Estimating the Risk of Chronic Pain: Development and Validation of a Prognostic Model (PICKUP) for Patients with Acute Low Back Pain

Perceptions of advice for acute low back pain: a content analysis of qualitative data collected in a randomised experiment

OBJECTIVES

To explore how people perceive three different forms of advice for acute low back pain (LBP).

DESIGN

Content analysis of qualitative data collected in a three-arm randomised experiment.

PARTICIPANTS

2200 participants with acute LBP (ie, pain duration for ≤6 weeks) were randomly assigned to receive three types of advice: guideline advice and guideline advice with the addition of either brief pain science or ergonomics messages.

PRIMARY AND SECONDARY OUTCOMES

After receiving the advice, participants answered two questions: 'If your health professional gave you this advice, how would it make you feel?' and 'If your health professional gave you this advice, what treatments (if any) do you think you would need?' Two researchers coded responses using deductive content analysis.

RESULTS

We analysed 4400 free-text responses from 2200 participants. There were little to no differences in participants' feelings, thoughts and expectations after receiving three types of advice for acute LBP. Participants most commonly expressed feeling positive about the advice (38%-35%), reassured (23%-22%) and empowered (10%-8%). Some expressed being unhappy or being frustrated with the advice (4%-3%). Participants most commonly thought they needed no treatment apart from staying active, followed by exercise and medication.

CONCLUSIONS

Guideline advice with or without the addition of brief pain science or ergonomics messages generated positive feelings, reassurance or a sense of empowerment in many people with acute LBP, with no difference between types of advice.

TRIAL REGISTRATION NUMBER

ACTRN12623000364673.

Stratified health care for low back pain using the STarT Back approach: Holy Grail or doomed to fail?

ABSTRACT

There have been at least 7 separate randomised controlled trials published between 2011 and 2023 that have examined primary care for nonspecific low back pain informed by the STarT Back approach to stratified care based on risk prediction, compared with care not informed by this approach. The results, across 4 countries, have been contrasting-some demonstrating effectiveness and/or efficiency of this approach, others finding no benefits over comparison interventions. This review considers possible explanations for the differences, particularly whether this is related to poor predictive performance of the STarT Back risk-prediction tool or to variable degrees of success in implementing the whole STarT Back approach (subgrouping and matching treatments to predicted risk of poor outcomes) in different healthcare systems. The review concludes that although there is room for improving and expanding the predictive value of the STarT Back tool, its performance in allocating individuals to their appropriate risk categories cannot alone explain the variation in results of the trials to date. Rather, the learning thus far suggests that challenges in implementing stratified care in clinical practice and in changing professional practice largely explain the contrasting trial results. The review makes recommendations for future research, including greater focus on studying facilitators of implementation of stratified care and developing better treatments for patients with nonspecific low back pain at high risk of poor outcomes.

Validation of the Keele STarT MSK Tool for Patients With Musculoskeletal Pain in United States-based Outpatient Physical Therapy Settings

The STarT MSK tool was developed to enable risk stratification of patients with common musculoskeletal (MSK) pain conditions and help identify individuals who may require more targeted interventions or closer monitoring in primary care settings, however, its validity in U.S.-based outpatient physical therapy settings has not been investigated. The 10-item Keele STarT MSK risk stratification tool was tested for construct (convergent and discriminant) and predictive validity using a multicenter, prospective cohort study design. Participants (n = 141) receiving physical therapy for MSK pain of the back, neck, shoulder, hip, knee, or multisite regions completed intake questionnaires including the Keele STarT MSK tool, Functional Comorbidity Index (FCI), Optimal Screening for Prediction of Referral and Outcome Review-of-Systems and Optimal Screening for Prediction of Referral and Outcome Yellow Flag tools. Pain intensity, pain interference, and health-related quality of life (Medical Outcomes Study 8-item Short-Form Health Survey (SF-8) physical [PCS] and mental [MCS] component summary scores) were measured at 2- and 6-month follow-up. Participants were classified as STarT MSK tool low (44%), medium (39%), and high (17%) risk. Follow-up rates were 70.2% (2 months) and 49.6% (6 months). For convergent validity, fair relationships were observed between the STarT MSK tool and FCI and SF-8 MCS (r = .35-.37) while moderate-to-good relationships (r = .51-.72) were observed for 7 other clinical measures. For discriminant validity, STarT MSK tool risk-dependent relationships were observed for Optimal Screening for Prediction of Referral and Outcome Review-of-Systems, Optimal Screening for Prediction of Referral and Outcome Yellow Flag, pain interference, and SF-8 PCS (low < medium < high; P < .01) and FCI, pain intensity, and SF-8 MCS (low < medium-or-high; P < .01). For predictive validity, intake STarT MSK tool scores explained additional variability in pain intensity (11.2%, 20.0%), pain interference (7.5%, 14.1%), and SF-8 PCS (8.2%, 12.8%) scores at 2 and 6 months, respectively. This study contributes to the existing literature by providing additional evidence of STarT MSK tool cross-sectional construct validity and longitudinal predictive validity. PERSPECTIVE: This study presents STarT MSK risk stratification tool validity findings from a U.S. outpatient physical therapy sample. The STarT MSK tool has the potential to help physical therapists identify individuals presenting with the most common MSK pain conditions who may require more targeted interventions or closer monitoring.

Lumbar extension peak-torque, muscle endurance and motor imagery in junior-elite basketballers with and without a history of low back pain: a pilot study

Objectives

Low back pain (LBP) is common in elite athletes. Several peripheral and central factors have been identified to be altered in non-athletic LBP populations, however whether these alterations also exist in elite athletes with LBP is unknown. The aim of this study was to determine whether elite basketballers with a history of persistent LBP perform worse than those without LBP at a lumbar muscle endurance task, a lumbar extension peak-torque task, and a lumbar motor imagery task.

Method

An observational pilot study. Twenty junior elite-level male basketballers with (n = 11) and without (n = 9) a history of persistent LBP were recruited. Athletes completed a lumbar extensor muscle endurance (Biering-Sorensen) task, two lumbar extensor peak-torque (modified Biering-Sorensen) tasks and two motor imagery (left/right lumbar and hand judgement) tasks across two sessions (48 hours apart). Performance in these tasks were compared between the groups with and without a history of LBP.

Results

Young athletes with a history of LBP had reduced lumbar extensor muscle endurance (p < 0.001), reduced lumbar extension peak-torque (p < 0.001), and were less accurate at the left/right lumbar judgement task (p = 0.02) but no less accurate at a left/right hand judgement task (p = 0.59), than athletes without a history of LBP. Response times for both left/right judgement tasks did not differ between groups (lumbar p = 0.24; hand p = 0.58).

Conclusions

Junior elite male basketballers with a history of LBP demonstrate reduced lumbar extensor muscle endurance and lumbar extension peak-torque and are less accurate at a left/right lumbar rotation judgement task, than those without LBP.

Sex Differences in the Serum Proteomic Profile During Acute Low Back Pain-A Preliminary Study of the Relationship to Future Low Back Pain

The molecular processes driving the transition from acute to chronic low back pain (LBP) remain poorly understood and are likely to be sexually dimorphic. This study aimed to explore sex differences in the serum proteomic profile of people experiencing an acute LBP episode and determine if serum protein concentrations were associated with three-month outcome. Serum samples were collected through venepuncture from 30 female and 29 male participants experiencing an acute LBP episode. Serum samples underwent trypsin digestion and fractionation using hydrophobic interaction chromatography and were then analysed using mass-spectrometry. Mass-spectrometry spectra were searched in the Swissprot database for protein identification. Sex differences in protein abundance changes were evident upon inspection of fold changes. Multivariable data analysis identified 21 serum proteins during the acute episode that correctly classified 93% of males and 23 serum proteins that correctly classified 90% of females with ongoing LBP at 3 months. Pathway analysis suggested the differentially expressed proteins during acute LBP were frequently involved in immune, inflammatory, complement, or coagulation responses. This data provides preliminary evidence that biological processes during an acute LBP episode may contribute to the resolution, or persistence, of LBP symptoms at 3 months, however, these processes differ between males and females. PERSPECTIVE: Differential expression of serum proteins was observed between male and female participants during an acute LBP episode. This preliminary work provides a foundation for future research targeting distinct immune system processes in males and females that may interfere with the transition from acute to chronic LBP.

Strategies to optimise machine learning classification performance when using biomechanical features

Building prediction models using biomechanical features is challenging because such models may require large sample sizes. However, collecting biomechanical data on large sample sizes is logistically very challenging. This study aims to investigate if modern machine learning algorithms can help overcome the issue of limited sample sizes on developing prediction models. This was a secondary data analysis two biomechanical datasets - a walking dataset on 2295 participants, and a countermovement jump dataset on 31 participants. The input features were the three-dimensional ground reaction forces (GRFs) of the lower limbs. The outcome was the orthopaedic disease category (healthy, calcaneus, ankle, knee, hip) in the walking dataset, and healthy vs people with patellofemoral pain syndrome in the jump dataset. Different algorithms were compared: multinomial/LASSO regression, XGBoost, various deep learning time-series algorithms with augmented data, and with transfer learning. For the outcome of weighted multiclass area under the receiver operating curve (AUC) in the walking dataset, the three models with the best performance were InceptionTime with x12 augmented data (0.810), XGBoost (0.804), and multinomial logistic regression (0.800). For the jump dataset, the top three models with the highest AUC were the LASSO (1.00), InceptionTime with x8 augmentation (0.750), and transfer learning (0.653). Machine-learning based strategies for managing the challenging issue of limited sample size for biomechanical ML-based problems, could benefit the development of alternative prediction models in healthcare, especially when time-series data are involved.

Brain white matter pathways of resilience to chronic back pain: a multisite validation

Chronic back pain (CBP) is a global health concern with significant societal and economic burden. While various predictors of back pain chronicity have been proposed, including demographic and psychosocial factors, neuroimaging studies have shown that brain characteristics can serve as robust predictors of CBP. However, large-scale, multisite validation of these predictors is currently lacking. In two independent longitudinal studies, we examined white matter diffusion imaging data and pain characteristics in patients with subacute back pain (SBP) over six- and 12-month periods. Diffusion data from individuals with CBP and healthy controls (HC) were analyzed for comparison. Whole-brain tract-based spatial statistics analyses revealed that a cluster in the right superior longitudinal fasciculus (SLF) tract had larger fractional anisotropy (FA) values in patients who recovered (SBPr) compared to those with persistent pain (SBPp), and predicted changes in pain severity. The SLF FA values accurately classified patients at baseline and follow-up in a third publicly available dataset (Area under the Receiver Operating Curve ~ 0.70). Notably, patients who recovered had FA values larger than those of HC suggesting a potential role of SLF integrity in resilience to CBP. Structural connectivity-based models also classified SBPp and SBPr patients from the three data sets (validation accuracy 67%). Our results validate the right SLF as a robust predictor of CBP development, with potential for clinical translation. Cognitive and behavioral processes dependent on the right SLF, such as proprioception and visuospatial attention, should be analyzed in subacute stages as they could prove important for back pain chronicity.

Adding Brief Pain Science or Ergonomics Messages to Guideline Advice Did Not Increase Feelings of Reassurance in People With Acute Low Back Pain: A Randomized Experiment

OBJECTIVE: To investigate the effects of adding pain science or ergonomics messages to guideline advice on feelings of reassurance and management intentions among people with acute low back pain (LBP). DESIGN: Three-arm parallel-group randomized experiment. METHODS: We recruited people with acute LBP (pain for ≤6 weeks) to participate in an online experiment. Participants were randomized at a 1:1:1 ratio to one of three groups: guideline advice alone or guideline advice with the addition of brief pain science or ergonomics messages. The intervention was delivered via prerecorded videos in all 3 groups. Coprimary outcomes were reassurance that (1) no serious condition is causing LBP and (2) continuing with daily activities is safe. Secondary outcomes were perceived risk of developing chronic pain, management intentions (bed rest, see a health professional, see a specialist, and imaging), credibility, and relevance of the advice in addressing the participant's concerns. RESULTS: Two thousand two hundred ninety-seven responses (99.3% of 2,313 randomized) were analyzed. Adding brief pain science or ergonomics messages to guideline advice did not change reassurance that LBP was not caused by serious disease. The addition of ergonomics advice provided worse reassurance that it is safe to continue with daily activities compared to guideline advice (mean difference [MD], -0.33; 95% CI: 0.13, 0.53). There was no difference between groups on management intentions. CONCLUSION: Adding pain science or ergonomics messages to guideline advice did not increase reassurance or change management intentions in people with acute LBP. Ergonomics messages may lead to reduced feelings of reassurance. J Orthop Sports Phys Ther 2023;53(12)1-11. Epub 26 September 2023. doi:10.2519/jospt.2023.12090.

Development and External Validation of Individualized Prediction Models for Pain Intensity Outcomes in Patients With Neck Pain, Low Back Pain, or Both in Primary Care Settings

OBJECTIVE

The purpose of this study was to develop and externally validate multivariable prediction models for future pain intensity outcomes to inform targeted interventions for patients with neck or low back pain in primary care settings.

METHODS

Model development data were obtained from a group of 679 adults with neck or low back pain who consulted a participating United Kingdom general practice. Predictors included self-report items regarding pain severity and impact from the STarT MSK Tool. Pain intensity at 2 and 6 months was modeled separately for continuous and dichotomized outcomes using linear and logistic regression, respectively. External validation of all models was conducted in a separate group of 586 patients recruited from a similar population with patients' predictor information collected both at point of consultation and 2 to 4 weeks later using self-report questionnaires. Calibration and discrimination of the models were assessed separately using STarT MSK Tool data from both time points to assess differences in predictive performance.

RESULTS

Pain intensity and patients reporting their condition would last a long time contributed most to predictions of future pain intensity conditional on other variables. On external validation, models were reasonably well calibrated on average when using tool measurements taken 2 to 4 weeks after consultation (calibration slope = 0.848 [95% CI = 0.767 to 0.928] for 2-month pain intensity score), but performance was poor using point-of-consultation tool data (calibration slope for 2-month pain intensity score of 0.650 [95% CI = 0.549 to 0.750]).

CONCLUSION

Model predictive accuracy was good when predictors were measured 2 to 4 weeks after primary care consultation, but poor when measured at the point of consultation. Future research will explore whether additional, nonmodifiable predictors improve point-of-consultation predictive performance.

IMPACT

External validation demonstrated that these individualized prediction models were not sufficiently accurate to recommend their use in clinical practice. Further research is required to improve performance through inclusion of additional nonmodifiable risk factors.

Development and validation of a work-related risk score for upper-extremity musculoskeletal disorders in a French working population

OBJECTIVES

The aim was to develop an easy-to-use risk score based on occupational factors and to validate its performance to identify workers either having (diagnostic setting) or developing (prognostic setting) upper-extremity musculoskeletal disorders (UEMSD).

METHODS

This study relied on data from the Cosali prospective cohort conducted in a French working population. Diagnostic status for six UEMSD at inclusion and at follow-up was assessed by a standardized clinical examination. Data on occupational factors were collected through a self-administered questionnaire completed before the clinical examination at inclusion. The risk score was derived from a prediction model developed on data of 2,468 workers included in 2002-2003, and the validation sample is composed of 1,051 workers included later in 2004-2005. The prognostic performance of the risk score was assessed in workers without UEMSD at baseline.

RESULTS

A total of 13% and 12% of workers had a UEMSD at inclusion in the development and validation sample. The developed risk score includes physical, organizational and psychosocial factors at work. In the validation sample, this score had acceptable performance for identifying workers having or not UEMSD at baseline (AUC: 0.60 [95% CI 0.57 to 0.63]), in particular the negative predictive value was high (89%-90%). The baseline risk score showed similar performance for predicting incident UEMSD at follow-up examination.

CONCLUSION

This score can be useful as a first-line risk assessment tool, especially for excluding the low-risk work situations from further intervention by an ergonomist. Further validation studies are needed to determine its performance among various working populations.

Multidimensional risk factor analysis of acute low back pain progressing to chronicity: a longitudinal cohort study protocol

Introduction

Approximately 40% of patients with acute low back pain (LBP) develop chronic low back pain, which significantly increases the risk of poor prognosis. To reduce the risk of acute LBP becoming chronic, effective preventive strategies are needed. Early identification of risk factors for the development of chronic LBP can help clinicians choose appropriate treatment options and improve patient outcomes. However, previous screening tools have not considered medical imaging findings. The aim of this study is to identify factors that can predict the risk of acute LBP becoming chronic based on clinical information, pain and disability assessment, and MRI imaging findings. This protocol describes the methodology and plan for investigating multidimensional risk factors for acute LBP becoming chronic, in order to better understand the development of acute LBP and prevent chronic LBP.

Methods

This is a prospective multicenter study. We plan to recruit 1,000 adult patients with acute low back pain from four centers. In order to select four representative centers, we find the larger hospitals from different regions in Yunnan Province. The study will use a longitudinal cohort design. Patients will undergo baseline assessments upon admission and will be followed up for 5 years to collect the time of chronicity and associated risk factors. Upon admission, patients will be collected detailed demographic information, subjective and objective pain scores, disability scale, and lumbar spine MRI scanning. In addition, patient's medical history, lifestyle, psychological factors will be collected. Patients will be followed up at 3 months, 6 months, 1 year, 2 years and up for 5 years after admission to collect the time of chronicity and associated factors. Multivariate analysis will be used to explore the multidimensional risk factors affecting the chronicity of acute LBP patients (such as age, gender, BMI, degree of intervertebral disc degeneration, etc.), and survival analysis will be performed to explore the impact of each factor on the time of chronicity.

Ethics and dissemination

The study has been approved by the institutional research ethics committee of each study center (main center number: 2022-L-305). Results will be disseminated through scientific conferences and peer-reviewed publications, as well as meetings with stakeholders.

Six Externally Validated Prognostic Models Have Potential Clinical Value to Predict Patient Health Outcomes in the Rehabilitation of Musculoskeletal Conditions: A Systematic Review

OBJECTIVE

The purpose of this systematic review was to identify and appraise externally validated prognostic models to predict a patient's health outcomes relevant to physical rehabilitation of musculoskeletal (MSK) conditions.

METHODS

We systematically reviewed 8 databases and reported our findings according to Preferred Reporting Items for Systematic Reviews and Meta-Analysis 2020. An information specialist designed a search strategy to identify externally validated prognostic models for MSK conditions. Paired reviewers independently screened the title, abstract, and full text and conducted data extraction. We extracted characteristics of included studies (eg, country and study design), prognostic models (eg, performance measures and type of model) and predicted clinical outcomes (eg, pain and disability). We assessed the risk of bias and concerns of applicability using the prediction model risk of bias assessment tool. We proposed and used a 5-step method to determine which prognostic models were clinically valuable.

RESULTS

We found 4896 citations, read 300 full-text articles, and included 46 papers (37 distinct models). Prognostic models were externally validated for the spine, upper limb, lower limb conditions, and MSK trauma, injuries, and pain. All studies presented a high risk of bias. Half of the models showed low concerns for applicability. Reporting of calibration and discrimination performance measures was often lacking. We found 6 externally validated models with adequate measures, which could be deemed clinically valuable [ie, (1) STart Back Screening Tool, (2) Wallis Occupational Rehabilitation RisK model, (3) Da Silva model, (4) PICKUP model, (5) Schellingerhout rule, and (6) Keene model]. Despite having a high risk of bias, which is mostly explained by the very conservative properties of the PROBAST tool, the 6 models remain clinically relevant.

CONCLUSION

We found 6 externally validated prognostic models developed to predict patients' health outcomes that were clinically relevant to the physical rehabilitation of MSK conditions.

IMPACT

Our results provide clinicians with externally validated prognostic models to help them better predict patients' clinical outcomes and facilitate personalized treatment plans. Incorporating clinically valuable prognostic models could inherently improve the value of care provided by physical therapists.

Development and external validation of multivariable risk models to predict incident and resolved neuropathic pain: a DOLORisk Dundee study

Neuropathic pain is difficult to treat, and an understanding of the risk factors for its onset and resolution is warranted. This study aimed to develop and externally validate two clinical risk models to predict onset and resolution of chronic neuropathic pain. Participants of Generation Scotland: Scottish Family Health Study (GS; general Scottish population; n = 20,221) and Genetic of Diabetes Audit and Research in Tayside Scotland (GoDARTS; n = 5236) were sent a questionnaire on neuropathic pain and followed- -up 18 months later. Chronic neuropathic pain was defined using DN4 scores (≥ 3/7) and pain for 3 months or more. The models were developed in GS using logistic regression with backward elimination based on the Akaike information criterion. External validation was conducted in GoDARTS and assessed model discrimination (ROC and Precision-Recall curves), calibration and clinical utility (decision curve analysis [DCA]). Analysis revealed incidences of neuropathic pain onset (6.0% in GS [236/3903] and 10.7% in GoDARTS [61/571]) and resolution (42.6% in GS [230/540] and 23.7% in GoDARTS [56/236]). Psychosocial and lifestyle factors were included in both onset and resolved prediction models. In GoDARTS, these models showed adequate discrimination (ROC = 0.636 and 0.699), but there was evidence of miscalibration (Intercept = - 0.511 and - 0.424; slope = 0.623 and 0.999). The DCA indicated that the models would provide clinical benefit over a range of possible risk thresholds. To our knowledge, these are the first externally validated risk models for neuropathic pain. The findings are of interest to patients and clinicians in the community, who may take preventative or remedial measures.

Treatment effect modifiers for individuals with acute low back pain: secondary analysis of the TARGET trial

ABSTRACT

Treatment effect modifiers identify patient characteristics associated with treatment responses. The purpose of this secondary analysis was to identify potential treatment effect modifiers for disability from the TARGET trial that compared usual care (control) with usual care + psychologically informed physical therapy (PIPT). The sample consisted of a STarT Back tool identified high-risk patients with acute low back pain that completed Oswestry Disability Index (ODI) data at index visit and 6 months later (n = 1250). Candidate treatment effect modifiers were identified a priori and informed by the literature. Linear mixed models tested for treatment effect modification through tests of statistical interaction. All statistical interactions ( P ≤ 0.20) were stratified by modifier to inspect for specific effects ( P ≤ 0.05). Smoking was identified as a potential effect modifier (treatment * smoking interaction, P = 0.08). In participants who were smokers, the effect of PIPT was (ODI = 5.5; 95% CI: 0.6-10.4; P = 0.03) compared with usual care. In participants who were nonsmokers, the effect of PIPT was (ODI = 1.5; 95% CI: -1.4 to 4.4; P = 0.31) compared with usual care. Pain medication was also identified as a potential effect modifier (treatment × pain medication interaction, P = 0.10). In participants prescribed ≥3 pain medications, the effect of PIPT was (ODI = 7.1; 95% CI: -0.1 to 14.2; P = 0.05) compared with usual care. The PIPT effect for participants prescribed no pain medication was (ODI = 3.5; 95% CI: -0.4 to 7.4; P = 0.08) and for participants prescribed 1 to 2 pain medications was (ODI = 0.6; 95% CI: -2.5 to 3.7; P = 0.70) when compared with usual care. These findings may be used for generating hypotheses and planning future clinical trials investigating the effectiveness of tailored application of PIPT.

Person-centred education and advice for people with low back pain: Making the best of what we know

BACKGROUND

The first-line treatment consistently recommended for people with low back pain is patient education and advice. Regardless of the duration of low back pain, clinicians should provide education on the benign nature of low back pain, reassurance about the absence of a serious medical condition, and advice to remain active. There is little guidance on how best to provide this care.

OBJECTIVE

This Masterclass will draw on recent evidence to explore how physical therapy clinicians could deliver person-centred education and advice to people with low back pain to refine their clinical consultation.

DISCUSSION

First, we highlight the potential value of providing validation to acknowledge the distressing experience and consequences of low back pain. Second, we describe a tool to open channels of communication to provide education and advice in a patient-centred and efficient way. Clinicians could consider using the Attitude toward Education and advice for Low back pain Questionnaire to gain an insight into patient attitudes toward education and advice at the outset of a clinical encounter. Finally, we provide options for tailoring patient education and advice to promote self-management of low back pain based on patient attitudes. We present evidence that a positive attitude toward messages about causes rather than messages about physical activity predicts intention to self-manage low back pain. We combine this evidence to suggest a pathway for clinicians to provide education and advice to people with low back pain within the time constraints of a clinical consultation.

Cortical function and sensorimotor plasticity are prognostic factors associated with future low back pain after an acute episode: the Understanding persistent Pain Where it ResiDes prospective cohort study

ABSTRACT

Predicting the development of chronic low back pain (LBP) at the time of an acute episode remains challenging. The Understanding persistent Pain Where it ResiDes study aimed to identify neurobiological and psychological risk factors for chronic LBP. Individuals with acute LBP (N = 120) participated in a prospective cohort study with 6-month follow-up. Candidate predictors were selected from the neurobiological (eg, sensorimotor cortical excitability assessed by sensory and motor-evoked potentials and brain-derived neurotrophic factor genotype), psychological (eg, depression and anxiety), symptom-related (eg, LBP history), and demographic domains. Analyses involved multivariable linear regression models with pain intensity or disability degree as continuous variables. Secondary analyses involved a multivariable logistic model with the presence of LBP at 6 months (thresholding pain intensity and disability degree) as a dichotomous variable. Lower sensory cortex and corticomotor excitability, higher baseline pain intensity, higher depression, stress, and pain catastrophizing were the strongest predictors ( R2 = 0.47) of pain intensity at 6 months. Older age and higher pain catastrophizing were the strongest predictors ( R2 = 0.30) of disability at 6 months. When the LBP outcome was dichotomised, sensory cortex and corticomotor excitability, brain-derived neurotrophic factor genotype, depression and anxiety, LBP history and baseline pain intensity, discriminated between those who did and did not report LBP at 6 months (C-statistic 0.91). This study identifies novel risk factors for the development of future LBP. Neurobiological risk factors, when added to a multivariable linear regression model, explained a further 15% of the variance in the 6-month pain intensity.

Prevalence of chronic non-specific low back pain among caregivers of stroke survivors in Kano, Nigeria and factors associated with it: A cross-sectional study

Purpose

Low back pain (LBP) may have a specific or non-specific cause such as abnormal posture or repetitive tasks. For instance, lifting and transferring patients during caregiving for stroke survivors may predispose the caregivers to LBP.

Objectives

The aim of this study is to determine the prevalence of chronic non-specific LBP and factors associated with it in caregivers of stroke survivors.

Method

The research design used is cross-sectional study design. Participants of the study were caregivers of stroke survivors in Kano, Nigeria who were at least 18 years old. They were included if they had at least one-month experience with caregiving for at least 1 h per day. Presence of LBP and level of disability were assessed using participants' self-report and Rolland Morris Low Back Pain Disability Questionnaire respectively. The data collected was analyzed using descriptive, Chi-square statistics and Binary Logistics Regression.

Result

Three hundred caregivers with mean age, 33.24 ± 10.32 years in which 207 and 93 were males and females respectively, participated in the study. The results showed that, there was a high prevalence (64.7%) of LBP among the caregivers. The prevalence was significantly associated with gender (p < 0.001), age (p = 0.029), occupation (p < 0.001) and duration of caregiving (p < 0.001) of the study participants. In addition, the result of the regression model showed that, being a female (p = 0.001), a civil servant (p = 0.031), a trader (p = 0.013), and a complete caregiver (0.001); and caregiving for a duration of 5 h or more per day (p = 0.024) are significant predictors of having LBP. Similarly, level of disability due to the presence of LBP among the study participants was significantly associated with gender (p < 0.001), occupation (p < 0.001), duration of caregiving (p = 0.025), and the nature of the caregiving (p < 0.001).

Conclusion

Informal caregiving for stroke survivors may result in developing chronic non-specific LBP, especially among females, Civil servants, traders, complete caregivers and those with long duration of caregiving. This can add an additional burden on the family in terms of cost of care, result in reduced quality of caregiving and cause psychological stress. Thus, it is important the health of the caregivers of stroke survivors is considered during stroke rehabilitation.

Four Variables Were Sufficient for Low Back Pain: Determining Which Patient-Reported Tools Pain and Disability Improvements

OBJECTIVE: To predict 30- and 180-day improvements in disability and pain for patients seeking physical therapy care for low back pain (LBP). DESIGN: Longitudinal cohort. METHODS: Baseline assessment was completed by 259 patients with chief complaint of LBP, and the assessment includes psychosocial measures (Keele STarT Back Screening [SBST] and the Optimal Screening for Prediction of Referral and Outcome Yellow Flag [OSPRO-YF] tools), the Optimal Screening for Prediction of Referral and Outcome Review of Symptoms (OSPRO-ROS) and the Review of Symptoms Plus (OSPRO-ROS+) tools, the Charlson Comorbidity Index (CCI), the Area Deprivation Index (ADI), and the National Institute of Health Chronic Pain Criteria (NIH-CP). Using the Modified Low Back Disability Questionnaire (MDQ) and the Numeric Pain Rating Scale (NPRS) as primary outcomes, statistical analysis determined multiple sets of predictor variables with similar model performance. RESULTS: The parsimonious "best model" for prediction of the 180-day MDQ change included 3 predictors (Admit MDQ, NIH-CP, and OSPRO ROS+) because it had the lowest penalized goodness-of-fit statistic (BIC = -35.21) and the highest explained variance (R2 = 0.295). The parsimonious "best model" for 180-day NPRS change included 2 variables (Admit NPRS and OSPRO-ROS+) with the lowest penalized goodness-of-fit statistic (BIC = -18.2) and the highest explained variance (R2 = 0.190). CONCLUSION: There were many model options with similar statistical performance when using established measures to predict MDQ and NPRS outcomes. A potential variable set for a standard predictive model that balances statistical performance with pragmatic considerations included the OSPRO-ROS+, OSPRO-YF, NIH-CP definition, and admit MDQ and NPRS scores. J Orthop Sports Phys Ther 2022;52(10):685-693. Epub: 12 August 2022. doi:10.2519/jospt.2022.11018.

Development and internal validation of a machine learning prediction model for low back pain non-recovery in patients with an acute episode consulting a physiotherapist in primary care

Background

While low back pain occurs in nearly everybody and is the leading cause of disability worldwide, we lack instruments to accurately predict persistence of acute low back pain. We aimed to develop and internally validate a machine learning model predicting non-recovery in acute low back pain and to compare this with current practice and ‘traditional’ prediction modeling.

Methods

Prognostic cohort-study in primary care physiotherapy. Patients (n = 247) with acute low back pain (≤ one month) consulting physiotherapists were included. Candidate predictors were assessed by questionnaire at baseline and (to capture early recovery) after one and two weeks. Primary outcome was non-recovery after three months, defined as at least mild pain (Numeric Rating Scale > 2/10). Machine learning models to predict non-recovery were developed and internally validated, and compared with two current practices in physiotherapy (STarT Back tool and physiotherapists’ expectation) and ‘traditional’ logistic regression analysis.

Results

Forty-seven percent of the participants did not recover at three months. The best performing machine learning model showed acceptable predictive performance (area under the curve: 0.66). Although this was no better than a’traditional’ logistic regression model, it outperformed current practice.

Conclusions

We developed two prognostic models containing partially different predictors, with acceptable performance for predicting (non-)recovery in patients with acute LBP, which was better than current practice. Our prognostic models have the potential of integration in a clinical decision support system to facilitate data-driven, personalized treatment of acute low back pain, but needs external validation first.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-022-05718-7.

What messages predict intention to self-manage low back pain? A study of attitudes towards patient education

ABSTRACT

This observational study evaluated people's attitudes towards educational statements and tested whether this predicted intention to self-manage low back pain (LBP). People with or without LBP who were older than 18 years and fluent in written English were recruited. Participants completed an online survey asking demographic questions and questions on the presence or absence of LBP, its duration, and intensity. We assessed attitude toward educational statements and conducted linear regression analyses to investigate the relationship between attitude toward each statement and intention to self-manage. We recruited 656 participants, n = 345 (53.6%), with LBP of varying duration. On average, participants had a positive attitude toward all statements except one; participants with chronic LBP had a negative attitude toward a statement relating to the cause of LBP. The effect of attitude on intention to self-manage was dependent on whether someone had LBP and for how long. For example, increased intention to self-manage was predicted by a positive attitude toward educational statements related to staying active (β = 0.22 [CI 0.11-0.33]) in participants without pain, statements about reassurance (β = 0.33 [CI 0.16-0.49]) for participants with acute or subacute LBP, and statements about the severity of back pain (β = 0.25 [CI 0.18-0.33]) for participants with chronic LBP. We noted differences in attitude toward educational messages and individuals' intention to self-manage LBP depending on pain duration. Self-management could be encouraged with specific reassurance in people with acute or subacute LBP and education about severity in people with chronic LBP.

The association between person and fracture characteristics with patient reported outcome after ankle fractures in adults: A systematic review

BACKGROUND

The incidence of ankle fractures is increasing and the clinical outcome is highly variable.

QUESTION

What person and fracture characteristics are associated with patient reported outcomes after surgically or conservatively managed ankle fractures in adults?

DATA SOURCES

Medline, EMBASE, and Allied and Complimentary Health Medical Database (AMED) databases were searched from the earliest available date until 16th July 2020.

STUDY SELECTION

Prognostic factors studies recruiting adults of age 18 years or older with a radiologically confirmed ankle fracture, and evaluating function, symptoms and quality of life by patient reported outcome measures, were included.

STUDY APPRAISAL/SYNTHESIS METHODS

Risk of bias of individual studies was assessed by the Quality in Prognostic Factors Studies tool. Correlation coefficients were calculated and data were analysed using narrative synthesis.

RESULTS

Fifty-one phase 1 explanatory studies with 6177 participants met the inclusion criteria. Thirty-one studies were rated as high risk of bias using the Quality in Prognostic Factors Studies tool. There was low quality evidence that age, body mass index, American Society of Anesthesiologists classification and pre-injury mobility were associated with function, and low to moderate quality evidence that age, smoking and American Society of Anesthesiologists classification were associated with quality of life. No person characteristics were associated with symptoms and no fracture characteristics were associated with any outcomes.

CONCLUSION

There was low to moderate quality evidence that person characteristics may be associated with patient reported function and quality of life following ankle fracture.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO registration number CRD42020184830.

Stress and Pain. Predictive (Neuro)Pattern Identification for Chronic Back Pain: A Longitudinal Observational Study

Introduction

Low back pain (LBP) leads to considerable impairment of quality of life worldwide and is often accompanied by psychosomatic symptoms.

Objectives

First, to assess the association between stress and chronic low back pain (CLBP) and its simultaneous appearance with fatigue and depression as a symptom triad. Second, to identify the most predictive stress-related pattern set for CLBP for a 1-year diagnosis.

Methods

In a 1-year observational study with four measurement points, a total of 140 volunteers (aged 18–45 years with intermittent pain) were recruited. The primary outcomes were pain [characteristic pain intensity (CPI), subjective pain disability (DISS)], fatigue, and depressive mood. Stress was assessed as chronic stress, perceived stress, effort reward imbalance, life events, and physiological markers [allostatic load index (ALI), hair cortisol concentration (HCC)]. Multiple linear regression models and selection procedures for model shrinkage and variable selection (least absolute shrinkage and selection operator) were applied. Prediction accuracy was calculated by root mean squared error (RMSE) and receiver-operating characteristic curves.

Results

There were 110 participants completed the baseline assessments (28.2 ± 7.5 years, 38.1% female), including HCC, and a further of 46 participants agreed to ALI laboratory measurements. Different stress types were associated with LBP, CLBP, fatigue, and depressive mood and its joint occurrence as a symptom triad at baseline; mainly social-related stress types were of relevance. Work-related stress, such as “excessive demands at work”[b = 0.51 (95%CI -0.23, 1.25), p = 0.18] played a role for upcoming chronic pain disability. “Social overload” [b = 0.45 (95%CI -0.06, 0.96), p = 0.080] and “over-commitment at work” [b = 0.28 (95%CI -0.39, 0.95), p = 0.42] were associated with an upcoming depressive mood within 1-year. Finally, seven psychometric (CPI: RMSE = 12.63; DISS: RMSE = 9.81) and five biomarkers (CPI: RMSE = 12.21; DISS: RMSE = 8.94) could be derived as the most predictive pattern set for a 1-year prediction of CLBP. The biomarker set showed an apparent area under the curve of 0.88 for CPI and 0.99 for DISS.

Conclusion

Stress disrupts allostasis and favors the development of chronic pain, fatigue, and depression and the emergence of a “hypocortisolemic symptom triad,” whereby the social-related stressors play a significant role. For translational medicine, a predictive pattern set could be derived which enables to diagnose the individuals at higher risk for the upcoming pain disorders and can be used in practice.

No prognostic model for people with recent-onset low back pain has yet been demonstrated to be suitable for use in clinical practice: a systematic review

OBJECTIVE

What model development and external validation studies exist that focus on the prognosis of patients with recent-onset low back pain (LBP)? What is the performance (in terms of discrimination and calibration) of these clinical prediction models?

METHODS

Systematic searches on MEDLINE, Embase and CINAHL were conducted. Model development and/or external validation studies of patients with recent-onset LBP were selected. Models predicting outcomes of pain, disability, sick leave, work absence and self-reported recovery, with at least 12 weeks of follow-up, were included. Risk of bias was assessed using the PROBAST instrument.

RESULTS

We identified 17 prognostic models developed to predict outcomes in people with recent-onset LBP: six models were in the development phase and 11 were in the validation phase. The most assessed prediction model was the Original Örebro Musculoskeletal Pain Questionnaire. The Da Silva Clinical Prediction Model was the only model, from a study with low risk of bias, that presented acceptable discrimination, demonstrating 'good' performance in predicting recovery from pain (C-statistic 0.71, 95% CI 0.63 to 0.78) and overall acceptable agreement in calibration.

CONCLUSION

Most prediction models for prognosis of patients with recent-onset LBP did not perform well at discrimination, few studies reported calibration and their performance varied across studies. It seems premature to advocate use of the available models, at their current state of development and validation, for low back pain in primary care, considering their generally poor methods and performance.

REGISTRATION

CRD42020160988.

Immediate effects of spinal manipulation on painful sensitivity and postural stability in patients with chronic nonspecific low back pain: study protocol for a controlled randomised clinical trial

BACKGROUND

Low back pain is one of the main public health concerns. Chronic low back pain (cLBP) reduces functional capacity and affects postural stability. Although health professionals widely use spinal manipulation, its immediate effect on painful sensitivity and postural stability is lacking. This study aims to verify the immediate effects of lumbar spinal manipulation on the pressure pain threshold and postural stability in individuals with cLBP.

METHODS

A two-arm, placebo-controlled clinical trial with parallel groups and examiner-blinded will be conducted with 80 participants with cLBP from an outpatient physical therapy department, randomly allocated at a 1:1 distribution. The experimental group will receive a lumbar spinal manipulation technique, and the placebo group will receive a simulated lumbar spinal manipulation. Both groups will receive one session of treatment and will be evaluated before and immediately after the intervention. The primary outcomes will be the pressure pain threshold and postural stability. Pain intensity and patient's expectation will be assessed as a secondary outcome. The pressure pain threshold will be assessed using a pressure algometer in 6 different anatomical regions. The evaluation of postural stability will be performed in a baropodometry exam by displacing the centre of pressure. The pain intensity will be measured using the Numeric Pain Rating Scale. A Likert scale will be used for the patient's expectation about the treatment. A two-way analysis of variance will compare the effect of the interventions between groups.

DISCUSSION

This study will provide insights regarding the immediate effects of spinal manipulation in patients with cLBP against a simulated spinal manipulation using objective outcomes and considering patients' expectations regarding the treatment.

TRIAL REGISTRATION

Brazilian Registry of Clinical Trials RBR-3ksq2c . Registered on 13 July 2020.

Machine Learning Approaches to Predict Chronic Lower Back Pain in People Aged over 50 Years

Background and Objectives: Chronic lower back pain (LBP) is a common clinical disorder. The early identification of patients who will develop chronic LBP would help develop preventive measures and treatment. We aimed to develop machine learning models that can accurately predict the risk of chronic LBP. Materials and Methods: Data from the Sixth Korea National Health and Nutrition Examination Survey conducted in 2014 and 2015 (KNHANES VI-2, 3) were screened for selecting patients with chronic LBP. LBP lasting >30 days in the past 3 months was defined as chronic LBP in the survey. The following classification models with machine learning algorithms were developed and validated to predict chronic LBP: logistic regression (LR), k-nearest neighbors (KNN), naïve Bayes (NB), decision tree (DT), random forest (RF), gradient boosting machine (GBM), support vector machine (SVM), and artificial neural network (ANN). The performance of these models was compared with respect to the area under the receiver operating characteristic curve (AUROC). Results: A total of 6119 patients were analyzed in this study, of which 1394 had LBP. The feature selected data consisted of 13 variables. The LR, KNN, NB, DT, RF, GBM, SVM, and ANN models showed performances (in terms of AUROCs) of 0.656, 0.656, 0.712, 0.671, 0.699, 0.660, 0.707, and 0.716, respectively, with ten-fold cross-validation. Conclusions: In this study, the ANN model was identified as the best machine learning classification model for predicting the occurrence of chronic LBP. Therefore, machine learning could be effectively applied in the identification of populations at high risk of chronic LBP.

Changes in Pain Catastrophizing and Fear-Avoidance Beliefs as Mediators of Early Physical Therapy on Disability and Pain in Acute Low-Back Pain: A Secondary Analysis of a Clinical Trial

OBJECTIVE

The Fear-Avoidance Model of chronic pain (FAM) posits that pain catastrophizing and fear-avoidance beliefs are prognostic for disability and chronicity. In acute low-back pain, early physical therapy (PT) is effective in reducing disability in some patients. How early PT impacts short- and long-term changes in disability for patients with acute pain is unknown. Based on the FAM, we hypothesized that early reductions in pain catastrophizing and fear-avoidance beliefs would mediate early PT's effect on changes in disability (primary outcome) and pain intensity (secondary outcome) over 3 months and 1 year.

SUBJECTS

Participants were 204 patients with low-back pain of < 16 days duration, who enrolled in a clinical trial (NCT01726803) comparing early PT sessions or usual care provided over 4 weeks.

METHODS

Patients completed the Pain Catastrophizing Scale (PCS), Fear-Avoidance Beliefs Questionnaire (FABQ work and physical activity scales) and outcomes (Oswestry Disability Index and Numeric Pain Rating Scale) at baseline, 4 weeks, 3 months, and 1 year. We applied longitudinal mediation analysis with single and multiple mediators.

RESULTS

Early PT led to improvements in disability and pain over 3 months, but not 1 year. In the single mediator model, four-week reductions in pain catastrophizing mediated early PT's effects on 3-month disability and pain intensity improvements, explaining 16% and 22% of the association, respectively, but the effects were small. Pain catastrophizing and fear-avoidance beliefs did not jointly mediate these associations.

CONCLUSIONS

In acute low-back pain, early PT may improve disability and pain outcomes at least partly through reducing patients' catastrophizing.

Producing Clinically Meaningful Reductions in Disability: A Causal Mediation Analysis of a Patient Education Intervention

Patient education is recommended as first-line care for low back pain (LBP), although its efficacy for providing clinically meaningful reductions in disability has been questioned. One way to improve treatment effects is to identify and improve targeting of treatment mechanisms. We conducted a pre-planned causal mediation analysis of a randomized, placebo-controlled trial investigating the effectiveness of patient education for patients with acute LBP. 202 patients who had fewer than six-weeks' duration of LBP and were at high-risk of developing chronic LBP completed two, one-hour treatment sessions of either intensive patient education, or placebo patient education. 189 participants provided data for the outcome self-reported disability at three-months and the mediators, pain self-efficacy, pain catastrophizing, and back beliefs at one-week post treatment. This causal mediation analysis found that pain catastrophizing (mediated effect, -0.64; 95% Confidence Interval [CI], -1.31 to -0.15) and back beliefs (mediated effect, -0.51; 95% CI, -1.15 to -0.02) partly explained the effect of patient education on disability but pain self-efficacy did not (mediated effect, -0.40; 95% CI -1.13 to 0.28). Considering the mediator-outcome relationship, patient education would need to induce an 8 point difference on the pain self-efficacy questionnaire (0-60); an 11 point difference on the back beliefs questionnaire (9-45); and a 21 point difference on the pain catastrophizing scale (0-52) to achieve a minimally clinically important difference of 2 points on the Roland Morris Disability Questionnaire (0-24). PERSPECTIVE: Understanding the mechanisms of patient education can inform how this treatment can be adapted to provide clinically meaningful reductions in disability. Our findings suggest that adapting patient education to better target back beliefs and pain self-efficacy could result in clinically meaningful reductions in disability whereas the role of pain catastrophizing in acute LBP is less clear.

Feeling reassured after a consultation does not reduce disability or healthcare use in people with acute low back pain: a mediation analysis of a randomised trial

QUESTION

Does feeling reassured after a consultation reduce future disability or healthcare use in people with acute low back pain (LBP)?

DESIGN

Mediation analysis of a randomised, sham-controlled trial.

PARTICIPANTS

Two hundred and two people with acute LBP at above average risk (high risk) of developing chronic LBP.

INTERVENTION

All participants received guideline-based care from their usual clinician. Participants received two additional 1-hour sessions of patient education focused on emphasising the benign nature of LBP or sham patient education that included active listening only.

OUTCOME MEASURES

The two primary outcomes for this study were self-reported disability and healthcare use. The mediator was feeling reassured that LBP was not caused by serious illness.

RESULTS

Data from 194 (96%) participants and 178 (88%) participants were included in the analysis for disability and healthcare use outcome models, respectively. Feeling reassured did not mediate the effect of the intervention on disability (indirect effect -0.23, 95% CI -0.71 to 0.18) or healthcare use (indirect effect 0.00, 95% CI -0.04 to 0.04). Patient education intervention increased feeling reassured (1.14 points, 95% CI 0.43 to 1.85) compared with sham patient education. However, the mediator (ie, feeling reassured) did not reduce disability (-0.20 points, 95% CI -0.58 to 0.19) or healthcare use (OR 1.09, 95% CI 0.98 to 1.21).

CONCLUSION

Feeling reassured after a consultation did not lead to improvements in disability and healthcare use for people with acute LBP. Clinicians should reflect on the time that they allocate to reassuring their patients and consider reallocating time to other aspects of the consultation that could reduce disability and future healthcare use.

TRIAL REGISTRATION

ACTRN12612001180808, study protocol https://osf.io/4tfaz/.

Effect of a Consumer-Focused Website for Low Back Pain on Health Literacy, Treatment Choices, and Clinical Outcomes: Randomized Controlled Trial

Background

The internet is used for information related to health conditions, including low back pain (LBP), but most LBP websites provide inaccurate information. Few studies have investigated the effectiveness of internet resources in changing health literacy or treatment choices.

Objective

This study aims to evaluate the effectiveness of the MyBackPain website compared with unguided internet use on health literacy, choice of treatments, and clinical outcomes in people with LBP.

Methods

This was a pragmatic, web-based, participant- and assessor-blinded randomized trial of individuals with LBP stratified by duration. Participants were randomly allocated to have access to the evidence-based MyBackPain website, which was designed with input from consumers and expert consensus or unguided internet use. The coprimary outcomes were two dimensions of the Health Literacy Questionnaire (dimension 2: “having sufficient information to manage my health;” dimension 3: “actively managing my health;” converted to scores 1-100) at 3 months. Secondary outcomes included additional Health Literacy Questionnaire dimensions, quality of treatment choices, and clinical outcomes.

Results

A total of 453 participants were recruited, and 321 (70.9%) completed the primary outcomes. Access to MyBackPain was not superior to unguided internet use on primary outcomes (dimension 2: mean difference −0.87 units, 95% CI −3.56 to 1.82; dimension 3: mean difference −0.41 units, 95% CI −2.78 to 1.96). Between-group differences in other secondary outcomes had inconsistent directions and were unlikely to be clinically important, although a small improvement of unclear importance in the quality of stated treatment choices at 1 month was found (mean difference 0.93 units, 95% CI 0.03 to 1.84).

Conclusions

MyBackPain was not superior to unguided internet use for health literacy, but data suggest some short-term improvement in treatment choices. Future research should investigate if greater interactivity and engagement with the website may enhance its impact.

Trial Registration

Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12617001292369; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=372926

International Registered Report Identifier (IRRID)

RR2-10.1136/bmjopen-2018-027516

Developing clinical prediction models for nonrecovery in older patients seeking care for back pain: the back complaints in the elders prospective cohort study

ABSTRACT

Back pain is a leading cause of disability worldwide and is common in older adults. No clinical prediction models for poor long-term outcomes have been developed in older patients with back pain. This study aimed to develop and internally validate 3 clinical prediction models for nonrecovery in this population. A prospective cohort study in general practice was conducted (Back Complaints in the Elders, Netherlands), including 675 patients >55 years with a new episode of care for back pain. Three definitions of nonrecovery were used combining 6-month and 12-month follow-up data: (1) persistent back pain, (2) persistent disability, and (3) perceived nonrecovery. Sample size calculation resulted in a maximum of 14 candidate predictors that were selected from back pain prognostic literature and clinical experience. Multivariable logistic regression was used to develop the models (backward selection procedure). Models' performance was evaluated with explained variance (Nagelkerke's R2), calibration (Hosmer-Lemeshow test), and discrimination (area under the curve [AUC]) measures. The models were internally validated in 250 bootstrapped samples to correct for overoptimism. All 3 models displayed good overall performance during development and internal validation (ie, R2 > 30%; AUC > 0.77). The model predicting persistent disability performed best, showing good calibration, discrimination (AUC 0.86, 95% confidence interval 0.83-0.89; optimism-adjusted AUC 0.85), and explained variance (R2 49%, optimism-adjusted R2 46%). Common predictors in all models were: age, chronic duration, disability, a recent back pain episode, and patients' recovery expectations. Spinal morning stiffness and pain during spinal rotation were included in 2 of 3 models. These models should be externally validated before being used in a clinical primary care setting.

Derivation of a Risk Assessment Tool for Prediction of Long-Term Pain Intensity Reduction After Physical Therapy

Rationale

Risk assessment tools can improve clinical decision-making for individuals with musculoskeletal pain, but do not currently exist for predicting reduction of pain intensity as an outcome from physical therapy.

Aims and Objective

The objective of this study was to develop a tool that predicts failure to achieve a 50% pain intensity reduction by 1) determining the appropriate statistical model to inform the tool and 2) select the model that considers the tradeoff between clinical feasibility and statistical accuracy.

Methods

This was a retrospective, secondary data analysis of the Optimal Screening for Prediction of Referral and Outcome (OSPRO) cohort. Two hundred and seventy-nine individuals seeking physical therapy for neck, shoulder, back, or knee pain who completed 12-month follow-up were included. Two modeling approaches were taken: a longitudinal model included demographics, presence of previous episodes of pain, and regions of pain in addition to baseline and change in OSPRO Yellow Flag scores to 12 months; two comparison models included the same predictors but assessed only baseline and early change (4 weeks) scores. The primary outcome was failure to achieve a 50% reduction in pain intensity score at 12 months. We compared the area under the curve (AUC) to assess the performance of each candidate model and to determine which to inform the Personalized Pain Prediction (P3) risk assessment tool.

Results

The baseline only and early change models demonstrated lower accuracy (AUC=0.68 and 0.71, respectively) than the longitudinal model (0.79) but were within an acceptable predictive range. Therefore, both baseline and early change models were used to inform the P3 risk assessment tool.

Conclusion

The P3 tool provides physical therapists with a data-driven approach to identify patients who may be at risk for not achieving improvements in pain intensity following physical therapy.

Lack of Consensus Across Clinical Guidelines Regarding the Role of Psychosocial Factors Within Low Back Pain Care: A Systematic Review

It is widely accepted that psychosocial prognostic factors should be addressed by clinicians in their assessment and management of patient suffering from low back pain (LBP). On the other hand, an overview is missing how these factors are addressed in clinical LBP guidelines. Therefore, our objective was to summarize and compare recommendations regarding the assessment and management of psychosocial prognostic factors for LBP chronicity, as reported in clinical LBP guidelines. We performed a systematic search of clinical LBP guidelines (PROSPERO registration number 154730). This search consisted of a combination of previously published systematic review articles and a new systematic search in medical or guideline-related databases. From the included guidelines, we extracted recommendations regarding the assessment and management of LBP which addressed psychosocial prognostic factors (ie, psychological factors ["yellow flags"], perceptions about the relationship between work and health, ["blue flags"], system or contextual obstacles ["black flags") and psychiatric symptoms ["orange flags"]). In addition, we evaluated the level or quality of evidence of these recommendations. In total, we included 15 guidelines. Psychosocial prognostic factors were addressed in 13 of 15 guidelines regarding their assessment and in 14 of 15 guidelines regarding their management. Recommendations addressing psychosocial factors almost exclusively concerned "yellow" or "black flags," and varied widely across guidelines. The supporting evidence was generally of very low quality. We conclude that in general, clinical LBP guidelines do not provide clinicians with clear instructions about how to incorporate psychosocial factors in LBP care and should be optimized in this respect. More specifically, clinical guidelines vary widely in whether and how they address psychosocial factors, and recommendations regarding these factors generally require better evidence support. This emphasizes a need for a stronger evidence-base underlying the role of psychosocial risk factors within LBP care, and a need for uniformity in methodology and terminology across guidelines. PERSPECTIVE: This systematic review summarized clinical guidelines on low back pain (LBP) on how they addressed the identification and management of psychosocial factors. This review revealed a large amount of variety across guidelines in whether and how psychosocial factors were addressed. Moreover, recommendations generally lacked details and were based on low quality evidence.

Exploring the origin of pain subclassification, with emphasis on low back pain: a scoping review

OBJECTIVE

This scoping review aimed to explore the different working definitions for the duration of acute, subacute, and chronic pain, with emphasis on low back pain, and to establish where these definitions originated and the rationale provided for the time frames used.

INTRODUCTION

From a global perspective, low back pain is a major social and economic problem. One of the most commonly used methods to stratify and manage low back pain is the traditional duration-based classification (acute, subacute, and chronic). Where these time points lie to differentiate these transitions continues to be debated within the scientific community, which may engender a degree of heterogeneity in study findings. Therefore, applying these findings to clinical practice may be somewhat challenging. This review encapsulates the historical origins of the different duration categories to provide an understanding of how these variations were derived.

INCLUSION CRITERIA

Studies that included participants with low back pain were the focus of this review. Sources that included children or other specific pain pathologies, such as cancer pain, were excluded. The main concept of interest was that the publication proposed an original definition of the duration of acute, subacute, or chronic low back pain. All study designs were included provided they gave a rationale for the duration that they used.

METHODS

The following databases were searched: MEDLINE, Embase, CINAHL, and PsycINFO, from the inception of each database until September 18, 2019. This review was limited to studies published in English. Two independent reviewers screened the retrieved articles against the eligibility criteria. Additional studies were searched from the reference lists of studies to find the original source. Some original sources overlapped with general pain duration literature. This led to a deviation from the scoping review protocol, which originally intended to focus on definitions of low back pain duration only. Data extraction was undertaken using a charting table developed specifically for the review objectives. The findings were presented using narrative synthesis.

RESULTS

Nineteen records were included in this review, and comprised three book chapters, four review articles, four articles that arose following pain expert group discussions, seven primary research studies, and a spinal guideline. Data were extracted from the included studies and categorized into four themes based on the origin of the classification of the duration. The themes included i) work/employment setting, ii) empirical studies, iii) expert reasoning, and iv) pathophysiological explanation.

CONCLUSIONS

This scoping review compiled the existing literature on the working definitions of the duration of acute, subacute, and chronic low back pain and found a wide variation. These ranged from seven days, 14 days, and seven weeks for the acute and subacute transition points, and seven weeks to three years for chronic low back pain. The duration definitions specifically referring to the general pain literature focused on three and/or six months for the transition to chronic. Better integration of reasoning between the identified themes could facilitate the establishment of more ideal duration definitions in the future. Although inconclusive, the definition most commonly cited, with most consensus, was three months for the transition to chronic low back pain.

Cohort profile: DOLORisk Dundee: a longitudinal study of chronic neuropathic pain

PURPOSE

Neuropathic pain is a common disorder of the somatosensory system that affects 7%-10% of the general population. The disorder places a large social and economic burden on patients as well as healthcare services. However, not everyone with a relevant underlying aetiology develops corresponding pain. DOLORisk Dundee, a European Union-funded cohort, part of the multicentre DOLORisk consortium, was set up to increase current understanding of this variation in onset. In particular, the cohort will allow exploration of psychosocial, clinical and genetic predictors of neuropathic pain onset.

PARTICIPANTS

DOLORisk Dundee has been constructed by rephenotyping two pre-existing Scottish population cohorts for neuropathic pain using a standardised 'core' study protocol: Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) (n=5236) consisting of predominantly type 2 diabetics from the Tayside region, and Generation Scotland: Scottish Family Health Study (GS:SFHS; n=20 221). Rephenotyping was conducted in two phases: a baseline postal survey and a combined postal and online follow-up survey. DOLORisk Dundee consists of 9155 participants (GoDARTS=1915; GS:SFHS=7240) who responded to the baseline survey, of which 6338 (69.2%; GoDARTS=1046; GS:SFHS=5292) also responded to the follow-up survey (18 months later).

FINDINGS TO DATE

At baseline, the proportion of those with chronic neuropathic pain (Douleur Neuropathique en 4 Questions questionnaire score ≥3, duration ≥3 months) was 30.5% in GoDARTS and 14.2% in Generation Scotland. Electronic record linkage enables large scale genetic association studies to be conducted and risk models have been constructed for neuropathic pain.

FUTURE PLANS

The cohort is being maintained by an access committee, through which collaborations are encouraged. Details of how to do this will be available on the study website (http://dolorisk.eu/). Further follow-up surveys of the cohort are planned and funding applications are being prepared to this effect. This will be conducted in harmony with similar pain rephenotyping of UK Biobank.

Predicting Recurrent Care Seeking of Physical Therapy for Musculoskeletal Pain Conditions

OBJECTIVE

Musculoskeletal pain conditions are a leading cause of pain and disability internationally and a common reason to seek health care. Accurate prediction of recurrence of health care seeking due to musculoskeletal conditions could allow for better tailoring of treatment. The aim of this project was to characterize patterns of recurrent physical therapy seeking for musculoskeletal pain conditions and to develop a preliminary prediction model to identify those at increased risk of recurrent care seeking.

DESIGN

Retrospective cohort.

SETTING

Ambulatory care.

SUBJECTS

Patients (n = 578,461) seeking outpatient physical therapy (United States).

METHODS

Potential predictor variables were extracted from the electronic medical record, and patients were placed into three different recurrent care categories. Logistic regression models were used to identify individual predictors of recurrent care seeking, and the least absolute shrinkage and selection operator (LASSO) was used to develop multivariate prediction models.

RESULTS

The accuracy of models for different definitions of recurrent care ranged from 0.59 to 0.64 (c-statistic), and individual predictors were identified from multivariate models. Predictors of increased risk of recurrent care included receiving workers' compensation and Medicare insurance, having comorbid arthritis, being postoperative at the time of the first episode, age range of 44-64 years, and reporting night sweats or night pain. Predictors of decreased risk of recurrent care included lumbar pain, chronic injury, neck pain, pregnancy, age range of 25-44 years, and smoking.

CONCLUSION

This analysis identified a preliminary predictive model for recurrence of care seeking of physical therapy, but model accuracy needs to improve to better guide clinical decision-making.

Prognostic factors for pain chronicity in low back pain: a systematic review

Supplemental Digital Content is Available in the Text.

Several prognostic factors are related to low back pain chronicity, and these should be taken into account when planning more comprehensive models in its prevention.

Low back pain is the leading cause for years lived in disability. Most people with acute low back pain improve rapidly, but 4% to 25% of patients become chronic. Since the previous systematic reviews on the subject, a large number of new studies have been conducted. The objective of this article was to review the evidence of the prognostic factors behind nonspecific chronic low back pain. A systematic literature search was performed without date limitation from the MEDLINE, Cochrane library, and Medic databases. Specific inclusion criteria were used, and risk factors before the onset of chronic symptoms were searched. Study quality was assessed by 2 independent reviewers. One hundred eleven full articles were read for potential inclusion, and 25 articles met all the inclusion criteria. One study was rated as good quality, 19 studies were rated as fair quality, and 5 articles were rated as poor quality. Higher pain intensity, higher body weight, carrying heavy loads at work, difficult working positions, and depression were the most frequently observed risk factors for chronic low back pain. Maladaptive behavior strategies, general anxiety, functional limitation during the episode, smoking, and particularly physical work were also explicitly predictive of chronicity. According to this systematic review, several prognostic factors from the biomechanical, psychological and psychosocial point of view are significant for chronicity in low back pain.

Psychosocial Moderators and Mediators of Sensorimotor Exercise in Low Back Pain: A Randomized Multicenter Controlled Trial

The effects of exercise interventions on unspecific chronic low back pain (CLBP) have been investigated in many studies, but the results are inconclusive regarding exercise types, efficiency, and sustainability. This may be because the influence of psychosocial factors on exercise induced adaptation regarding CLBP is neglected. Therefore, this study assessed psychosocial characteristics, which moderate and mediate the effects of sensorimotor exercise on LBP. A single-blind 3-arm multicenter randomized controlled trial was conducted for 12-weeks. Three exercise groups, sensorimotor exercise (SMT), sensorimotor and behavioral training (SMT-BT), and regular routines (CG) were randomly assigned to 662 volunteers. Primary outcomes (pain intensity and disability) and psychosocial characteristics were assessed at baseline (M1) and follow-up (3/6/12/24 weeks, M2-M5). Multiple regression models were used to analyze whether psychosocial characteristics are moderators of the relationship between exercise and pain, meaning that psychosocial factors and exercise interact. Causal mediation analysis were conducted to analyze, whether psychosocial characteristics mediate the exercise effect on pain. A total of 453 participants with intermittent pain (mean age = 39.5 ± 12.2 years, f = 62%) completed the training. It was shown, that depressive symptomatology (at M4, M5), vital exhaustion (at M4), and perceived social support (at M5) are significant moderators of the relationship between exercise and the reduction of pain intensity. Further depressive mood (at M4), social-satisfaction (at M4), and anxiety (at M5 SMT) significantly moderate the exercise effect on pain disability. The amount of moderation was of clinical relevance. In contrast, there were no psychosocial variables which mediated exercise effects on pain. In conclusion it was shown, that psychosocial variables can be moderators in the relationship between sensorimotor exercise induced adaptation on CLBP which may explain conflicting results in the past regarding the merit of exercise interventions in CLBP. Results suggest further an early identification of psychosocial risk factors by diagnostic tools, which may essential support the planning of personalized exercise therapy. Level of Evidence: Level I. Clinical Trial Registration: DRKS00004977, LOE: I, MiSpEx: grant-number: 080102A/11-14. https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00004977.

Emerging Topics in the Behavioral Neuroscience of Tinnitus

This volume has highlighted the many recent advances in tinnitus theory, models, diagnostics, therapies, and therapeutics. But tinnitus knowledge is far from complete. In this chapter, contributors to the Behavioral Neuroscience of Tinnitus consider emerging topics and areas of research needed in light of recent findings. New research avenues and methods to explore are discussed. Issues pertaining to current assessment, treatment, and research methods are outlined, along with recommendations on new avenues to explore with research.

CLINICAL ANALYSIS OF PATIENTS WITH LOW BACK PAIN IN THE EMERGENCY DEPARTMENT

ABSTRACT Objective To describe the daily practice in an emergency service and to provide relevant data for future studies about the treatment of low back pain from the perspective of emergency medicine. Methods Analysis of hospital records and review of medical records. Results 2,434 patients were attended between January 1 and December 31, 2017 with the complaint of low back pain. Radiographs of the spine were performed in 15.7% of patients and computerized tomography scans in 7.6%. Eighty-five patients required hospitalization, with a mean hospital stay of 8.3 days. The rate of use was 52.7% for tricyclic or antiepileptic drugs and 12% for strong opioids among hospitalized patients. Conclusions A high prevalence of low back complaints was observed in the emergency care service (4.6% of total emergency room visits during the year), with low hospitalization potential. The rates of hospitalization and tomographic examinations were higher than those observed in similar studies, with a lower proportion of radiograph and strong opioid use as compared with the same studies. The paucity of national and international data for more in-depth comparisons makes clear the need for further studies and development of new recommendations specifically targeting this subset of patients. Level of evidence IV; Prognostic studies.

Chronic Pain Diagnosis Using Machine Learning, Questionnaires, and QST: A Sensitivity Experiment

In the last decade, machine learning has been widely used in different fields, especially because of its capacity to work with complex data. With the support of machine learning techniques, different studies have been using data-driven approaches to better understand some syndromes like mild cognitive impairment, Alzheimer’s disease, schizophrenia, and chronic pain. Chronic pain is a complex disease that can recurrently be misdiagnosed due to its comorbidities with other syndromes with which it shares symptoms. Within that context, several studies have been suggesting different machine learning algorithms to classify or predict chronic pain conditions. Those algorithms were fed with a diversity of data types, from self-report data based on questionnaires to the most advanced brain imaging techniques. In this study, we assessed the sensitivity of different algorithms and datasets classifying chronic pain syndromes. Together with this assessment, we highlighted important methodological steps that should be taken into account when an experiment using machine learning is conducted. The best results were obtained by ensemble-based algorithms and the dataset containing the greatest diversity of information, resulting in area under the receiver operating curve (AUC) values of around 0.85. In addition, the performance of the algorithms is strongly related to the hyper-parameters. Thus, a good strategy for hyper-parameter optimization should be used to extract the most from the algorithm. These findings support the notion that machine learning can be a powerful tool to better understand chronic pain conditions.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

IMPACT

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

Implementing high value back pain care in private physiotherapy in Australia: A qualitative evaluation of physiotherapists who participated in an "implementation to innovation" system

Objectives: Many barriers exist to delivering high-value care for people with low back pain (LBP). We have developed a multistrategy implementation system to overcome these barriers. Here we describe a qualitative evaluation of the experiences of private-sector physiotherapists implementing the system.

Design: PRISM (Practice-based innovation and implementation system) is an iterative clinician-as-scientist implementation program, tailored here for acute and subacute LBP. PRISM integrates strategies from behavioral change, implementation, and educational science fields. Semistructured interviews, group discussion forums, and electronic questionnaires were used to collect data at multiple time points that were then analyzed using an interpretative descriptive approach.

Participants: Six physiotherapists (purposive sample) practicing in private practice physiotherapy clinics in the Adelaide region, South Australia, were enrolled in the study.

Interventions: Interventions included an educational pain science and care workshop incorporating self-regulated learning principles, a co-planned clinical pathway, an electronic decision support tool, development and support of a community of practice, case study simulations, audit and feedback, and collaborative problem solving and innovation for physiotherapists.

Results: Participants’ experiences and perceptions centered around five themes: (1) knowledge and skills training; (2) networking and mentoring; (3) a clear clinical pathway; (4) practical tools; and (5) data feedback. Participants appraised the implementation process positively but identified patient receptiveness as a challenge at times. Suggestions for improvement included streamlining/automating data collection forms and processes and providing more simulation opportunities.

Conclusions: PRISM appears to be a promising approach to overcoming several barriers that prevent people with back pain from receiving high-value care. It consolidates and increases pain science knowledge and increases physiotherapist confidence in delivering high-value care. It appears to legitimize some current practices, enhance clinical reasoning and communication skills, extend knowledge in line with contemporary pain science, and facilitate the application of a biopsychosocial management approach. The high-level acceptance by participants provides a foundation for further research to test outcomes and delivery in different settings.

Contribution of the article

A quality improvement intervention designed to improve delivery of high-value care was well received by private practice physiotherapists.

Physiotherapists particularly valued using experiential learning to improve fluency in communicating with, and educating patients about, contemporary pain science.

A structured clinical pathway and tools guided physiotherapists on the basic elements of necessary care and allowed them to concentrate on higher levels of decision making and communication with patients.

Personalized Treatment Suggestions: The Validity and Applicability of the Risk-Prevention-Index Social in Low Back Pain Exercise Treatments

Background: The back pain screening tool Risk-Prevention-Index Social (RPI-S) identifies the individual psychosocial risk for low back pain chronification and supports the allocation of patients at risk in additional multidisciplinary treatments. The study objectives were to evaluate (1) the prognostic validity of the RPI-S for a 6-month time frame and (2) the clinical benefit of the RPI-S. Methods: In a multicenter single-blind 3-armed randomized controlled trial, n = 660 persons (age 18–65 years) were randomly assigned to a twelve-week uni- or multidisciplinary exercise intervention or control group. Psychosocial risk was assessed by the RPI-S domain social environment (RPI-S_SE) and the outcome pain by the Chronic Pain Grade Questionnaire (baseline M1, 12-weeks M4, 24-weeks M5). Prognostic validity was quantified by the root mean squared error (RMSE) within the control group. The clinical benefit of RPI-S_SE was calculated by repeated measures ANOVA in intervention groups. Results: A subsample of n = 274 participants (mean = 38.0 years, SD 13.1) was analyzed, of which 30% were classified at risk in their psychosocial profile. The half-year prognostic validity was good (RMSE for disability of 9.04 at M4 and of 9.73 at M5; RMSE for pain intensity of 12.45 at M4 and of 14.49 at M5). People at risk showed significantly stronger reduction in pain disability and intensity at M4/M5, if participating in a multidisciplinary exercise treatment. Subjects at no risk showed a smaller reduction in pain disability in both interventions and no group differences for pain intensity. Regarding disability due to pain, around 41% of the sample would gain an unfitted treatment without the back pain screening. Conclusion: The RPI-S_SE prognostic validity demonstrated good applicability and a clinical benefit confirmed by a clear advantage of an individualized treatment possibility.

A prediction model of low back pain risk: a population based cohort study in Korea

Background

Well-validated risk prediction models help to identify individuals at high risk of diseases and suggest preventive measures. A recent systematic review reported lack of validated prediction models for low back pain (LBP). We aimed to develop prediction models to estimate the 8-year risk of developing LBP and its recurrence.

Methods

A population based prospective cohort study using data from 435,968 participants in the National Health Insurance Service–National Sample Cohort enrolled from 2002 to 2010. We used Cox proportional hazards models.

Results

During median follow-up period of 8.4 years, there were 143,396 (32.9%) first onset LBP cases. The prediction model of first onset consisted of age, sex, income grade, alcohol consumption, physical exercise, body mass index (BMI), total cholesterol, blood pressure, and medical history of diseases. The model of 5-year recurrence risk was comprised of age, sex, income grade, BMI, length of prescription, and medical history of diseases. The Harrell’s C-statistic was 0.812 (95% confidence interval [CI], 0.804-0.820) and 0.916 (95% CI, 0.907-0.924) in validation cohorts of LBP onset and recurrence models, respectively. Age, disc degeneration, and sex conferred the highest risk points for onset, whereas age, spondylolisthesis, and disc degeneration conferred the highest risk for recurrence.

Conclusions

LBP risk prediction models and simplified risk scores have been developed and validated using data from general medical practice. This study also offers an opportunity for external validation and updating of the models by incorporating other risk predictors in other settings, especially in this era of precision medicine.

An Internet-Based Consumer Resource for People with Low Back Pain (MyBackPain): Development and Evaluation

People increasingly use the internet to obtain information about health complaints, including low back pain (LBP). LBP is the leading cause of disability internationally, and outcomes are worsening. There is an urgent need for resources that aid improvement of outcomes. There have been calls to engage consumers in the development of resources, but this has rarely been implemented. MyBackPain is a website that was developed with extensive involvement of consumers to ensure that the resource meets their needs for content and presentation. This paper aimed to describe the multistep process undertaken to develop the MyBackPain website and provide an extensive evaluation of its impact. Development of MyBackPain involved 10 steps, many of which have been published in the academic literature. These steps included consultation regarding consumer needs, evaluation of existing internet resources, identification of key messages to be reinforced, identification of frequently asked questions, consensus for content, content development (including development of algorithms to guide tailoring of the user experience), development of consumer-focused evidence-based treatment summaries, development of descriptions of health care providers, and testing. Evaluation included qualitative examination of people's interactions with the website and its effects on their daily lives and an ongoing randomized controlled trial of impact of use of the site on people's LBP-related health literacy, clinical outcomes, and treatment choices. It is hoped that the website can aid in the reduction of the massive burden of LBP and provide a template for the development of resources for other conditions.

Kinesiophobia is not required to predict chronic low back pain in workers: a decision curve analysis

BACKGROUND

Currently used performance measures for discrimination were not informative to determine the clinical benefit of predictor variables. The purpose was to evaluate if a former relevant predictor, kinesiophobia, remained clinically relevant to predict chronic occupational low back pain (LBP) in the light of a novel discriminative performance measure, Decision Curve Analysis (DCA), using the Net Benefit (NB).

METHODS

Prospective cohort data (n = 170) of two merged randomized trials with workers with LBP on sickleave, treated with Usual Care (UC) were used for the analyses. An existing prediction model for chronic LBP with the variables 'a clinically relevant change in pain intensity and disability status in the first 3 months', 'baseline measured pain intensity' and 'kinesiophobia' was compared with the same model without the variable 'kinesiophobia' using the NB and DCA.

RESULTS

Both prediction models showed an equal performance according to the DCA and NB. Between 10 and 95% probability thresholds of chronic LBP risk, both models were of clinically benefit. There were virtually no differences between both models in the improved classification of true positive (TP) patients.

CONCLUSIONS

This study showed that the variable kinesiophobia, which was originally included in a prediction model for chronic LBP, was not informative to predict chronic LBP by using DCA. DCA and NB have to be used more often to develop clinically beneficial prediction models in workers because they are more sensitive to evaluate the discriminate ability of prediction models.

Framework for improving outcome prediction for acute to chronic low back pain transitions

Clinical practice guidelines and the Federal Pain Research Strategy (United States) have recently highlighted research priorities to lessen the public health impact of low back pain (LBP). It may be necessary to improve existing predictive approaches to meet these research priorities for the transition from acute to chronic LBP. In this article, we first present a mapping review of previous studies investigating this transition and, from the characterization of the mapping review, present a predictive framework that accounts for limitations in the identified studies. Potential advantages of implementing this predictive framework are further considered. These advantages include (1) leveraging routinely collected health care data to improve prediction of the development of chronic LBP and (2) facilitating use of advanced analytical approaches that may improve prediction accuracy. Furthermore, successful implementation of this predictive framework in the electronic health record would allow for widespread testing of accuracy resulting in validated clinical decision aids for predicting chronic LBP development.

Explanatory multivariate modeling for disability, pain, and claims in patients with spine pain via a physical therapy direct access model of care

BACKGROUND

Direct access physical therapy (DAPT) may result in improved patient outcomes and reduced healthcare costs. Prognostic factors associated with spine-related outcomes and insurance claims with DAPT are needed.

OBJECTIVE

To identify factors that predict variations in outcomes for spine pain and insurance claims using DAPT.

METHODS

Individuals (N = 250) with spine pain were analyzed. Outcomes were classified into High, Low, or Did Not Meet minimal clinically important difference (MCID) scores. Claims were categorized into low, medium, or high tertiles. Prognostic variables were identified from patient information.

RESULTS

Females were more likely to meet High MCID (odds ratio [OR] 2.84 (95% CI = 1.32, 6.11) and Low MCID (OR 2.86, 95% CI = 1.34, 6.10). Higher initial ODI/NDI scores were associated with High MCID (OR 1.04, 95% CI = 1.07, 1.22) and Low MCID (OR 0.91, 95% CI = 0.77, 1.07). Odds of a high claim were lowered by the absence of imaging (OR 0.04, 95% CI = 0.02, 0.09) and an active versus passive treatment (OR 0.38, 95% CI = 0.18, 0.80).

CONCLUSION

Females and higher initial disability predicted favorable outcomes. The novel introduction of claims into the prognostic modeling supports that active interventions and avoiding imaging may reduce claims.