Physical performance analysis: A new approach to assessing free-living physical activity in musculoskeletal pain and mobility-limited populations

Measuring objective physical activity in people with chronic low back pain using accelerometers: a scoping review

Purpose

Accelerometers can be used to objectively measure physical activity. They could be offered to people with chronic low back pain (CLBP) who are encouraged to maintain an active lifestyle. The aim of this study was to examine the use of accelerometers in studies of people with CLBP and to synthesize the main results regarding the measurement of objective physical activity.

Methods

A scoping review was conducted following Arksey and O'Malley's framework. Relevant studies were collected from 4 electronic databases (PubMed, Embase, CINHAL, Web of Science) between January 2000 and July 2023. Two reviewers independently screened all studies and extracted data.

Results

40 publications out of 810 citations were included for analysis. The use of accelerometers in people with CLBP differed across studies; the duration of measurement, physical activity outcomes and models varied, and several limitations of accelerometry were reported. The main results of objective physical activity measures varied and were sometimes contradictory. Thus, they question the validity of measurement methods and provide the opportunity to discuss the objective physical activity of people with CLBP.

Conclusions

Accelerometers have the potential to monitor physical performance in people with CLBP; however, important technical limitations must be overcome.

Objective wearable measures correlate with self-reported chronic pain levels in people with spinal cord stimulation systems

Spinal Cord Stimulation (SCS) is a well-established therapy for treating chronic pain. However, perceived treatment response to SCS therapy may vary among people with chronic pain due to diverse needs and backgrounds. Patient Reported Outcomes (PROs) from standard survey questions do not provide the full picture of what has happened to a patient since their last visit, and digital PROs require patients to visit an app or otherwise regularly engage with software. This study aims to assess the feasibility of using digital biomarkers collected from wearables during SCS treatment to predict pain and PRO outcomes. Twenty participants with chronic pain were recruited and implanted with SCS. During the six months of the study, activity and physiological metrics were collected and data from 15 participants was used to develop a machine learning pipeline to objectively predict pain levels and categories of PRO measures. The model reached an accuracy of 0.768 ± 0.012 in predicting the pain intensity of mild, moderate, and severe. Feature importance analysis showed that digital biomarkers from the smartwatch such as heart rate, heart rate variability, step count, and stand time can contribute to modeling different aspects of pain. The results of the study suggest that wearable biomarkers can be used to predict therapy outcomes in people with chronic pain, enabling continuous, real-time monitoring of patients during the use of implanted therapies.

Biomechanical Phenotyping of Chronic Low Back Pain: Protocol for BACPAC

OBJECTIVE

Biomechanics represents the common final output through which all biopsychosocial constructs of back pain must pass, making it a rich target for phenotyping. To exploit this feature, several sites within the NIH Back Pain Consortium (BACPAC) have developed biomechanics measurement and phenotyping tools. The overall aims of this article were to: 1) provide a narrative review of biomechanics as a phenotyping tool; 2) describe the diverse array of tools and outcome measures that exist within BACPAC; and 3) highlight how leveraging these technologies with the other data collected within BACPAC could elucidate the relationship between biomechanics and other metrics used to characterize low back pain (LBP).

METHODS

The narrative review highlights how biomechanical outcomes can discriminate between those with and without LBP, as well as among levels of severity of LBP. It also addresses how biomechanical outcomes track with functional improvements in LBP. Additionally, we present the clinical use case for biomechanical outcome measures that can be met via emerging technologies.

RESULTS

To answer the need for measuring biomechanical performance, our "Results" section describes the spectrum of technologies that have been developed and are being used within BACPAC.

CONCLUSION AND FUTURE DIRECTIONS

The outcome measures collected by these technologies will be an integral part of longitudinal and cross-sectional studies conducted in BACPAC. Linking these measures with other biopsychosocial data collected within BACPAC increases our potential to use biomechanics as a tool for understanding the mechanisms of LBP, phenotyping unique LBP subgroups, and matching these individuals with an appropriate treatment paradigm.

Objective wearable measures and subjective questionnaires for predicting response to neurostimulation in people with chronic pain

BACKGROUND

Neurostimulation is an effective therapy for treating and management of refractory chronic pain. However, the complex nature of pain and infrequent in-clinic visits, determining subject's long-term response to the therapy remains difficult. Frequent measurement of pain in this population can help with early diagnosis, disease progression monitoring, and evaluating long-term therapeutic efficacy. This paper compares the utilization of the common subjective patient-reported outcomes with objective measures captured through a wearable device for predicting the response to neurostimulation therapy.

METHOD

Data is from the ongoing international prospective post-market REALITY clinical study, which collects long-term patient-reported outcomes from 557 subjects implanted by Spinal Cord Stimulator (SCS) or Dorsal Root Ganglia (DRG) neurostimulators. The REALITY sub-study was designed for collecting additional wearables data on a subset of 20 participants implanted with SCS devices for up to six months post implantation. We first implemented a combination of dimensionality reduction algorithms and correlation analyses to explore the mathematical relationships between objective wearable data and subjective patient-reported outcomes. We then developed machine learning models to predict therapy outcome based on the subject's response to the numerical rating scale (NRS) or patient global impression of change (PGIC).

RESULTS

Principal component analysis showed that psychological aspects of pain were associated with heart rate variability, while movement-related measures were strongly associated with patient-reported outcomes related to physical function and social role participation. Our machine learning models using objective wearable data predicted PGIC and NRS outcomes with high accuracy without subjective data. The prediction accuracy was higher for PGIC compared with the NRS using subjective-only measures primarily driven by the patient satisfaction feature. Similarly, the PGIC questions reflect an overall change since the study onset and could be a better predictor of long-term neurostimulation therapy outcome.

CONCLUSIONS

The significance of this study is to introduce a novel use of wearable data collected from a subset of patients to capture multi-dimensional aspects of pain and compare the prediction power with the subjective data from a larger data set. The discovery of pain digital biomarkers could result in a better understanding of the patient's response to therapy and their general well-being.

The future of individualized cardiovascular care: how wearables could be integrated to improve outcomes

Personalized medicine is a concept all clinicians must strive to deliver. Recent advances in technology increasingly offer new opportunities to personalize care, not least in cardiovascular medicine. Health trackers and wearables are technologies in an explosive phase of development. They allow accurate and continuous measurement of bio-data, recorded and analysed using apps and mobile devices. However, although there is huge potential, most physicians and healthcare organizations are yet to realize the value of integrating wearables into routine clinical practice. We discuss how this state-of-the-art technology can support patients in making meaningful lifestyle changes and revolutionize the future of cardiovascular medicine.

Evaluation of Motion Segment Size as a New Sensor-based Functional Outcome Measure in Stroke Rehabilitation

Objective

To evaluate a novel parameter, motion segment size (MSS), in stroke patients with upper limb impairment and validate its clinical applicability by correlating results with a standard clinical task-based functional evaluation tool.

Methods

In this cross-sectional study, patients with hemiplegia and healthy controls equipped with multiple inertial measurement unit (IMU) sensors performed Action Research Arm Test (ARAT) and activities of daily living (ADL) tasks. Acceleration of the wrist and Euler angles of each upper limb segment were measured. The average and maximum MSS, accumulated motion, total performance time, and average motion speed (AMS) were extracted for analysis.

Results

Data from nine patients and 10 controls showed that the average MSS of forearm supination/pronation and elbow flexion/extension during full ARAT tasks showed a significant difference between patients and controls and a significant correlation with ARAT scores.

Conclusions

We suggest that MSS may provide clinically relevant information regarding upper limb functional status in stroke patients.

Objective features of sedentary time and light activity differentiate people with low back pain from healthy controls: a pilot study

BACKGROUND CONTEXT

Physical inactivity has been described as both a cause and a consequence of low back pain (LBP) largely based on self-reported measures of daily activity. A better understanding of the connections between routine physical activity and LBP may improve LBP interventions.

PURPOSE

In this study, we aim to objectively characterize the free-living physical activity of people with low back pain in comparison to healthy controls using accelerometers, and we aim to derive a set of LBP-specific physical activity minutes thresholds that may be used as targets for future physical activity interventions.

STUDY DESIGN

Cross-sectional.

PATIENT SAMPLE

A total of 22 low back pain patients and 155 controls.

OUTCOME MEASURES

Accelerometry derived physical activity measures.

METHODS

Twenty-two people with LBP were compared to 155 age and gender-matched healthy controls. All subjects wore an ActiGraph accelerometer on the right hip for 7 consecutive days. Accelerometry-based physical activity features (count-per-minute CPM) were derived using Freedson's intervals and physical performance intervals. A random forest machine learning classifier was trained to classify LBP status using a leave-one-out cross-validation procedure. An interpretation algorithm, the SHapley Additive exPlanations (SHAP) algorithm was subsequently applied to assess the feature importance and to establish LBP-specific physical activity thresholds.

RESULTS

The LBP group reported mild to moderate disability (average ODI=18.5). The random forest classifier identified a set of 8 features (digital biomarkers) that achieved 88.1% accuracy for distinguishing LBP from controls. All of the top distinguishing features were related to differences in the sedentary and light activity ranges (<800 CPM), whereas moderate to vigorous physical activity was not discriminative. In addition, we identified and ranked physical activity thresholds that are associated with LBP prediction that can be used in future studies of physical activity interventions for LBP.

CONCLUSIONS

We describe a set of physical activity features from accelerometry data associated with LBP. All of the discriminating features were derived from the sedentary and light activity range. We also identified specific activity intensity minutes thresholds that distinguished LBP subjects from healthy controls. Future examination on the digital markers and thresholds identified through this work can be used to improve physical activity interventions for LBP treatment and prevention by allowing the development of LBP-specific physical activity guidelines.

Examining the Association Between Self-Reported Estimates of Function and Objective Measures of Gait and Physical Capacity in Lumbar Stenosis

Objective:

To evaluate the association of self-reported physical function with subjective and objective measures as well as temporospatial gait features in lumbar spinal stenosis (LSS).

Design:

Cross-sectional pilot study.

Setting:

Outpatient multispecialty clinic.

Participants:

Participants with LSS and matched controls without LSS (n=10 per group; N=20).

Interventions:

Not applicable.

Main Outcome Measures:

Self-reported physical function (36-Item Short Form Health Survey [SF-36] physical functioning domain), Oswestry Disability Index, Swiss Spinal Stenosis Questionnaire, the Neurogenic Claudication Outcome Score, and inertia measurement unit (IMU)-derived temporospatial gait features

Results:

Higher self-reported physical function scores (SF-36 physical functioning) correlated with lower disability ratings, neurogenic claudication, and symptom severity ratings in patients with LSS (P<.05). Compared with controls without LSS, patients with LSS have lower scores on physical capacity measures (median total distance traveled on 6-minute walk test: controls 505 m vs LSS 316 m; median total distance traveled on self-paced walking test: controls 718 m vs LSS 174 m). Observed differences in IMU-derived gait features, physical capacity measures, disability ratings, and neurogenic claudication scores between populations with and without LSS were statistically significant.

Conclusions:

Further evaluation of the association of IMU-derived temporospatial gait with self-reported physical function, pain related-disability, neurogenic claudication, and spinal stenosis symptom severity score in LSS would help clarify their role in tracking LSS outcomes.

The EPIPHA-KNEE trial: Explaining Pain to target unhelpful pain beliefs to Increase PHysical Activity in KNEE osteoarthritis - a protocol for a multicentre, randomised controlled trial with clinical- and cost-effectiveness analysis

Background

Despite well-established benefits of physical activity for knee osteoarthritis (OA), nine of ten people with knee OA are inactive. People with knee OA who are inactive often believe that physical activity is dangerous, fearing that it will further damage their joint(s). Such unhelpful beliefs can negatively influence physical activity levels. We aim to evaluate the clinical- and cost-effectiveness of integrating physiotherapist-delivered pain science education (PSE), an evidence-based conceptual change intervention targeting unhelpful pain beliefs by increasing pain knowledge, with an individualised walking, strengthening, and general education program.

Methods

Two-arm, parallel-design, multicentre randomised controlled trial involving 198 people aged ≥50 years with painful knee OA who do not meet physical activity guideline recommendations or walk regularly for exercise. Both groups receive an individualised physiotherapist-led walking, strengthening, and OA/activity education program via 4x weekly in-person treatment sessions, followed by 4 weeks of at-home activities (weekly check-in via telehealth), with follow-up sessions at 3 months (telehealth) and 5 and 9 months (in-person). The EPIPHA-KNEE group also receives contemporary PSE about OA/pain and activity, embedded into all aspects of the intervention. Outcomes are assessed at baseline, 12 weeks, 6 and 12 months. Primary outcomes are physical activity level (step count; wrist-based accelerometry) and self-reported knee symptoms (WOMAC Total score) at 12 months. Secondary outcomes are quality of life, pain intensity, global rating of change, self-efficacy, pain catastrophising, depression, anxiety, stress, fear of movement, knee awareness, OA/activity conceptualisation, and self-regulated learning ability. Additional measures include adherence, adverse events, blinding success, COVID-19 impact on activity, intention to exercise, treatment expectancy/perceived credibility, implicit movement/environmental bias, implicit motor imagery, two-point discrimination, and pain sensitivity to activity. Cost-utility analysis of the EPIPHA-KNEE intervention will be undertaken, in addition to evaluation of cost-effectiveness in the context of primary trial outcomes.

Discussion

We will determine whether the integration of PSE into an individualised OA education, walking, and strengthening program is more effective than receiving the individualised program alone. Findings will inform the development and implementation of future delivery of PSE as part of best practice for people with knee OA.

Trial registration

Australian New Zealand Clinical Trials Registry: ACTRN12620001041943 (13/10/2020).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-021-04561-6.

Physical activity thresholds for predicting longitudinal gait decline in adults with knee osteoarthritis

OBJECTIVE

To investigate the longitudinal relationship between physical performance (via real-life accelerometry) and physical capacity (laboratory measurement of gait speed) in patients with knee osteoarthritis (KOA), and to derive accelerometry measured thresholds associated with gait speed decline in KOA that may provide targets for disease-specific physical activity guidelines.

DESIGN

Longitudinal data from the Osteoarthritis Initiative (OAI) accelerometer sub-study was extracted from 1,229 participants assessed 2 years apart. Extracted data include functional capacity, demographic and anthropometric characteristics, patient-reported outcome measures, and accelerometry-based physical activity measures. A "poor capacity" group was defined based on the gait speed quintile decline between baseline and the 2-yr follow-up. A Random Forest classifier was trained to classify individuals' capacity status, and the impact of each extracted factor on the prediction outcome was analyzed using a novel machine learning interpretation algorithm.

RESULTS

The most impactful predicting feature for gait decline is low minutes in the performance of moderate-vigorous activity (count per min 2,500+). Slower sit-to-stand performance, higher age and self-reported knee pain, and lower minutes in performance light activities (count per min 350-2499) also contributed to the model prediction. The overall classification accuracy is 76.3% (75.4% sensitivity, 76.5% specificity).

CONCLUSIONS

We investigated the impact magnitude and direction of each predicting feature on the longitudinal capacity status among KOA patients. Using novel data interpretation method, we established feature thresholds that may increase the probability of gait decline. These identified thresholds may provide meaningful information for establishing specific physical activity guidelines for KOA.

Smoking Is Associated with Pain in All Body Regions, with Greatest Influence on Spinal Pain

OBJECTIVE

Examine the interrelationship between smoking and pain in the US population.

DESIGN

A cross-sectional population-based study.

SETTING

Nationwide survey.

METHODS

Comprehensive pain reports categorically defined as head, spine, trunk, and limb pain; smoking history; demographics; medical history from a total of 2,307 subjects from the 2003-2004 National Health and Nutrition Examination Survey obtained from the Centers for Disease Control were analyzed. Unpaired t tests were used to analyze independent continuous variables, and chi-square tests were used to analyze categorical variables between smoker and nonsmoker groups. Weighted multivariate logistic regression analyses determined the association of current smoking with the presence of pain in various body regions.

RESULTS

Smoking is most strongly associated with spine pain (odds ratio [OR] = 2.89, 95% confidence interval [CI] = 2.21-3.77), followed by headache (OR = 2.47, 95% CI = 1.73-3.53), trunk pain (OR = 2.17, 95% CI = 1.45-2.74), and limb pain (OR = 1.99, 95% CI = 1.45-2.73).

CONCLUSIONS

Current smoking is associated with pain in every region of the body. This association is strongest for spine and head pain. Given that pain is a strong motivator and that current smoking was associated with pain in all body regions, we recommend that these results be used to further raise public awareness about the potential harms of smoking.

The emerging clinical role of wearables: factors for successful implementation in healthcare

Wearable technologies promise to redefine assessment of health behaviors, yet their clinical implementation remains a challenge. To address this gap, two of the NIH’s Big Data to Knowledge Centers of Excellence organized a workshop on potential clinical applications of wearables. A workgroup comprised of 14 stakeholders from diverse backgrounds (hospital administration, clinical medicine, academia, insurance, and the commercial device industry) discussed two successful digital health interventions that involve wearables to identify common features responsible for their success. Seven features were identified including: a clearly defined problem, integration into a system of healthcare delivery, technology support, personalized experience, focus on end-user experience, alignment with reimbursement models, and inclusion of clinician champions. Health providers and systems keen to establish new models of care inclusive of wearables may consider these features during program design. A better understanding of these features is necessary to guide future clinical applications of wearable technology.

Psychosocial Correlates of Objective, Performance-Based, and Patient-Reported Physical Function Among Patients with Heterogeneous Chronic Pain

BACKGROUND

Improving all aspects of physical function is an important goal of chronic pain management. Few studies follow recent guidelines to comprehensively assess physical function via patient-reported, performance-based, and objective/ambulatory measures.

PURPOSE

To test 1) the interrelation between the 3 types of physical function measurement and 2) the association between psychosocial factors and each type of physical function measurement.

METHODS

Patients with chronic pain (N=79) completed measures of: 1) physical function (patient-reported disability; performance-based 6-minute walk-test; objective accelerometer step count); 2) pain and non-adaptive coping (pain during rest and activity, pain-catastrophizing, kinesiophobia); 3) adaptive coping (mindfulness, general coping, pain-resilience); and 4) social-emotional dysfunction (anxiety, depression, social isolation and emotional support). First, we tested the interrelation among the 3 aspects of physical function. Second, we used structural equation modeling to test associations between psychosocial factors (pain and non-adaptive coping, adaptive coping, and social-emotional dysfunction) and each measurement of physical function.

RESULTS

Performance-based and objective physical function were significantly interrelated (r=0.48, p<0.001) but did not correlate with patient-reported disability. Pain and non-adaptive coping (β=0.68, p<0.001), adaptive coping (β=-0.65, p<0.001) and social-emotional dysfunction (β=0.65, p<0.001) were associated with patient-reported disability but not to performance-based or objective physical function (ps>0.1).

CONCLUSION

Results suggest that patient-reported physical function may provide limited information about patients' physical capacity or ambulatory activity. While pain and non-adaptive reactions to it, adaptive coping, and social-emotional dysfunction may potentially improve patient-reported physical function, additional targets may be needed to improve functional capacity and ambulatory activity.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03412916.

Assessing Motor Function in Congenital Muscular Dystrophy Patients Using Accelerometry

BACKGROUND

When tested in a controlled clinic environment, individuals with neuromuscular-related symptoms may complete motor tasks within normal predicted ranges. However, measuring activity at home may better reflect typical motor performance. The accuracy of accelerometry measurements in individuals with congenital muscular dystrophy (CMD) is unknown. We aimed to compare accelerometry and manual step counts and assess free-living physical activity intensity in individuals with CMD using accelerometry.

METHODS

Ambulatory pediatric CMD participants (n = 9) performed the 6-minute walk test in clinic while wearing ActiGraph GT3X accelerometer devices. During the test, manual step counting was conducted to assess concurrent validity of the ActiGraph step count in this population using Bland-Altman analysis. In addition, activity intensity of 6 pediatric CMD participants was monitored at home with accelerometer devices for an average of 7 days. Cut-point values previously validated for neuromuscular disorders were used for data analysis.

RESULTS

Bland-Altman and intraclass correlation analyses showed no concurrent validity between manual and ActiGraph-recorded step counts. Fewer steps were recorded by ActiGraph step counts compared with manual step counts (411 ± 74 vs 699 ± 43, respectively; P = .004). Although improved, results were in the same direction with the application of low-frequency extension filters (587 ± 40 vs 699 ± 43, P = .03). ActiGraph step-count data did not correlate with manual step count (Spearman ρ = 0.32, P = .41; with low-frequency extension: Spearman ρ = 0.45, P = .22). Seven-day physical activity monitoring showed that participants spent more than 80% of their time in the sedentary activity level.

CONCLUSIONS

In a controlled clinic setting, step count was significantly lower by ActiGraph GT3X than by manual step counting, possibly because of the abnormal gait in this population. Additional studies using triaxial assessment are needed to validate accelerometry measurement of activity intensity in individuals with CMD. Accelerometry outcomes may provide valuable measures and complement the 6-minute walk test in the assessment of treatment efficacy in CMD.

Obesity and pain: a systematic review

BACKGROUND/OBJECTIVES

The current systematic review considered research published within the 10 years preceding June 2019, dealing with the topic of obesity and pain. Within the context of the complex biological and behavioral interrelationships among these phenomena, we sought to identify gaps in the literature and to highlight key targets for future transdisciplinary research. The overarching inclusion criteria were that the included studies could directly contribute to our understanding of these complex phenomena.

METHODS

We searched PubMed/Medline/Cochrane databases dating back 10 years, using the primary search terms "obesity" and "pain," and for a secondary search we used the search terms "pain" and "diet quality."

RESULTS

Included studies (n = 70) are primarily human; however, some animal studies were included to enhance understanding of related basic biological phenomena and/or where human data were absent or significantly limited.

CONCLUSIONS

Our overall conclusions highlight (1) the mechanisms of obesity-related pain (i.e., mechanical, behavioral, and physiological) and potential biological and behavioral contributors (e.g., gender, distribution of body fat, and dietary factors), (2) the requirement for accurate and reliable objective measurement, (3) the need to integrate biological and behavioral contributors into comprehensive, well-controlled prospective study designs.

Subjective and Objective Measures of Daytime Activity and Sleep Disturbance in Retinitis Pigmentosa

SIGNIFICANCE

Objectively measured limitations in daytime activity levels appear to be inextricably linked with sleep disturbances in retinitis pigmentosa (RP) patients, as well as associated with unemployment status and central vision loss. Innovative interventional strategies should be developed to help improve these issues and overall quality of life for RP patients.

PURPOSE

Novel sensor devices are emerging as valuable tools to objectively assess behavior. We used validated measures of wrist accelerometry to determine relationships between sleep, vision, and physical activity in RP subjects.

METHODS

For one week, 33 RP adults wore a wrist Actiwatch to detect movement during the day (average total activity counts) and disturbed sleep at night. They completed Early Treatment Diabetic Retinopathy Study visual acuity testing, Pelli-Robson contrast sensitivity, Goldmann V4e visual fields, and sleep diaries and validated questionnaires to assess their sleep and general health.

RESULTS

Greater wake after sleep onset time measured with actigraphy (i.e., sleep disruption) (P = .01), loss of visual acuity (P = .009), and nonemployment/student status (P = .002) were all significant predictors of reduced daytime average total activity counts in a multiple linear regression model, after adjusting for contrast sensitivity as a cooperative suppressor variable (P = .01) (R = 0.54). Fragmentation measured with actigraphy (i.e., restlessness during sleep) (P = .07) and decreased sleep quality ratings reported upon awakening by the participants in a sleep diary (P = .06) were each marginally associated with reduced daytime average total activity counts, whereas nonemployment/student status, reduced visual acuity, and contrast sensitivity were still significant predictors. Objective and subjective measures of sleep or daytime activity were not statistically significantly correlated (P > .05).

CONCLUSIONS

We find nonemployment/student status and sleep disturbances appear to be related to reduced daytime activity levels in adults with central vision loss due to RP. These findings underscore the importance of developing and evaluating interventions to help RP patients maintain engagement in productive activities and improve their disturbed sleep.

Measurement properties of walking outcome measures for neurogenic claudication: a systematic review and meta analysis

BACKGROUND CONTEXT

Selecting a walking outcome measure for neurogenic claudication requires knowledge of its measurement properties.

PURPOSE

To systematically review and appraise the literature on the measurement properties of walking outcome measures for patients with neurogenic claudication.

STUDY DESIGN

A systematic review and meta-analysis.

METHODS

A systematic search was conducted on the following seven databases: PubMed, PsychINFO, Web of Science, Embase, CINAHL, MEDLINE, and Cochrane Central Register of Controlled Trials. Clinical studies that assessed a measurement property of a walking outcome measure for patients with neurogenic claudication were selected. The methodological quality of studies was assessed using the Consensus-based Standards for the selection of health Measurement Instruments (COSMIN) checklist. Measurement property results were assessed using the adapted criteria from Terwee et al. (2007).

RESULTS

Twelve studies that evaluated 15 separate walking outcome measures were included. Out of the 12 studies included, half had poor methodological quality. Four measures had acceptable test-retest reliability: the self-paced walking test (intraclass correlation coefficient, or ICC was 0.98, 95% CI: 0.95-0.99), Physical Function Scale (PFS) (pooled analysis ICC = 0.79, 95% CI: 0.77-0.89), PFS walk item (ICC = 0.81, 95% CI: 0.68-0.89), and Oswestry Disability Index (ODI) walk item (ICC = 0.86, 95% CI: 0.76-0.92). Responsiveness was assessed on five walking outcome measures, and three had adequate responsiveness: the ODI walk item (Area under the Curve, or AUC, was 0.76, SD 0.15), Treadmill test (AUC = 0.70), and PFS (AUC = 0.77, SD 0.14). A meta-analysis demonstrated the PFS had adequate test retest reliability (pooled ICC = 0.79, 95% CI: 0.77-0.89) and internal consistency (pooled Cronbach's αlpha (α) = 0.84, 95% CI: 0.81-0.86), but not criterion validity (pooled correlation coefficient = -0.59, 95% CI: -0.71, -0.45). Measures that recorded adequate criterion validity were the ODI walk item (pooled correlation coefficient = -0.71, 95% CI: -0.80, -0.58), Treadmill test (pooled correlation coefficient = 0.86, 95% CI: 0.78-0.91), and self predicted walking item (pooled correlation coefficient = 0.74, 95% CI: 0.63-0.82).

CONCLUSIONS

The results of our systematic review demonstrated that high-quality studies that asses the measurement properties of walking outcome measures for patients with neurogenic claudication are lacking. There was only limited evidence available for each walking measure, which prevented any single outcome from being confirmed as the gold standard measure of neurogenic claudication. Clinicians and researchers are recommended to use the self-paced walking test and ODI walk item until further evidence is available. Future research should focus on producing high-quality studies with excellent methodology and larger sample sizes.

Upper extremity disability is associated with pain intensity and grip strength in women with bilateral idiopathic carpal tunnel syndrome

BACKGROUND

The upper extremity disability in patients with carpal tunnel syndrome (CTS) is related to dysfunction due to the median nerve damage. However, there is no report on which dysfunctions affect the upper extremity disability.

PURPOSE

This study aimed to investigate which clinical factors influence upper extremity disability in women with CTS.

METHODS

We analyzed 60 hands of women with bilateral idiopathic CTS. Upper extremity disability was assessed using Hand10, a validated and self-administered tool. Pain intensity was measured using the Japanese version of the Short-Form McGill Pain Questionnaire (SF-MPQ-J). We performed nerve conduction studies, assessed physical and psychological parameters, and collected demographic data. Physical parameters comprised grip strength, pinch strength, tactile threshold, static 2-point discrimination sensation, and severity of numbness. Psychological parameters include depression, pain anxiety, and distress.

RESULTS

The bivariate analysis revealed that Hand10 was significantly correlated with age, symptom duration, SF-MPQ-J, grip strength, pain anxiety, and distress. Multiple regression analysis demonstrated that SF-MPQ-J and grip strength were related to Hand10 score.

CONCLUSIONS

Pain intensity and grip strength were dysfunctions affecting the upper extremity disability in women with bilateral idiopathic CTS. Rehabilitation approaches for CTS should be considered based on the adaptive activities of the neural networks.

Digital biomarkers of spine and musculoskeletal disease from accelerometers: Defining phenotypes of free-living physical activity in knee osteoarthritis and lumbar spinal stenosis

BACKGROUND CONTEXT

Lumbar spinal stenosis (LSS) and knee osteoarthritis (OA) are 2 of the leading causes of disability worldwide. In order to provide disease-specific prescriptions for physical activity, there is a clear need to better understand physical activity in daily life (performance) in these populations.

PURPOSE

To discover performance phenotypes for LSS and OA by applying novel analytical methods to accelerometry data. Specific objectives include the following: (1) to identify characteristic features (phenotypes) of free-living physical activity unique to individuals with LSS and OA, and (2) to determine which features can best differentiate between these conditions.

STUDY DESIGN AND SETTING

Leveraging data from 3 existing cross-sectional cohorts, accelerometry signal feature characterization and selection were performed in a computational laboratory.

PATIENT SAMPLE

Data from a total of 4,028 individuals were analyzed from the following 3 datasets: LSS Accelerometry Database (n=75); OA Initiative (n=1950); and the 2003 to 2004 National Health and Nutrition Examination Survey (pain-free controls, n=2003).

METHODS

In order to characterize the accelerometry signals, data were examined using (1) standard intervals for counts/minute from Freedson et al. and (2) the physical performance intervals for mobility-limited pain populations. From this, 42 novel accelerometry features were defined and evaluated for significance in discriminating between the groups (LSS, OA, and controls) in order to then determine which sparse set of features best differentiates between the groups. These sparse sets of features defined the performance phenotypes.

OUTCOME MEASURES

Accelerometry features and their ability to differentiate between individuals with LSS, OA, and controls.

RESULTS

Given age and gender, classification rates were at least 80% accurate (pairwise) between diseased and pain-free populations (LSS vs. controls and OA vs. controls). The most important features to distinguish between disease groups corresponded to measures in the light and sedentary activity intervals. The more subtle classification between diseased populations (LSS vs. OA) was 72% accurate, with light and moderate activity providing the prominent distinguishing features.

CONCLUSIONS

We describe the discovery of performance phenotypes of LSS and OA from accelerometry data, revealed through a novel set of features that characterize daily patterns of movement in people with LSS and OA. These performance phenotypes provide a new method for analyzing free-living physical activity (performance) in LSS and OA, and provide the groundwork for more personalized approaches to measuring and improving function.

Inferring Physical Function From Wearable Activity Monitors: Analysis of Free-Living Activity Data From Patients With Knee Osteoarthritis

Background

Clinical assessments for physical function do not objectively quantify routine daily activities. Wearable activity monitors (WAMs) enable objective measurement of daily activities, but it remains unclear how these map to clinically measured physical function measures.

Objective

This study aims to derive a representation of physical function from daily measurements of free-living activity obtained through a WAM. In addition, we evaluate our derived measure against objectively measured function using an ordinal classification setup.

Methods

We defined function profiles representing average time spent in a set of pattern classes over consecutive days. We constructed a function profile using minute-level activity data from a WAM available from the Osteoarthritis Initiative. Using the function profile as input, we trained statistical models that classified subjects into quartiles of objective measurements of physical function as measured through the 400-m walk test, 20-m walk test, and 5 times sit-stand test. Furthermore, we evaluated model performance on held-out data.

Results

The function profile derived from minute-level activity data can accurately predict physical performance as measured through clinical assessments. Using held-out data, the Goodman-Kruskal Gamma statistic obtained in classifying performance values in the first quartile, interquartile range, and the fourth quartile was 0.62, 0.53, and 0.51 for the 400-m walk, 20-m walk, and 5 times sit-stand tests, respectively.

Conclusions

Function profiles accurately represent physical function, as demonstrated by the relationship between the profiles and clinically measured physical performance. The estimation of physical performance through function profiles derived from free-living activity data may enable remote functional monitoring of patients.

US National Health and Nutrition Examination Survey Arthritis Initiatives, Methodologies and Data

The US National Health and Nutrition Examination Survey (NHANES) has collected population-based, nationally representative examination, laboratory, and radiographic data for arthritis and musculoskeletal diseases for more than 50 years. The resulting body of data and publications are substantial, yet much data remain unpublished. This review provides a basic understanding of the design and capabilities of the NHANES survey, reviewing the major accomplishments in the area of arthritis and musculoskeletal diseases. Currently available US National Health and Nutrition Examination Survey arthritis-related datasets are identified. Guidelines for using these data, and opportunities for data analysis and designing future studies are presented.

Does the physical activity profile change in patients with hip dysplasia from before to 1 year after periacetabular osteotomy?

Background and purpose - Knowledge of physical activity profiles among patients with hip dysplasia is lacking. We investigated whether patients with hip dysplasia change physical activity profile from before to 1 year after periacetabular osteotomy. Furthermore, we investigated associations between change in accelerometer-based physical activity and change in self-reported participation in preferred physical activities (PA). Patients and methods - Physical activity was objectively measured at very low to high intensity levels with accelerometer-based sensors. Subjectively, PA was recorded with Copenhagen Hip and Groin Outcome Score (HAGOS) in 77 patients. Associations between the 2 were analyzed with simple linear regression analyses. Results - Changes in accelerometer-based physical activity ranged from -2.2 to 4.0% points at all intensity levels from baseline to 1-year follow-up. These changes represent very small effect sizes (-0.16 to 0.14). In contrast, self-reported PA showed a statistically and clinically relevant increase of 22 (CI 14-29) HAGOS PA points 1 year post-surgery. Associations between change in accelerometer-based physical activity and change in self-reported PA were, however, not statistically significant and correspond to a percentage change in physical activity of only -0.87% to 0.65% for a change of 10 HAGOS PA points. Interpretation - Patients with hip dysplasia do not seem to change physical activity profile 1 year post-surgery if measured with objective accelerometer-based sensors. This is interesting as self-reported PA indicates that patients' ability to participate in physical activity increases, suggesting that this increased self-reported participatory capacity is not manifested as increased objectively measured physical activity.

Pre-operative sensor-based gait parameters predict functional outcome after total knee arthroplasty

BACKGROUND

Despite the general success of total knee arthroplasty (TKA) regarding patient-reported outcome measures, studies investigating gait function have shown diverse functional outcomes. Mobile sensor-based systems have recently been employed for accurate clinical gait assessments, as they allow a better integration of gait analysis into clinical routines as compared to laboratory based systems.

RESEARCH QUESTION

In this study, we sought to examine whether an accurate assessment of gait function of knee osteoarthritis patients with respect to surgery outcome evaluation after TKA using a mobile sensor-based gait analysis system is possible.

METHODS

A foot-worn sensor-based system was used to assess spatio-temporal gait parameters of 24 knee osteoarthritis patients one day before and one year after TKA, and in comparison to matched control participants. Patients were clustered into positive and negative responder groups using a heuristic approach regarding improvements in gait function. Machine learning was used to predict surgery outcome based on pre-operative gait parameters.

RESULTS

Gait function differed significantly between controls and patients. Patient-reported outcome measures improved significantly after surgery, but no significant global gait parameter difference was observed between pre- and post-operative status. However, the responder groups could be correctly predicted with an accuracy of up to 89% using pre-operative gait parameters. Patients exhibiting high pre-operative gait function were more likely to experience a functional decrease after surgery. Important gait parameters for the discrimination were stride time and stride length.

SIGNIFICANCE

The early identification of post-surgical functional outcomes of patients is of great importance to better inform patients pre-operatively regarding surgery success and to improve post-surgical management.