Telehealth delivery of physical therapist-led interventions for persons with chronic low back pain in underserved communities: lessons from pragmatic clinical trials.

In this perspective, we present our experience developing and conducting two pragmatic clinical trials investigating physical therapist-led telehealth strategies for persons with chronic low back pain. Both trials, the BeatPain Utah and AIM-Back trials, are part of pragmatic clinical trial collaboratories and are being conducted with persons from communities that experience pain management disparities. Practice guidelines recommend nonpharmacologic care, and advise against opioid therapy, for the primary care management of persons with chronic low back pain. Gaps between these recommendations and actual practice patterns are pervasive, particularly for persons from racial or ethnic minoritized communities, those with fewer economic resources, and those living in rural areas including Veterans. Access barriers to evidence-based nonpharmacologic care, which is often provided by physical therapists, have contributed to these evidence-practice gaps. Telehealth delivery has created new opportunities to overcome access barriers for nonpharmacologic pain care. As a relatively new delivery mode however, telehealth delivery of physical therapy comes with additional challenges related to technology, intervention adaptations and cultural competence. The purpose of this article is to describe the challenges encountered when implementing telehealth physical therapy programs for persons with chronic low back pain in historically underserved communities. We also discuss strategies developed to overcome barriers in an effort to improve access to telehealth physical therapy and reduce pain management disparities. Inclusion of diverse and under-represented communities in pragmatic clinical trials is a critical consideration for improving disparities, but the unique circumstances present in these communities must be considered when developing implementation strategies.

Transition from Acute to Chronic Low Back Pain in a Community-Based Cohort.

The transition from acute to chronic low back pain (LBP) in community settings has yet to be well understood. We recruited n=131 participants with acute LBP from the community and followed them for 3 and 6-month outcomes. Acute LBP was defined by a duration of < 4 weeks, and participants must have reported a 30-day LBP-free period before the current acute episode. Chronic LBP was defined as pain most or every day over the past 3 months. Baseline psychological, social, and demographic factors were examined as predictors of transition to chronic LBP at 3 months or continuation of chronic LBP at 6 months. The transition from acute to chronic LBP at 3 months was 32.2% ( 38/118). At 6 months, 80.7% (25/111) of participants who transitioned at 3 months continued to have chronic LBP. At 6 months, participants who identified as Black or African American were more likely than white participants to transition to chronic LBP (RR=1.76, 95% CI 1.05, 2.95) and more likely to continue to have chronic LBP (RR=2.19, 95% CI 1.14, 4.21). Those classified at baseline by both LBP most or every day and intensity of at least 30/100 were more likely to transition to chronic LBP (RR=3.13, 95% CI 1.84, 5.30) and continue to have chronic LBP at 6 months (RR=2.58, 95% CI 1.43, 4.16). The STarT Back Screening Tool and the OSPRO-YF were associated with the transition to chronic LBP at 3 months and continuation at 6 months. Participants with higher PROMIS General Health and PROMIS Physical Health scores were less likely to transition to chronic LBP or continue to have chronic LBP at 6 months. These findings identify factors of acute LBP in the community that may predict the transition to chronic LBP. Larger studies are needed to confirm these findings and better understand the mechanisms driving the transition to chronic LBP.

Identifying characteristics and clinical conditions associated with hand grip strength in adults: the Project Baseline Health Study.

Low hand grip strength (HGS) is associated with several conditions, but its value outside of the older adult population is unclear. We sought to identify the most salient factors associated with HGS from an extensive list of candidate variables while stratifying by age and sex. We used data from the initial visit from the Project Baseline Health Study (N = 2502) which captured detailed demographic, occupational, social, lifestyle, and clinical data. We applied MI-LASSO using group methods to determine variables most associated with HGS out of 175 candidate variables. We performed analyses separately for sex and age (< 65 vs. ≥ 65 years). Race was associated with HGS to varying degrees across groups. Osteoporosis and osteopenia were negatively associated with HGS in female study participants. Immune cell counts were negatively associated with HGS for male participants ≥ 65 (neutrophils) and female participants (≥ 65, monocytes; < 65, lymphocytes). Most findings were age and/or sex group-specific; few were common across all groups. Several of the variables associated with HGS in each group were novel, while others corroborate previous research. Our results support HGS as a useful indicator of a variety of clinical characteristics; however, its utility varies by age and sex.

Characterizing Acute Low Back Pain in a Community-Based Cohort.

Acute low back pain (LBP) is a common experience, however, the associated pain severity, pain frequency, and characteristics of individuals with acute LBP in community settings have yet to be well understood. In this manuscript, three acute LBP severity categorization definitions were used based on LBP frequency combined with either 1) pain impact frequency (impact-based) or 2) pain intensity (intensity-based), as well as LBP pain interference frequency (interference only-based) severity categories. The purpose of this manuscript is to describe and then compare these acute LBP severity groups in the following characteristics: 1) sociodemographic, 2) general and physical health, and 3) psychological. This cross-sectional study used baseline data from 131 community-based participants with acute LBP (<4 weeks duration before screening and ≥30 pain-free days before acute LBP onset). Descriptive associations were calculated as prevalence ratios for categorical variables and Hedges' g for continuous variables. Our analyses identified several large associations for impact-based and intensity-based categories with global mental health, global physical health, STarT Back Screening Tool risk category, and general health. Larger associations were found with social constructs (racially and ethnically minoritized, performance of social roles, and isolation) when using the intensity-based versus impact-based categorization. The interference-based category did not capture as much variability between acute LBP severity categories. This study adds to the literature by providing standard ways to characterize community-based individuals experiencing acute LBP. The robust differences observed between these categorization approaches suggest that how we define acute LBP severity is consequential; these different approaches may be used to improve the early identification of factors potentially contributing to the development of chronic LBP.

Automated segmentation and prediction of intervertebral disc morphology and uniaxial deformations from MRI.

Objective: The measurement of in vivo intervertebral disc (IVD) mechanics may be used to understand the etiology of IVD degeneration and low back pain (LBP). To this end, our lab has developed methods to measure IVD morphology and uniaxial compressive deformation (% change in IVD height) resulting from dynamic activity, in vivo, using magnetic resonance images (MRI). However, due to the time-intensive nature of manual image segmentation, we sought to validate an image segmentation algorithm that could accurately and reliably reproduce models of in vivo tissue mechanics. Design: Therefore, we developed and evaluated two commonly employed deep learning architectures (2D and 3D U-Net) for the segmentation of IVDs from MRI. The performance of these models was evaluated for morphological accuracy by comparing predicted IVD segmentations (Dice similarity coefficient, mDSC; average surface distance, ASD) to manual (ground truth) measures. Likewise, functional reliability and precision were assessed by evaluating the intraclass correlation coefficient (ICC) and standard error of measurement (SEm) of predicted and manually derived deformation measures. Results: Peak model performance was obtained using the 3D U-net architecture, yielding a maximum mDSC â€‹= â€‹0.9824 and component-wise ASDx â€‹= â€‹0.0683 â€‹mm; ASDy â€‹= â€‹0.0335 â€‹mm; ASDz â€‹= â€‹0.0329 â€‹mm. Functional model performance demonstrated excellent reliability ICC â€‹= â€‹0.926 and precision SEm â€‹= â€‹0.42%. Conclusions: This study demonstrated that a deep learning framework can precisely and reliably automate measures of IVD function, drastically improving the throughput of these time-intensive methods.

The Predicted Position of the Knee Near the Time of ACL Rupture Is Similar Between 2 Commonly Observed Patterns of Bone Bruising on MRI.

BACKGROUND: Bone bruises observed on magnetic resonance imaging (MRI) can provide insight into the mechanisms of noncontact anterior cruciate ligament (ACL) injury. However, it remains unclear whether the position of the knee near the time of injury differs between patients evaluated with different patterns of bone bruising, particularly with regard to valgus angles. HYPOTHESIS: The position of the knee near the time of injury is similar between patients evaluated with 2 commonly occurring patterns of bone bruising. STUDY DESIGN: Descriptive laboratory study. METHODS: Clinical T2- and T1-weighted MRI scans obtained within 6 weeks of noncontact ACL rupture were reviewed. Patients had either 3 (n = 20) or 4 (n = 30) bone bruises. Patients in the 4-bone bruise group had bruising of the medial and lateral compartments of the femur and tibia, whereas patients in the 3-bone bruise group did not have a bruise on the medial femoral condyle. The outer contours of the bones and associated bruises were segmented from the MRI scans and used to create 3-dimensional surface models. For each patient, the position of the knee near the time of injury was predicted by moving the tibial model relative to the femoral model to maximize the overlap of the tibiofemoral bone bruises. Logistic regressions (adjusted for sex, age, and presence of medial collateral ligament injury) were used to assess relationships between predicted injury position (quantified in terms of knee flexion angle, valgus angle, internal rotation angle, and anterior tibial translation) and bone bruise group. RESULTS: The predicted injury position for patients in both groups involved a flexion angle <20°, anterior translation >20 mm, valgus angle <10°, and internal rotation angle <10°. The injury position for the 3-bone bruise group involved less flexion (odds ratio [OR], 0.914; 95% CI, 0.846-0.987; P = .02) and internal rotation (OR, 0.832; 95% CI, 0.739-0.937; P = .002) as compared with patients with 4 bone bruises. CONCLUSION: The predicted position of injury for patients displaying both 3 and 4 bone bruises involved substantial anterior tibial translation (>20 mm), with the knee in a straight position in both the sagittal (<20°) and the coronal (<10°) planes. CLINICAL RELEVANCE: Landing on a straight knee with subsequent anterior tibial translation is a potential mechanism of noncontact ACL injury.

Nightmare disorder and low back pain in veterans: cross-sectional association and effect over time.

Low back pain (LBP) disproportionately impacts US military veterans compared with nonveterans. Although the effect of psychological conditions on LBP is regularly studied, there is little published to date investigating nightmare disorder (NMD) and LBP. The purpose of this study was to (1) investigate whether an association exists between NMD and LBP and (2) estimate the effect of NMD diagnosis on time to LBP. We used a retrospective cohort design with oversampling of those with NMD from the Veterans Health Administration (n = 15 983). We used logistic regression to assess for a cross-sectional association between NMD and LBP and survival analysis to estimate the effect of NMD on time to LBP, up to 60-month follow-up, conditioning on age, sex, race, index year, Charlson Comorbidity Index, depression, anxiety, insomnia, combat exposure, and prisoner of war history to address confounding. Odds ratios (with 95% confidence intervals [CIs]) indicated a cross-sectional association of 1.35 (1.13 to 1.60) and 1.21 (1.02 to 1.42) for NMD and LBP within 6 months and 12 months pre- or post-NMD diagnosis, respectively. Hazard ratios (HRs) indicated the effect of NMD on time to LBP that was time-dependent-HR (with 95% CIs) 1.27 (1.02 to 1.59), 1.23 (1.03 to 1.48), 1.19 (1.01 to 1.40), and 1.10 (0.94 to 1.29) in the first 3, 6, 9, and 12 months post-diagnosis, respectively-approximating the null (1.00) at >12 months. The estimated effect of NMD on LBP suggests that improved screening for NMD among veterans may help clinicians and researchers predict (or intervene to reduce) risk of future back pain.

Biomarker clusters differentiate phenotypes of lumbar spine degeneration and low back pain: The Johnston County Osteoarthritis Project.

Objective: Describe the association between biomarkers and lumbar spine degeneration (vertebral osteophytes [OST], facet joint osteoarthritis [FOA], and disc space narrowing [DSN]), for persons with and without low back pain (LBP) and determine whether clusters based on biomarkers differentiate lumbar spine structure with and without LBP. Methods: Using data from the Johnston County Osteoarthritis Project (2006-2010), we measured serum N-cadherin, Keratin-19, Lumican, CXCL6, RANTES, HA, IL-6, BDNF, OPG, and NPY, and urinary CTX-II. Biomarkers were used to group participants using k-means cluster analysis. Logistic regression models were used to compare biomarker clusters. Results: The sample consisted of 731 participants with biospecimens and lumbar spine radiographic data. Three biomarker subgroups were identified: one characterized by structural degenerative changes; another characterized by structural degenerative changes and inflammation, with pain; and a referent cluster with lower levels of biomarkers, pain, and structural degenerative changes. Compared to the referent subgroup, the structural change subgroup was associated with DSN (OR = 1.94, 95% CI 1.30-2.90) and FOA (OR = 1.72, 95% CI 1.12-2.62), and the subgroup with structural degenerative change, inflammation, and pain was associated with OST with LBP (OR = 1.60, 95% CI 1.04-2.46), FOA with LBP (OR = 1.59, 95% CI 1.04-2.45), and LBP (OR = 1.63, 95% CI 1.11-2.41). The subgroup with structural degenerative changes was more likely to have OST (OR = 1.82, 95% CI 1.06-3.13) and less likely to have FOA with LBP (OR = 0.62, 95% CI 0.40-0.96) compared to the group with inflammation and pain. Conclusion: Clustering by biomarkers may assist in differentiating patients for specific clinical interventions aimed at decreasing LBP.

Association of Biomarkers with Individual and Multiple Body Sites of Pain: The Johnston County Osteoarthritis Project.

Introduction: Biochemical biomarkers may provide insight into musculoskeletal pain reported at individual or multiple body sites. The purpose of this study was to determine if biomarkers or pressure-pain threshold (PPT) were associated with individual or multiple sites of pain. Methods: This cross-sectional analysis included 689 community-based participants. Self-reported symptoms (ie, pain, aching, or stiffness) were ascertained about the neck, upper back/thoracic, low back, shoulders, elbows, wrist, hands, hips, knees, ankles, and feet. Measured analytes included CXCL-6, RANTES, HA, IL-6, BDNF, OPG and NPY. A standard dolorimeter measured PPT. Logistic regression was used determine the association between biomarkers and PPT with individual and summed sites of pain. Results: Increased IL-6 and HA were associated with knee pain (OR=1.30, 95% CI 1.03, 1.64) and (OR=1.32, 95% CI 1.01, 1.73) respectively; HA was also associated with elbow/wrist/hand pain (OR=1.60, 95% CI 1.22, 2.09). Those with increased NPY levels were less likely to have shoulder pain (OR=0.56, 95% CI 0.33, 0.93). Biomarkers HA (OR=1.50, 95% CI 1.07, 2.10), OPG (OR=1.74, 95% CI 1.00, 3.03), CXCL-6 (OR=1.75, 95% CI 1.02, 3.01) and decreased PPT (OR=3.97, 95% CI 2.22, 7.12) were associated with multiple compared to no sites of pain. Biomarker HA (OR=1.57, 95% CI 1.06, 2.32) and decreased PPT (OR=3.53, 95% CI 1.81, 6.88) were associated with multiple compared to a single site of pain. Conclusion: Biomarkers of inflammation (HA, OPG, IL-6 and CXCL-6), pain (NPY) and PPT may help to understand the etiology of single and multiple pain sites.

In vivo fluid transport in human intervertebral discs varies by spinal level and disc region.

Background: The lumbar discs are large, dense tissues that are primarily avascular, and cells residing in the central region of the disc are up to 6-8 mm from the nearest blood vessel in adults. To maintain homeostasis, disc cells rely on nutrient transport between the discs and adjacent vertebrae. Thus, diminished transport has been proposed as a factor in age-related disc degeneration. Methods: In this study, we used magnetic resonance imaging (MRI) to quantify diurnal changes in T2 relaxation time, an MRI biomarker related to disc hydration, to generate 3D models of disc fluid distribution and determine how diurnal changes in fluid varied by spinal level. We recruited 10 participants (five males/five females; age: 21-30 years; BMI: 19.1-29.0 kg/m2) and evaluated the T2 relaxation time of each disc at 8:00 AM and 7:00 PM, as well as degeneration grade (Pfirrmann). We also measured disc height, volume, and perimeter in a subset of individuals as a preliminary comparison of geometry and transport properties. Results: We found that the baseline (AM) T2 relaxation time and the diurnal change in T2 relaxation time were greatest in the cranial lumbar discs, decreasing along the lumbar spine from cranial to caudal. In cranial discs, T2 relaxation times decreased in each disc region (nucleus pulposus [NP], inner annulus fibrosus [IAF], and outer annulus fibrosus [OAF]), whereas in caudal discs, T2 relaxation times decreased in the NP but increased in the AF. Conclusions: Fluid transport varied by spinal level, where transport was greatest in the most cranial lumbar discs and decreased from cranial to caudal along the lumbar spine. Future work should evaluate what level-dependent factors affect transport.

The Lumbar Stenosis Prognostic Subgroups for Personalizing Care and Treatment (PROSPECTS) study: protocol for an inception cohort study.

BACKGROUND: Lumbar spinal stenosis (LSS) is a common degenerative condition that contributes to back and back-related leg pain in older adults. Most patients with symptomatic LSS initially receive non-operative care before surgical consultation. However, there is a scarcity of data regarding prognosis for patients seeking non-surgical care. The overall goal of this project is to develop and evaluate a clinically useful model to predict long-term physical function of patients initiating non-surgical care for symptomatic LSS. METHODS: This is a protocol for an inception cohort study of adults 50 years and older who are initiating non-surgical care for symptomatic LSS in a secondary care setting. We plan to recruit up to 625 patients at two study sites. We exclude patients with prior lumbar spine surgeries or those who are planning on lumbar spine surgery. We also exclude patients with serious medical conditions that have back pain as a symptom or limit walking. We are using weekly, automated data pulls from the electronic health records to identify potential participants. We then contact patients by email and telephone within 21 days of a new visit to determine eligibility, obtain consent, and enroll participants. We collect data using telephone interviews, web-based surveys, and queries of electronic health records. Participants are followed for 12 months, with surveys completed at baseline, 3, 6, and 12 months. The primary outcome measure is the 8-item PROMIS Physical Function (PF) Short Form. We will identify distinct phenotypes using PROMIS PF scores at baseline and 3, 6, and 12 months using group-based trajectory modeling. We will develop and evaluate the performance of a multivariable prognostic model to predict 12-month physical function using the least absolute shrinkage and selection operator and will compare performance to other machine learning methods. Internal validation will be conducted using k-folds cross-validation. DISCUSSION: This study will be one of the largest cohorts of individuals with symptomatic LSS initiating new episodes of non-surgical care. The successful completion of this project will produce a cross-validated prognostic model for LSS that can be used to tailor treatment approaches for patient care and clinical trials.

Utility of an obstacle-crossing test to classify future fallers and non-fallers at hospital discharge after stroke: A pilot study.

BACKGROUND: Existing clinical assessments of balance and functional mobility have poor predictive accuracy for prospectively identifying post-stroke fallers, which may be due to a lack of ecological complexity that is typical of community-based fall incidents. RESEARCH QUESTION: Does an obstacle-crossing test at hospital discharge predict fall status of ambulatory stroke survivors 3 months after discharge? METHODS: Ambulatory stroke survivors being discharged home completed an obstacle-crossing test at hospital discharge. Falls were tracked prospectively for 3 months after discharge. Logistic regression examined the relationship between obstacle-crossing at discharge (pass/fail) and fall status (faller/non-faller) at 3 months post discharge. RESULTS: 45 participants had discharge obstacle test and 3-month fall data. 21 (47 %) participants experienced at least one fall during follow-up, with 52 % of the falls occurring within the first month after discharge. Of the 21 fallers, 14 failed the obstacle-crossing test (67 % sensitivity). Among the 24 non-fallers, 20 passed the obstacle-crossing test (83 % specificity). The area under the receiver operating characteristic curve was 0.75 (95 % CI 0.60-0.90). Individuals who failed the obstacle-crossing test were 10.00 (95 % CI: 2.45-40.78) times more likely to fall in the first 3 months after discharge. The unadjusted logistic regression model correctly classified 76 % of the subjects. After adjusting for age, sex, days post stroke, and post-stroke disability, the odds ratio remained significant at 6.93 (95 % CI: 1.01-47.52) and correctly classified 79.5% of the participants. SIGNIFICANCE: The obstacle-crossing test may be a useful discharge assessment to identify ambulatory stroke survivors being discharged home who are likely to fall in the first 3 months post discharge. Modifications to improve the obstacle-crossing test sensitivity should be explored further.

Can Patient-Reported Outcome Measurement Information System Measures Differentiate Patients Who Will Undergo Hip and Knee Total Joint Arthroplasty: A Retrospective Case-Control Study.

BACKGROUND: The Patient-Reported Outcome Measurement Information System (PROMIS) can be used to monitor patients in population-health-based programs. However, it is unknown which measures are most appropriate to differentiate patients who will undergo hip or knee total joint arthroplasty (TJA) in a cohort of patients with osteoarthritis. METHODS: A retrospective cohort of new patients consulting for treatment from November 17, 2017 to April 20, 2020 (cases: hip: n = 157, knee: n = 112; randomly selected nonsurgical controls: hip: n = 314, knee: n = 224) was extracted from the electronic health record. We recorded demographics, comorbidity, and PROMIS scores for 8 domains (physical function, pain interference, pain intensity, anxiety, depression, sleep disturbance, ability to participate in social roles and activities, and fatigue). We performed descriptive statistics to characterize the cohorts and baseline PROMIS scores and conducted logistic regression models to determine which PROMIS domains differentiated patients undergoing hip and knee TJA. RESULTS: In univariate comparisons of PROMIS domains, the hip and knee surgical cohorts differed from controls in physical function (P < .01), pain interference (P < .01), and ability to participate in social roles and activities (P < .02). In logistic regression models informed by univariate analyses, PROMIS physical function was the only PROMIS measure to differentiate undergoing surgery in both hip and knee cohorts (P < .01). CONCLUSION: PROMIS physical function can differentiate TJA cases from nonsurgical controls in both hip and knee patients. These findings have implications for considering which PROMIS measures to administer in patients with hip and knee osteoarthritis.

Lumbar intervertebral disc diurnal deformations and T2 and T1rho relaxation times vary by spinal level and disc region.

PURPOSE: Magnetic resonance imaging (MRI) is routinely used to evaluate spine pathology; however, standard imaging findings weakly correlate to low back pain. Abnormal disc mechanical function is implicated as a cause of back pain but is not assessed using standard clinical MRI. Our objective was to utilize our established MRI protocol for measuring disc function to quantify disc mechanical function in a healthy cohort. METHODS: We recruited young, asymptomatic volunteers (6 male/6 female; age 18-30 years; BMI < 30) and used MRI to determine how diurnal deformations in disc height, volume, and perimeter were affected by spinal level, disc region, MRI biomarkers of disc health (T2, T1rho), and Pfirrmann grade. RESULTS: Lumbar discs deformed by a mean of -6.1% (95% CI: -7.6%, -4.7%) to -8.0% (CI: -10.6%, -5.4%) in height and -5.4% (CI: -7.6%, -3.3%) to -8.5% (CI: -11.0%, -6.0%) in volume from AM to PM across spinal levels. Regional deformations were more uniform in cranial lumbar levels and concentrated posteriorly in the caudal levels, reaching a maximum of 13.1% at L5-S1 (CI:-16.1%, -10.2%). T2 and T1rho relaxation times were greatest in the nucleus and varied circumferentially within the annulus. T2 relaxation times were greatest at the most cranial spinal levels and decreased caudally. In this young healthy cohort, we identified a weak association between nucleus T2 and the diurnal change in the perimeter. CONCLUSIONS: Spinal level is a key factor in determining regional disc deformations. Interestingly, deformations were concentrated in the posterior regions of caudal discs where disc herniation is most prevalent.

Predictors of Lumbar Spine Degeneration and Low Back Pain in the Community: The Johnston County Osteoarthritis Project.

OBJECTIVE: To determine the incidence and worsening of lumbar spine structure and low back pain (LBP) and whether they are predicted by demographic characteristics or clinical characteristics or appendicular joint osteoarthritis (OA). METHODS: Paired baseline (2003-2004) and follow-up (2006-2010) lumbar spine radiographs from the Johnston County Osteoarthritis Project were graded for osteophytes (OST), disc space narrowing (DSN), spondylolisthesis, and presence of facet joint OA (FOA). Spine OA was defined as at least mild OST and mild DSN at the same level for any level of the lumbar spine. LBP, comorbidities, and back injury were self-reported. Weibull models were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) of spine phenotypes accounting for potential predictors including demographic characteristics, clinical characteristics, comorbidities, obesity, and appendicular OA. RESULTS: Obesity was a consistent and strong predictor of incidence of DSN (HR 1.80 [95% CI 1.09-2.98]), spine OA (HR 1.56 [95% CI 1.01-2.41]), FOA (HR 4.99 [95% CI 1.46-17.10]), spondylolisthesis (HR 1.87 [95% CI 1.02-3.43]), and LBP (HR 1.75 [95% CI 1.19-2.56]), and worsening of DSN (HR 1.51 [95% CI 1.09-2.09]) and LBP (HR 1.51 [95% CI 1.12-2.06]). Knee OA was a predictor of incident FOA (HR 4.18 [95% CI 1.44-12.2]). Spine OA (HR 1.80 [95% CI 1.24-2.63]) and OST (HR 1.85 [95% CI 1.02-3.36]) were predictors of incidence of LBP. Hip OA (HR 1.39 [95% CI 1.04-1.85]) and OST (HR 1.58 [95% CI 1.00-2.49]) were predictors of LBP worsening. CONCLUSION: Among the multiple predictors of spine phenotypes, obesity was a common predictor for both incidence and worsening of lumbar spine degeneration and LBP.

Application of Heterogeneity of Treatment-Effects Methods: Exploratory Analyses of a Trial of Exercise-Based Interventions for Knee Osteoarthritis.

OBJECTIVE: To evaluate heterogeneity of treatment effects in a trial of exercise-based interventions for knee osteoarthritis (OA). METHODS: Participants (n = 350) were randomized to standard physical therapy (PT; n = 140), internet-based exercise training (IBET; n = 142), or wait list (WL; n = 68) control. We applied qualitative interaction trees (QUINT), a sequential partitioning method, and generalized unbiased interaction detection and estimation (GUIDE), a regression tree approach, to identify subgroups with greater improvements in Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) score over 4 months. Predictors included 24 demographic, clinical, and psychosocial characteristics. We conducted internal validation to estimate optimism (bias) in the range of mean outcome differences among arms. RESULTS: Both QUINT and GUIDE indicated that for participants with lower body mass index (BMI), IBET was better than PT (improvements of WOMAC ranged from 6.3 to 9.1 points lower), and for those with higher BMI and a longer duration of knee OA, PT was better than IBET (WOMAC improvement was 6.3 points). In GUIDE analyses comparing PT or IBET to WL, participants not employed had improvements in WOMAC ranging from 1.8 to 6.8 points lower with PT or IBT versus WL. From internal validation, there were large corrections to the mean outcome differences among arms; however, after correction, some differences remained in the clinically meaningful range. CONCLUSION: Results suggest there may be subgroups who experience greater improvement in symptoms from PT or IBET, and this finding could guide referrals and future trials. However, uncertainty persists for specific treatment-effects size estimates and how they apply beyond this study sample.

Expanding access to rehabilitation using mobile health to address musculoskeletal pain and disability.

Introduction: Musculoskeletal (MSK) disorders such as low back pain and osteoarthritis are a leading cause of disability and the leading contributor to the need for rehabilitation services globally. This need has surpassed the availability of trained clinicians; even in urban areas where services and providers are thought to be more abundant, access can be challenged by transportation options and financial costs associated with travel, care and lost time from work. However, continuing standard of fully in-person rehabilitation care for MSK-associated pain and disability may no longer be necessary. With increased ownership or access to even a basic mobile phone device, and evidence for remote management by trained clinicians, some individuals with MSK disorders may be able to continue their rehabilitation regimen predominantly from home after initial evaluation in primary care or an outpatient clinic. Methods: This manuscript describes application of a framework we used to culturally and contextually adapt an evidence-based approach for leveraging digital health technology using a mobile phone (mHealth) to expand access to rehabilitation services for MSK-associated pain and disability. We then conducted a multi-level analysis of policies related to the adapted approach for rehabilitation service delivery to identify opportunities to support sustainability. Results: Our study was conducted in Tanzania, a lower-middle income country with their first National Rehabilitation Strategic Plan released in 2021. Lessons learned can be applied even to countries with greater infrastructure or fewer barriers. The seven-step adaptation framework used can be applied in other regions to improve the likelihood of local mHealth adoption and implementation. Our practice and policy assessment for Tanzania can be applied in other regions and used collaboratively with government officials in support of building or implementing a national rehabilitation strategic plan. Conclusion: The work described, lessons learned and components of the plan are generalizable globally and can improve access to rehabilitation services using mHealth to address the significant and increasing burden of disability.

Immune cell profiles in synovial fluid after anterior cruciate ligament and meniscus injuries.

BACKGROUND: Anterior cruciate ligament (ACL) and meniscus tears are common knee injuries. Despite the high rate of post-traumatic osteoarthritis (PTOA) following these injuries, the contributing factors remain unclear. In this study, we characterized the immune cell profiles of normal and injured joints at the time of ACL and meniscal surgeries. METHODS: Twenty-nine patients (14 meniscus-injured and 15 ACL-injured) undergoing ACL and/or meniscus surgery but with a normal contralateral knee were recruited. During surgery, synovial fluid was aspirated from both normal and injured knees. Synovial fluid cells were pelleted, washed, and stained with an antibody cocktail consisting of fluorescent antibodies for cell surface proteins. Analysis of immune cells in the synovial fluid was performed by polychromatic flow cytometry. A broad spectrum immune cell panel was used in the first 10 subjects. Based on these results, a T cell-specific panel was used in the subsequent 19 subjects. RESULTS: Using the broad spectrum immune cell panel, we detected significantly more total viable cells and CD3 T cells in the injured compared to the paired normal knees. In addition, there were significantly more injured knees with T cells above a 500-cell threshold. Within the injured knees, CD4 and CD8 T cells were able to be differentiated into subsets. The frequency of total CD4 T cells was significantly different among injury types, but no statistical differences were detected among CD4 and CD8 T cell subsets by injury type. CONCLUSIONS: Our findings provide foundational data showing that ACL and meniscus injuries induce an immune cell-rich microenvironment that consists primarily of T cells with multiple T helper phenotypes. Future studies investigating the relationship between immune cells and joint degeneration may provide an enhanced understanding of the pathophysiology of PTOA following joint injury.

Mechanical metrics may show improved ability to predict osteoarthritis compared to T1rho mapping.

Changes in cartilage structure and composition are commonly observed during the progression of osteoarthritis (OA). Importantly, quantitative magnetic resonance imaging (MRI) methods, such as T1rho relaxation imaging, can noninvasively provide in vivo metrics that reflect changes in cartilage composition and therefore have the potential for use in early OA detection. Changes in cartilage mechanical properties are also hallmarks of OA cartilage; thus, measurement of cartilage mechanical properties may also be beneficial for earlier OA detection. However, the relative predictive ability of compositional versus mechanical properties in detecting OA has yet to be determined. Therefore, we developed logistic regression models predicting OA status in an ex vivo environment using several mechanical and compositional metrics to assess which metrics most effectively predict OA status. Specifically, in this study the compositional metric analyzed was the T1rho relaxation time, while the mechanical metrics analyzed were the stiffness and recovery (defined as a measure of how quickly cartilage returns to its original shape after loading) of the cartilage. Cartilage recovery had the best predictive ability of OA status both alone and in a multivariate model including the T1rho relaxation time. These findings highlight the potential of cartilage recovery as a non-invasive marker of in vivo cartilage health and motivate future investigation of this metric clinically.