Cognitive functional therapy with or without movement sensor biofeedback versus usual care for chronic, disabling low back pain (RESTORE): a randomised, controlled, three-arm, parallel group, phase 3, clinical trial.

BACKGROUND: Low back pain is the leading cause of years lived with disability globally, but most interventions have only short-lasting, small to moderate effects. Cognitive functional therapy (CFT) is an individualised approach that targets unhelpful pain-related cognitions, emotions, and behaviours that contribute to pain and disability. Movement sensor biofeedback might enhance treatment effects. We aimed to compare the effectiveness and economic efficiency of CFT, delivered with or without movement sensor biofeedback, with usual care for patients with chronic, disabling low back pain. METHODS: RESTORE was a randomised, controlled, three-arm, parallel group, phase 3 trial, done in 20 primary care physiotherapy clinics in Australia. We recruited adults (aged ≥18 years) with low back pain lasting more than 3 months with at least moderate pain-related physical activity limitation. Exclusion criteria were serious spinal pathology (eg, fracture, infection, or cancer), any medical condition that prevented being physically active, being pregnant or having given birth within the previous 3 months, inadequate English literacy for the study's questionnaires and instructions, a skin allergy to hypoallergenic tape adhesives, surgery scheduled within 3 months, or an unwillingness to travel to trial sites. Participants were randomly assigned (1:1:1) via a centralised adaptive schedule to usual care, CFT only, or CFT plus biofeedback. The primary clinical outcome was activity limitation at 13 weeks, self-reported by participants using the 24-point Roland Morris Disability Questionnaire. The primary economic outcome was quality-adjusted life-years (QALYs). Participants in both interventions received up to seven treatment sessions over 12 weeks plus a booster session at 26 weeks. Physiotherapists and patients were not masked. This trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12618001396213. FINDINGS: Between Oct 23, 2018 and Aug 3, 2020, we assessed 1011 patients for eligibility. After excluding 519 (51·3%) ineligible patients, we randomly assigned 492 (48·7%) participants; 164 (33%) to CFT only, 163 (33%) to CFT plus biofeedback, and 165 (34%) to usual care. Both interventions were more effective than usual care (CFT only mean difference -4·6 [95% CI -5·9 to -3·4] and CFT plus biofeedback mean difference -4·6 [-5·8 to -3·3]) for activity limitation at 13 weeks (primary endpoint). Effect sizes were similar at 52 weeks. Both interventions were also more effective than usual care for QALYs, and much less costly in terms of societal costs (direct and indirect costs and productivity losses; -AU$5276 [-10 529 to -24) and -8211 (-12 923 to -3500). INTERPRETATION: CFT can produce large and sustained improvements for people with chronic disabling low back pain at considerably lower societal cost than that of usual care. FUNDING: Australian National Health and Medical Research Council and Curtin University.

Concurrent validity of DorsaVi wireless motion sensor system Version 6 and the Vicon motion analysis system during lifting.

BACKGROUND: Wearable sensor technology may allow accurate monitoring of spine movement outside a clinical setting. The concurrent validity of wearable sensors during multiplane tasks, such as lifting, is unknown. This study assessed DorsaVi Version 6 sensors for their concurrent validity with the Vicon motion analysis system for measuring lumbar flexion during lifting. METHODS: Twelve participants (nine with, and three without back pain) wore sensors on T12 and S2 spinal levels with Vicon surface markers attached to those sensors. Participants performed 5 symmetrical (lifting from front) and 20 asymmetrical lifts (alternate lifting from left and right). The global-T12-angle, global-S2-angle and the angle between these two sensors (relative-lumbar-angle) were output in the sagittal plane. Agreement between systems was determined through-range and at peak flexion, using multilevel mixed-effects regression models to calculate root mean square errors and standard deviation. Mean differences and limits of agreement for peak flexion were calculated using the Bland Altman method. RESULTS: For through-range measures of symmetrical lifts, root mean squared errors (standard deviation) were 0.86° (0.78) at global-T12-angle, 0.90° (0.84) at global-S2-angle and 1.34° (1.25) at relative-lumbar-angle. For through-range measures of asymmetrical lifts, root mean squared errors (standard deviation) were 1.84° (1.58) at global-T12-angle, 1.90° (1.65) at global-S2-angle and 1.70° (1.54) at relative-lumbar-angle. The mean difference (95% limit of agreement) for peak flexion of symmetrical lifts, was - 0.90° (-6.80 to 5.00) for global-T12-angle, 0.60° (-2.16 to 3.36) for global-S2-angle and - 1.20° (-8.06 to 5.67) for relative-lumbar-angle. The mean difference (95% limit of agreement) for peak flexion of asymmetrical lifts was - 1.59° (-8.66 to 5.48) for global-T12-angle, -0.60° (-7.00 to 5.79) for global-S2-angle and - 0.84° (-8.55 to 6.88) for relative-lumbar-angle. CONCLUSION: The root means squared errors were slightly better for symmetrical lifts than they were for asymmetrical lifts. Mean differences and 95% limits of agreement showed variability across lift types. However, the root mean squared errors for all lifts were better than previous research and below clinically acceptable thresholds. This research supports the use of lumbar flexion measurements from these inertial measurement units in populations with low back pain, where multi-plane lifting movements are assessed.

Predicting Knee Joint Kinematics from Wearable Sensor Data in People with Knee Osteoarthritis and Clinical Considerations for Future Machine Learning Models.

Deep learning models developed to predict knee joint kinematics are usually trained on inertial measurement unit (IMU) data from healthy people and only for the activity of walking. Yet, people with knee osteoarthritis have difficulties with other activities and there are a lack of studies using IMU training data from this population. Our objective was to conduct a proof-of-concept study to determine the feasibility of using IMU training data from people with knee osteoarthritis performing multiple clinically important activities to predict knee joint sagittal plane kinematics using a deep learning approach. We trained a bidirectional long short-term memory model on IMU data from 17 participants with knee osteoarthritis to estimate knee joint flexion kinematics for phases of walking, transitioning to and from a chair, and negotiating stairs. We tested two models, a double-leg model (four IMUs) and a single-leg model (two IMUs). The single-leg model demonstrated less prediction error compared to the double-leg model. Across the different activity phases, RMSE (SD) ranged from 7.04° (2.6) to 11.78° (6.04), MAE (SD) from 5.99° (2.34) to 10.37° (5.44), and Pearson's R from 0.85 to 0.99 using leave-one-subject-out cross-validation. This study demonstrates the feasibility of using IMU training data from people who have knee osteoarthritis for the prediction of kinematics for multiple clinically relevant activities.

Does intra-lumbar flexion during lifting differ in manual workers with and without a history of low back pain? A cross-sectional laboratory study.

Advice to limit or avoid a flexed lumbar curvature during lifting is widely promoted to reduce the risk of low back pain (LBP), yet there is very limited evidence to support this relationship. To provide higher quality evidence this study compared intra-lumbar flexion in manual workers with (n = 21) and without a history of LBP (n = 21) during a repeated lifting task. In contrast to common expectations, the LBP group demonstrated less peak absolute intra-lumbar flexion during lifting than the noLBP group [adjusted difference -3.7° (95%CI -6.9 to -0.6)]. The LBP group was also further from the end of range intra-lumbar flexion and did not use more intra-lumbar range of motion during any lift condition (both symmetrical and asymmetrical lifts and different box loads). Peak absolute intra-lumbar flexion was more variable in the LBP group during lifting and both groups increased their peak absolute intra-lumbar flexion over the lift repetitions. This high-quality capture of intra-lumbar spine flexion during repeated lifting in a clinically relevant cohort questions dominant safe lifting advice.Practitioner summary: Lifting remains a common trigger for low back pain (LBP). This study demonstrated that people with LBP, lift with less intra-lumbar flexion than those without LBP. Providing the best quality in-vivo laboratory evidence, that greater intra-lumbar flexion is not associated with LBP in manual workers, raising questions about lifting advice.

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.

A conceptual framework for prognostic research.

BACKGROUND: Prognostic research has many important purposes, including (i) describing the natural history and clinical course of health conditions, (ii) investigating variables associated with health outcomes of interest, (iii) estimating an individual's probability of developing different outcomes, (iv) investigating the clinical application of prediction models, and (v) investigating determinants of recovery that can inform the development of interventions to improve patient outcomes. But much prognostic research has been poorly conducted and interpreted, indicating that a number of conceptual areas are often misunderstood. Recent initiatives to improve this include the Prognosis Research Strategy (PROGRESS) and the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) Statement. In this paper, we aim to show how different categories of prognostic research relate to each other, to differentiate exploratory and confirmatory studies, discuss moderators and mediators, and to show how important it is to understand study designs and the differences between prediction and causation. MAIN TEXT: We propose that there are four main objectives of prognostic studies - description, association, prediction and causation. By causation, we mean the effect of prediction and decision rules on outcomes as determined by intervention studies and the investigation of whether a prognostic factor is a determinant of outcome (on the causal pathway). These either fall under the umbrella of exploratory (description, association, and prediction model development) or confirmatory (prediction model external validation and investigation of causation). Including considerations of causation within a prognostic framework provides a more comprehensive roadmap of how different types of studies conceptually relate to each other, and better clarity about appropriate model performance measures and the inferences that can be drawn from different types of prognostic studies. We also propose definitions of 'candidate prognostic factors', 'prognostic factors', 'prognostic determinants (causal)' and 'prognostic markers (non-causal)'. Furthermore, we address common conceptual misunderstandings related to study design, analysis, and interpretation of multivariable models from the perspectives of association, prediction and causation. CONCLUSION: This paper uses a framework to clarify some concepts in prognostic research that remain poorly understood and implemented, to stimulate discussion about how prognostic studies can be strengthened and appropriately interpreted.

Cognitive Functional Therapy for People with Nonspecific Persistent Low Back Pain in a Secondary Care Setting-A Propensity Matched, Case-Control Feasibility Study.

BACKGROUND: Effective, inexpensive, and low-risk interventions are needed for patients with nonspecific persistent low back pain (NS-PLBP) who are unresponsive to primary care interventions. Cognitive functional therapy (CFT) is a multidimensional behavioral self-management approach that has demonstrated promising results in primary care and has not been tested in secondary care. OBJECTIVE: To investigate the effect of CFT and compare it with usual care for patients with NS-PLBP. DESIGN: Case-control study. SETTING: A secondary care spine center. SUBJECTS: Thirty-nine patients received a CFT intervention and were matched using propensity scoring to 185 control patients receiving usual care. METHODS: The primary outcome was Roland Morris Disability Questionnaire (0-100 scale) score. Group-level differences at six- and 12-month follow-up were estimated using mixed-effects linear regression. RESULTS: At six-month follow-up, a statistically significant and clinically relevant difference in disability favored the CFT group (-20.7, 95% confidence interval [CI] = -27.2 to -14.2, P < 0.001). Significant differences also occurred for LBP and leg pain, fear, anxiety, and catastrophizing in favor of CFT. At 12-month follow-up, the difference in disability was smaller and no longer statistically significant (-8.1, 95% CI = -17.4 to 1.2, P = 0.086). Differences in leg pain intensity and fear remained significantly in favor of CFT. Treatment satisfaction was significantly higher in the CFT group at six- (93% vs 66%) and 12-month (84% vs 52%) follow-up. CONCLUSIONS: These findings support that CFT is beneficial for patients with NS-PLBP who are unresponsive to primary care interventions. Subsequent randomized controlled trials could incorporate booster sessions, which may result in larger effects at 12-month follow-up.

What Influences Patient Satisfaction after TKA? A Qualitative Investigation.

BACKGROUND: Patient satisfaction is a common measure of the success of an orthopaedic intervention. However, there is poor understanding of what satisfaction means to patients or what influences it. QUESTIONS/PURPOSES: Using qualitative study methodology in patients undergoing TKA, we asked: (1) What does it mean to be satisfied after TKA? (2) What factors influence satisfaction levels after TKA? METHODS: People in a hospital registry who had completed 12-month follow-up questionnaires and were not more than 18 months post-TKA at the time of sampling were eligible (n = 121). To recruit a sample that provided insight into a range of TKA experiences, we divided eligible candidates on the registry into quadrants based on their responder status and satisfaction level. A responder was an individual who experienced a clinically meaningful change in pain and/or function on the WOMAC according to the Outcome Measures in Rheumatology-Osteoarthritis Research Society International (OMERACT-OARSI) responder criteria. Individuals were considered satisfied unless they indicated somewhat dissatisfied or very dissatisfied for one or more of the four items on the Self-Administered Patient Satisfaction Scale. From the resulting quadrants: responder satisfied, nonresponder satisfied, nonresponder dissatisfied, responder dissatisfied, we identified men and women with a range of ages and invited them to participate (n = 85). The final sample (n = 40), consisted of 10 responder satisfied, nine nonresponder satisfied, eight nonresponder dissatisfied, and 13 responder dissatisfied; 71% were women, with a mean age of 71 ± 7 years and a mean time since TKA surgery of 17 ± 2 months (range 13 to 25 months). Interview transcripts were analyzed by looking for factors in the participants' narrative that appeared to underscore their level of satisfaction and attaching inductive (data-derived, rather than a priori derived) codes to relevant sections of text. Coded data from participants who reported high and low levels of satisfaction were compared/contrasted and emerging patterns were mapped into a conceptual model. Recruitment continued until no new information was uncovered in data analysis of subsequent interviews, signalling to the researchers that further interviews would not change the key themes identified and data collection could cease. RESULTS: In those with high satisfaction levels, satisfaction was conceptualized as an improvement in pain and function. In those with low satisfaction levels, rather than an improvement, satisfaction was conceptualized as completely resolving all symptoms and functional limitations. In addition, we identified three pathways through which participants reached different levels of low and high satisfaction: (1) The full-glass pathway, characterized by no or minimal ongoing symptoms and functional deficits, which consistently led to high levels of satisfaction; (2) the glass-half-full pathway, characterized by ongoing symptoms and functional limitations, which led to high satisfaction; and (3) the glass-half-empty pathway, also characterized by ongoing symptoms and functional limitations, which led to low satisfaction levels. The latter two pathways were mediated by three core mechanisms (recalibration, reframing valued activities, and reconceptualization) influenced either positively or negatively by (1) a persons' thoughts and feelings such as optimism, self-efficacy, pain catastrophizing, external locus of control; and (2) social and contextual factors such as fulfilment of social roles, therapeutic alliance, lack of family/social support. CONCLUSIONS: This qualitative study suggests that for preoperative patients in whom unrealistically high hopes for complete symptom resolution and restoration of functional capacity persists, it may be appropriate to direct them away from TKA due to the risk of low satisfaction. For postoperative patients troubled by ongoing symptoms or functional limitations, clinicians may improve levels of satisfaction by targeting the three core mechanisms (recalibration, reframing valued activities, and reconceptualization) through addressing modifiable negative thoughts and feelings in interventions such as psychology or psychotherapy; and negative social and contextual factors by promoting a strong therapeutic alliance and engagement in community activities. Given that these factors may be identifiable preoperatively, future research is needed to explore if and how addressing them preoperatively may improve satisfaction post-TKA. LEVEL OF EVIDENCE: Level IV, therapeutic study.

Does movement matter in people with back pain? Investigating 'atypical' lumbo-pelvic kinematics in people with and without back pain using wireless movement sensors.

BACKGROUND: Interventions for low back pain (LBP) commonly target 'dysfunctional' or atypical lumbo-pelvic kinematics in the belief that correcting aberrant movement improves patients' pain and activity outcomes. If atypical kinematic parameters and postures have a relationship to LBP, they could be expected to more prevalent in people with LBP compared to people without LBP (NoLBP). This exploratory study measured, defined and compared atypical kinematic parameters in people with and without LBP. METHODS: Wireless inertial motion and EMG sensors were used to measure lumbo-pelvic kinematics during standing trunk flexion (range of motion (ROM), timing, sequence coordination, and extensor muscle activation) and in sitting (relative sitting position, pelvic tilt range) in a sample of 126 of adults without LBP and 140 chronic LBP subjects. Atypical movement was defined using the 10th/90th centiles of the NoLBP group. Mean differences and prevalence rates for atypical movement were calculated. Dichotomised pain scores for 'high-pain-on-bending' and 'high-pain-on-sitting' were tested for their association with atypical kinematic variables. RESULTS: For standing flexion, significant mean differences, after adjusting for age and gender factors, were seen for the LBP group with (i) reduced ROM (trunk flexion (NoLBP 111o, LBP 93o, p < .0001), lumbar flexion (NoLBP 52o, LBP 46o, p < .0001), pelvic flexion (NoLBP 59o, LBP 48o, p < .0001), (ii) greater extensor muscle activation for the LBP group (NoLBP 0.012, LBP 0.25 p < .0001), (iii) a greater delay in pelvic motion at the onset of flexion (NoLBP - 0.21 s; LBP - 0.36 s, p = 0.023), (iv) and longer movement duration for the LBP group (NoLBP 2.28 s; LBP 3.18 s, p < .0001). Atypical movement was significantly more prevalent in the LBP group for small trunk (× 5.4), lumbar (× 3.0) and pelvic ROM (× 3.9), low FRR (× 4.9), delayed pelvic motion at 20o flexion (× 2.9), and longer movement duration (× 4.7). No differences between groups were seen for any sitting parameters. High pain intensity was significantly associated with small lumbar ROM and pelvic ROM. CONCLUSION: Significant movement differences during flexion were seen in people with LBP, with a higher prevalence of small ROM, slower movement, delayed pelvic movement and greater lumbar extensor muscle activation but without differences for any sitting parameter.

The association between subgroups of MRI findings identified with latent class analysis and low back pain in 40-year-old Danes.

BACKGROUND: Research into the clinical importance of spinal MRI findings in patients with low back pain (LBP) has primarily focused on single imaging findings, such as Modic changes or disc degeneration, and found only weak associations with the presence of pain. However, numerous MRI findings almost always co-exist in the lumbar spine and are often present at more than one lumbar level. It is possible that multiple MRI findings are more strongly associated with LBP than single MRI findings. Latent Class Analysis is a statistical method that has recently been tested and found useful for identifying latent classes (subgroups) of MRI findings within multivariable datasets. The purpose of this study was to investigate the association between subgroups of MRI findings and the presence of LBP in people from the general population. METHODS: To identify subgroups of lumbar MRI findings with potential clinical relevance, Latent Class Analysis was initially performed on a clinical dataset of 631 patients seeking care for LBP. Subsequently, 412 participants in a general population cohort (the 'Backs on Funen' project) were statistically allocated to those existing subgroups by Latent Class Analysis, matching their MRI findings at a segmental level. The subgroups containing MRI findings from the general population were then organised into hypothetical pathways of degeneration and the association between subgroups in the pathways and the presence of LBP was tested using exact logistic regression. RESULTS: Six subgroups were identified in the clinical dataset and the data from the general population cohort fitted the subgroups well, with a median posterior probability of 93%-100%. These six subgroups described two pathways of increasing degeneration on upper (L1-L3) and lower (L4-L5) lumbar levels. An association with LBP was found for the subgroups describing severe and multiple degenerative MRI findings at the lower lumbar levels but none of the other subgroups were associated with LBP. CONCLUSION: Although MRI findings are common in asymptomatic people and the association between single MRI findings and LBP is often weak, our results suggest that subgroups of multiple and severe lumbar MRI findings have a stronger association with LBP than those with milder degrees of degeneration.

Subgroups of lumbo-pelvic flexion kinematics are present in people with and without persistent low back pain.

BACKGROUND: Movement dysfunctions have been associated with persistent low back pain (LBP) but optimal treatment remains unclear. One possibility is that subgroups of persistent LBP patients have differing movement characteristics and therefore different responses to interventions. This study examined if there were patterns of flexion-related lumbo-pelvic kinematic and EMG parameters that might define subgroups of movement. METHODS: This was a cross-sectional, observational study of 126 people without any history of significant LBP and 140 people with persistent LBP (n = 266). Wireless motion and surface EMG sensors collected lumbo-pelvic data on flexion parameters (range of motion (ROM) of trunk, lumbar, and pelvis), speed, sequence coordination and timing, and EMG extensor muscle activity in forward bending (flexion relaxation)), and sitting parameters (relative position, pelvic tilt range and tilt ratio). Latent class analysis was used to identify patterns in these parameters. RESULTS: Four subgroups with high probabilities of membership were found (mean 94.9%, SD10.1%). Subgroup 1 (n = 133 people, 26% LBP) had the greatest range of trunk flexion, fastest movement, full flexion relaxation, and synchronous lumbar versus pelvic movement. Subgroup 2 (n = 73, 71% LBP) had the greatest lumbar ROM, less flexion relaxation, and a 0.9 s lag of pelvic movement. Subgroup 3 (n = 41, 83% LBP) had the smallest lumbar ROM, a 0.6 s delay of lumbar movement (compared to pelvic movement), and less flexion relaxation than subgroup 2. Subgroup 4 (n = 19 people, 100% LBP) had the least flexion relaxation, slowest movement, greatest delay of pelvic movement and the smallest pelvic ROM. These patterns could be described as standard (subgroup 1), lumbar dominant (subgroup 2), pelvic dominant (subgroup 3) and guarded (subgroup 4). Significant post-hoc differences were seen between subgroups for most lumbo-pelvic kinematic and EMG parameters. There was greater direction-specific pain and activity limitation scores for subgroup 4 compared to other groups, and a greater percentage of people with leg pain in subgroups 2 and 4. CONCLUSION: Four subgroups of lumbo-pelvic flexion kinematics were revealed with an unequal distribution among people with and without a history of persistent LBP. Such subgroups may have implications for which patients are likely to respond to movement-based interventions.

How can latent trajectories of back pain be translated into defined subgroups?

BACKGROUND: Similar types of trajectory patterns have been identified by Latent Class Analyses (LCA) across multiple low back pain (LBP) cohorts, but these patterns are impractical to apply to new cohorts or individual patients. It would be useful to be able to identify trajectory subgroups from descriptive definitions, as a way to apply the same definitions of mutually exclusive subgroups across populations. In this study, we investigated if the course trajectories of two LBP cohorts fitted with previously suggested trajectory subgroup definitions, how distinctly different these subgroups were, and if the subgroup definitions matched with LCA-derived patterns. METHODS: Weekly measures of LBP intensity and frequency during 1 year were available from two clinical cohorts. We applied definitions of 16 possible trajectory subgroups to these observations and calculated the prevalence of the subgroups. The probability of belonging to each of eight LCA-derived patterns was determined within each subgroup. LBP intensity and frequency were described within subgroups and the subgroups of 'fluctuating' and 'episodic' LBP were compared on clinical characteristics. RESULTS: All of 1077 observed trajectories fitted with the defined subgroups. 'Severe episodic LBP' was the most frequent pattern in both cohorts and 'ongoing LBP' was almost non-existing. There was a clear relationship between the defined trajectory subgroups and LCA-derived trajectory patterns, as in most subgroups, all patients had high probabilities of belonging to only one or two of the LCA patterns. The characteristics of the six defined subgroups with minor LBP were very similar. 'Fluctuating LBP' subgroups were significantly more distressed, had more intense leg pain, higher levels of activity limitation, and more negative expectations about future LBP than 'episodic LBP' subgroups. CONCLUSION: Previously suggested definitions of LBP trajectory subgroups could be readily applied to patients' observed data resulting in subgroups that matched well with LCA-derived trajectory patterns. We suggest that the number of trajectory subgroups can be reduced by merging some subgroups with minor LBP. Stable levels of LBP were almost not observed and we suggest that minor fluctuations in pain intensity might be conceptualised as 'ongoing LBP'. Lastly, we found clear support for distinguishing between fluctuating and episodic LBP.

Latent class analysis derived subgroups of low back pain patients - do they have prognostic capacity?

BACKGROUND: Heterogeneity in patients with low back pain is well recognised and different approaches to subgrouping have been proposed. One statistical technique that is increasingly being used is Latent Class Analysis as it performs subgrouping based on pattern recognition with high accuracy. Previously, we developed two novel suggestions for subgrouping patients with low back pain based on Latent Class Analysis of patient baseline characteristics (patient history and physical examination), which resulted in 7 subgroups when using a single-stage analysis, and 9 subgroups when using a two-stage approach. However, their prognostic capacity was unexplored. This study (i) determined whether the subgrouping approaches were associated with the future outcomes of pain intensity, pain frequency and disability, (ii) assessed whether one of these two approaches was more strongly or more consistently associated with these outcomes, and (iii) assessed the performance of the novel subgroupings as compared to the following variables: two existing subgrouping tools (STarT Back Tool and Quebec Task Force classification), four baseline characteristics and a group of previously identified domain-specific patient categorisations (collectively, the 'comparator variables'). METHODS: This was a longitudinal cohort study of 928 patients consulting for low back pain in primary care. The associations between each subgroup approach and outcomes at 2 weeks, 3 and 12 months, and with weekly SMS responses were tested in linear regression models, and their prognostic capacity (variance explained) was compared to that of the comparator variables listed above. RESULTS: The two previously identified subgroupings were similarly associated with all outcomes. The prognostic capacity of both subgroupings was better than that of the comparator variables, except for participants' recovery beliefs and the domain-specific categorisations, but was still limited. The explained variance ranged from 4.3%-6.9% for pain intensity and from 6.8%-20.3% for disability, and highest at the 2 weeks follow-up. CONCLUSIONS: Latent Class-derived subgroups provided additional prognostic information when compared to a range of variables, but the improvements were not substantial enough to warrant further development into a new prognostic tool. Further research could investigate if these novel subgrouping approaches may help to improve existing tools that subgroup low back pain patients.

Identifying subgroups of patients using latent class analysis: should we use a single-stage or a two-stage approach? A methodological study using a cohort of patients with low back pain.

BACKGROUND: Heterogeneity in patients with low back pain (LBP) is well recognised and different approaches to subgrouping have been proposed. Latent Class Analysis (LCA) is a statistical technique that is increasingly being used to identify subgroups based on patient characteristics. However, as LBP is a complex multi-domain condition, the optimal approach when using LCA is unknown. Therefore, this paper describes the exploration of two approaches to LCA that may help improve the identification of clinically relevant and interpretable LBP subgroups. METHODS: From 928 LBP patients consulting a chiropractor, baseline data were used as input to the statistical subgrouping. In a single-stage LCA, all variables were modelled simultaneously to identify patient subgroups. In a two-stage LCA, we used the latent class membership from our previously published LCA within each of six domains of health (activity, contextual factors, pain, participation, physical impairment and psychology) (first stage) as the variables entered into the second stage of the two-stage LCA to identify patient subgroups. The description of the results of the single-stage and two-stage LCA was based on a combination of statistical performance measures, qualitative evaluation of clinical interpretability (face validity) and a subgroup membership comparison. RESULTS: For the single-stage LCA, a model solution with seven patient subgroups was preferred, and for the two-stage LCA, a nine patient subgroup model. Both approaches identified similar, but not identical, patient subgroups characterised by (i) mild intermittent LBP, (ii) recent severe LBP and activity limitations, (iii) very recent severe LBP with both activity and participation limitations, (iv) work-related LBP, (v) LBP and several negative consequences and (vi) LBP with nerve root involvement. CONCLUSIONS: Both approaches identified clinically interpretable patient subgroups. The potential importance of these subgroups needs to be investigated by exploring whether they can be identified in other cohorts and by examining their possible association with patient outcomes. This may inform the selection of a preferred LCA approach.

Clinical course and prognosis of musculoskeletal pain in patients referred for physiotherapy: does pain site matter?

BACKGROUND: Danish patients with musculoskeletal disorders are commonly referred for primary care physiotherapy treatment but little is known about their general health status, pain diagnoses, clinical course and prognosis. The objectives of this study were to 1) describe the clinical course of patients with musculoskeletal disorders referred to physiotherapy, 2) identify predictors associated with a satisfactory outcome, and 3) determine the influence of the primary pain site diagnosis relative to those predictors. METHODS: This was a prospective cohort study of patients (n = 2,706) newly referred because of musculoskeletal pain to 30 physiotherapy practices from January 2012 to May 2012. Data were collected via a web-based questionnaire 1-2 days prior to the first physiotherapy consultation and at 6 weeks, 3 and 6 months, from clinical records (including primary musculoskeletal symptom diagnosis based on the ICPC-2 classification system), and from national registry data. The main outcome was the Patient Acceptable Symptom State. Potential predictors were analysed using backwards step-wise selection during longitudinal Generalised Estimating Equation regression modelling. To assess the influence of pain site on these associations, primary pain site diagnosis was added to the model. RESULTS: Of the patients included, 66% were female and the mean age was 48 (SD 15). The percentage of patients reporting their symptoms as acceptable was 32% at 6 weeks, 43% at 3 months and 52% at 6 months. A higher probability of satisfactory outcome was associated with place of residence, being retired, no compensation claim, less frequent pain, shorter duration of pain, lower levels of disability and fear avoidance, better mental health and being a non-smoker. Primary pain site diagnosis had little influence on these associations, and was not predictive of a satisfactory outcome. CONCLUSION: Only half of the patients rated their symptoms as acceptable at 6 months. Although satisfactory outcome was difficult to predict at an individual patient level, there were a number of prognostic factors that were associated with this outcome. These factors should be considered when developing generic prediction tools to assess the probability of satisfactory outcome in musculoskeletal physiotherapy patients, because the site of pain did not affect that prognostic association.

Clinically acceptable agreement between the ViMove wireless motion sensor system and the Vicon motion capture system when measuring lumbar region inclination motion in the sagittal and coronal planes.

BACKGROUND: Wireless, wearable, inertial motion sensor technology introduces new possibilities for monitoring spinal motion and pain in people during their daily activities of work, rest and play. There are many types of these wireless devices currently available but the precision in measurement and the magnitude of measurement error from such devices is often unknown. This study investigated the concurrent validity of one inertial motion sensor system (ViMove) for its ability to measure lumbar inclination motion, compared with the Vicon motion capture system. METHODS: To mimic the variability of movement patterns in a clinical population, a sample of 34 people were included - 18 with low back pain and 16 without low back pain. ViMove sensors were attached to each participant's skin at spinal levels T12 and S2, and Vicon surface markers were attached to the ViMove sensors. Three repetitions of end-range flexion inclination, extension inclination and lateral flexion inclination to both sides while standing were measured by both systems concurrently with short rest periods in between. Measurement agreement through the whole movement range was analysed using a multilevel mixed-effects regression model to calculate the root mean squared errors and the limits of agreement were calculated using the Bland Altman method. RESULTS: We calculated root mean squared errors (standard deviation) of 1.82° (±1.00°) in flexion inclination, 0.71° (±0.34°) in extension inclination, 0.77° (±0.24°) in right lateral flexion inclination and 0.98° (±0.69°) in left lateral flexion inclination. 95% limits of agreement ranged between -3.86° and 4.69° in flexion inclination, -2.15° and 1.91° in extension inclination, -2.37° and 2.05° in right lateral flexion inclination and -3.11° and 2.96° in left lateral flexion inclination. CONCLUSIONS: We found a clinically acceptable level of agreement between these two methods for measuring standing lumbar inclination motion in these two cardinal movement planes. Further research should investigate the ViMove system's ability to measure lumbar motion in more complex 3D functional movements and to measure changes of movement patterns related to treatment effects.

The prognostic ability of the STarT Back Tool was affected by episode duration.

PURPOSE: The prognostic ability of the STarT Back Tool (SBT) reportedly varies, but the factors affecting this are unclear. This study investigated the influences of care setting (chiropractic, GP, physiotherapy, spine centre), episode duration (0-2, 3-4, 4-12, >12 weeks), and outcome time period (3, 6, 12 months) on SBT prognostic ability. METHODS: This was a secondary analysis of data from three primary care cohorts [chiropractic (n = 416), GP (n = 265), and physiotherapy (n = 200) practices] and one cohort from a secondary care outpatient spine centre (n = 974) in Denmark. Care pathways were not systematically affected by SBT risk subgroup (non-stratified care). Using generalised estimating equations, we investigated statistical interactions between SBT risk subgroups and potentially influential factors on the prognostic ability of the SBT subgroups, when Roland Morris Disability Questionnaire scores were the outcome. RESULTS: SBT risk subgroup, age, care setting, and episode duration were all independent prognostic factors. The only investigated factor that modified the prognostic ability of the SBT subgroups was episode duration. CONCLUSIONS: These results indicate that the prognostic ability of the SBT in these non-stratified care settings was unaffected by care setting on its own. However, the prognosis of patients is affected by diverse clinical characteristics that differ between patient populations, many of which are not assessed by the SBT. When controlling for some of those factors and testing potential interactions, the results showed that only episode duration affected the SBT prognostic ability and, specifically, that the SBT was less predictive in very acute patients (<2 weeks duration).

Do MRI findings identify patients with low back pain or sciatica who respond better to particular interventions? A systematic review.

PURPOSE: Magnetic resonance imaging (MRI) can reveal a range of degenerative findings and anatomical abnormalities; however, the clinical importance of these remains uncertain and controversial. We aimed to investigate if the presence of MRI findings identifies patients with low back pain (LBP) or sciatica who respond better to particular interventions. METHODS: MEDLINE, EMBASE and CENTRAL databases were searched. We included RCTs investigating MRI findings as treatment effect modifiers for patients with LBP or sciatica. We excluded studies with specific diseases as the cause of LBP. Risk of bias was assessed using the criteria of the Cochrane Back Review Group. Each MRI finding was examined for its individual capacity for effect modification. RESULTS: Eight published trials met the inclusion criteria. The methodological quality of trials was inconsistent. Substantial variability in MRI findings, treatments and outcomes across the eight trials prevented pooling of data. Patients with Modic type 1 when compared with patients with Modic type 2 had greater improvements in function when treated by Diprospan (steroid) injection, compared with saline. Patients with central disc herniation when compared with patients without central disc herniation had greater improvements in pain when treated by surgery, compared with rehabilitation. CONCLUSIONS: Although individual trials suggested that some MRI findings might be effect modifiers for specific interventions, none of these interactions were investigated in more than a single trial. High quality, adequately powered trials investigating MRI findings as effect modifiers are essential to determine the clinical importance of MRI findings in LBP and sciatica ( PROSPERO: CRD42013006571).

How consistent are lordosis, range of movement and lumbo-pelvic rhythm in people with and without back pain?

BACKGROUND: Comparing movements/postures in people with and without lower back pain (LBP) may assist identifying LBP-specific dysfunction and its relationship to pain or activity limitation. This study compared the consistency in lumbo-pelvic posture and movement (range and pattern) in people with and without chronic LBP (>12 week's duration). METHODS: Wireless, wearable, inertial measurement units measured lumbar lordosis angle, range of movement (ROM) and lumbo-pelvic rhythm in adults (n = 63). Measurements were taken on three separate occasions: two tests on the same day with different raters and a third (intra-rater) test one to two weeks later. Participants performed five repetitions of tested postures or movements. Test data were captured automatically. Minimal detectable change scores (MDC90) provided estimates of between-test consistency. RESULTS: There was no significant difference between participants with and without LBP for lordosis angle. There were significant differences for pelvic flexion ROM (LBP 60.8°, NoLBP 54.8°, F(1,63) = 4.31, p = 0.04), lumbar right lateral flexion ROM (LBP 22.2°, NoLBP 24.6° F(1,63) = 4.48, p = .04), trunk right lateral flexion ROM (LBP 28.4°, NoLBP 31.7°, F(1,63) = 5.9, p = .02) and lumbar contribution to lumbo-pelvic rhythm in the LBP group (LBP 45.8 %, F(1,63) = 4.20, NoLBP 51.3 % p = .044). MDC90 estimates for intra and inter-rater comparisons were 10°-15° for lumbar lordosis, and 5°-15° for most ROM. For lumbo-pelvic rhythm, we found 8-15 % variation in lumbar contribution to flexion and lateral flexion and 36-56 % variation in extension. Good to excellent agreement (reliability) was seen between raters (mean r = .88, ICC (2,2)). CONCLUSION: Comparisons of ROM between people with and without LBP showed few differences between groups, with reduced relative lumbar contribution to trunk flexion. There was no difference between groups for lordosis. Wide, within-group differences were seen for both groups for ROM and lordosis. Due to variability between test occasions, changes would need to exceed 10°-15° for lumbar lordosis, 5°-15° for ROM components, and 8-15 % of lumbar contribution to lumbo-pelvic rhythm, to have 90 % confidence that movements had actually changed. Lordosis, range of movement and lumbo-pelvic rhythm typically demonstrate variability between same-day and different-day tests. This variability needs to be considered when interpreting posture and movement changes.

What have we learned from ten years of trajectory research in low back pain?

BACKGROUND: Non-specific low back pain (LBP) is often categorised as acute, subacute or chronic by focusing on the duration of the current episode. However, more than twenty years ago this concept was challenged by a recognition that LBP is often an episodic condition. This episodic nature also means that the course of LBP is not well described by an overall population mean. Therefore, studies have investigated if specific LBP trajectories could be identified which better reflect individuals' course patterns. Following a pioneering study into LBP trajectories published by Dunn et al. in 2006, a number of subsequent studies have also identified LBP trajectories and it is timely to provide an overview of their findings and discuss how insights into these trajectories may be helpful for improving our understanding of LBP and its clinical management. DISCUSSION: LBP trajectories in adults have been identified by data driven approaches in ten cohorts, and these have consistently demonstrated that different trajectory patterns exist. Despite some differences between studies, common trajectories have been identified across settings and countries, which have associations with a number of patient characteristics from different health domains. One study has demonstrated that in many people such trajectories are stable over several years. LBP trajectories seem to be recognisable by patients, and appealing to clinicians, and we discuss their potential usefulness as prognostic factors, effect moderators, and as a tool to support communication with patients. CONCLUSIONS: Investigations of trajectories underpin the notion that differentiation between acute and chronic LBP is overly simplistic, and we believe it is time to shift from this paradigm to one that focuses on trajectories over time. We suggest that trajectory patterns may represent practical phenotypes of LBP that could improve the clinical dialogue with patients, and might have a potential for supporting clinical decision making, but their usefulness is still underexplored.