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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., (Copyright © 2024 International Association for the Study of Pain.)

Abstract: We developed the SupportPrim PT clinical decision support system (CDSS) using the artificial intelligence method case-based reasoning to support personalised musculoskeletal pain management. The aim of this study was to evaluate the effectiveness of the CDSS for patients in physiotherapy practice. A cluster randomised controlled trial was conducted in primary care in Norway. We randomised 44 physiotherapists to (1) use the CDSS alongside usual care or (2) usual care alone. The CDSS provided personalised treatment recommendations based on a case base of 105 patients with positive outcomes. During the trial, the case-based reasoning system did not have an active learning capability; therefore, the case base size remained the same throughout the study. We included 724 patients presenting with neck, shoulder, back, hip, knee, or complex pain (CDSS; n = 358, usual care; n = 366). Primary outcomes were assessed with multilevel logistic regression using self-reported Global Perceived Effect (GPE) and Patient-Specific Functional Scale (PSFS). At 12 weeks, 165/298 (55.4%) patients in the intervention group and 176/321 (54.8%) in the control group reported improvement in GPE (odds ratio, 1.18; confidence interval, 0.50-2.78). For PSFS, 173/290 (59.7%) patients in the intervention group and 218/310 (70.3%) in the control group reported clinically important improvement in function (odds ratio, 0.41; confidence interval, 0.20-0.85). No significant between-group differences were found for GPE. For PSFS, there was a significant difference favouring the control group, but this was less than the prespecified difference of 15%. We identified several study limitations and recommend further investigation into artificial intelligence applications for managing musculoskeletal pain., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the International Association for the Study of Pain.)

Moderate to severe chronic pain is a problem for 1.7 million children, costing $19.5 billion dollars annually in the United States alone. Risk-stratified care is known to improve outcomes in adults with chronic pain. However, no tool exists to stratify youth who present with pain complaints to appropriate interventions. The Pediatric Pain Screening Tool (PPST) presented here assesses prognostic factors associated with adverse outcomes among youth and defines risk groups to inform efficient treatment decision making. Youth (n = 321, ages 8-18, 90.0% Caucasian, 74.8% female) presenting for multidisciplinary pain clinic evaluation at a tertiary care center participated. Of these, 195 (61.1%) participated at 4-month follow-up. Participants completed the 9-item PPST in addition to measures of functional disability, pain catastrophizing, fear of pain, anxiety, and depressive symptoms. Sensitivity and specificity for the PPST ranged from adequate to excellent, with regard to significant disability (78%, 68%) and high emotional distress (81%, 63%). Participants were classified into low- (11%), medium- (32%), and high- (57%) risk groups. Risk groups did not significantly differ by pain diagnosis, location, or duration. Only 2% to 7% of patients who met reference standard case status for disability and emotional distress at 4-month follow-up were classified as low risk at baseline, whereas 71% to 79% of patients who met reference standard case status at follow-up were classified as high risk at baseline. A 9-item screening tool identifying factors associated with adverse outcomes among youth who present with pain complaints seems valid and provides risk stratification that can potentially guide effective pain treatment recommendations in the clinic setting.

Back pain is a leading cause of disability. Previous research suggests that modifiable risk factors influence recovery from back pain, and practice guidelines recommend integrating such factors within primary care management. Toward this goal, a brief, multidimensional questionnaire, the STarT Back Tool, was designed to facilitate risk assessment by reducing the need to administer multiple, unidimensional questionnaires. However, aspects of this tool's clinical utility remain unaddressed. For instance, it is unclear whether this tool is responsive to treatment-related changes or whether clinically meaningful information is lost when it replaces multiple risk questionnaires. This study compared the responsiveness of the STarT Back Tool to its corresponding full-length measures, and evaluated its ability to detect clinically meaningful improvement. The study sample included 300 participants that consulted their doctor with disabling back pain. The STarT Back Tool and its reference standard questionnaires (disability, catastrophizing, fear, and depression) were administered at baseline and 4 months later. Regression analyses tested whether, after controlling for its reference standard questionnaires, the STarT Back Tool (independent variable) predicted treatment-related changes in global improvement, pain severity, disability, catastrophizing, fear, and depression (dependent variables). Receiver operating characteristic analyses determined the level of STarT Back change needed for clinically meaningful improvement. STarT Back scores predicted changes in all dependent variables except depression. Reductions in STarT Back scores predicted meaningful improvement on all dependent variables. These findings suggest that the STarT Back Tool, instead of multiple risk questionnaires, can be used to measure recovery from back pain. Implications for future research and clinical practice are discussed., (Copyright © 2012 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.)