragm force in conventional organ bath studies was also reduced by TGF-a overexpression (p < 0.01). Results show that OCT-based indentation provided clear delineation of diseased diaphragm, and together with organ bath assessment, provides new evidence suggesting that TGF-a overexpression produces impairment in diaphragm function and, therefore, an increase in the work of breathing in chronic lung disease

Interpretable machine learning models for classifying low back pain status using functional physiological variables.

PURPOSE:To evaluate the predictive performance of statistical models which distinguishes different low back pain (LBP) sub-types and healthy controls, using as input predictors the time-varying signals of electromyographic and kinematic variables, collected during low-load lifting. METHODS:Motion capture with electromyography (EMG) assessment was performed on 49 participants [healthy control (con) = 16, remission LBP (rmLBP) = 16, current LBP (LBP) = 17], whilst performing a low-load lifting task, to extract a total of 40 predictors (kinematic and electromyographic variables). Three statistical models were developed using functional data boosting (FDboost), for binary classification of LBP statuses (model 1: con vs. LBP; model 2: con vs. rmLBP; model 3: rmLBP vs. LBP). After removing collinear predictors (i.e. a correlation of > 0.7 with other predictors) and inclusion of the covariate sex, 31 predictors were included for fitting model 1, 31 predictors for model 2, and 32 predictors for model 3. RESULTS:Seven EMG predictors were selected in model 1 (area under the receiver operator curve [AUC] of 90.4%), nine predictors in model 2 (AUC of 91.2%), and seven predictors in model 3 (AUC of 96.7%). The most influential predictor was the biceps femoris muscle (peak [Formula: see text]  = 0.047) in model 1, the deltoid muscle (peak [Formula: see text] =  0.052) in model 2, and the iliocostalis muscle (peak [Formula: see text] =  0.16) in model 3. CONCLUSION:The ability to transform time-varying physiological differences into clinical differences could be used in future prospective prognostic research to identify the dominant movement impairments that drive the increased risk. These slides can be retrieved under Electronic Supplementary Material

The benefits of strength training on musculoskeletal system health: practical applications for interdisciplinary care

Global health organizations have provided recommendations regarding exercise for the general population. Strength training has been included in several position statements due to its multi-systemic benefits. In this narrative review, we examine the available literature, first explaining how specific mechanical loading is converted into positive cellular responses. Secondly, benefits related to specific musculoskeletal tissues are discussed, with practical applications and training programmes clearly outlined for both common musculoskeletal disorders and primary prevention strategies

Cognitive functional therapy: an integrated behavioral approach for the targeted management of disabling low back pain (vol 98, pg 408, 2018)

On page 420, a statement was incorrectly referenced. The statement with corrected reference is: “CFT has shown long-term superior efficacy to physical therapist–led exercise and manual therapy in a randomized trial.”6

Pain in elite athletes - Neurophysiological, biomechanical and psychosocial considerations: A narrative review

Pain is a common problem among elite athletes and is frequently associated with sport injury. Both injury and pain interfere with peak performance. Pain management should be based on the physiological, anatomical and psychosocial influences on the individual's pain and is not equivalent to injury management, which focuses on musculoskeletal recovery and return-to-play. This narrative review provides a foundation for understanding the differing causes and types of pain in elite athletes, thereby serving as a springboard for comprehensive pain management

Patient-centered care in musculoskeletal practice: Key elements to support clinicians to focus on the person

Musculoskeletal rehabilitation, including physiotherapy, needs to move towards a broader biopsychosocial understanding of musculoskeletal conditions and the delivery of high-value care for people with persistent pain conditions, in which a patient-centered approach is a key feature. However, it has been reported that clinicians experience difficulties with integrating patient-centered care principles into their clinical practice. Based on a focused symposium about patient-centered care for patients with musculoskeletal conditions, held during the online 2021 World Physiotherapy Congress, the purpose of this article is to share key elements of the content of this symposium with a wider audience, aimed at enabling clinicians to enhance patient-centeredness in their current practice. These key elements include establishing meaningful connections, deciding together and self-management support. Moreover, challenges on patient-centered care in low/middle income countries will be discussed and recommendations to implement patient-centered care in clinical practice will be provided