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

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2020-09-24

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Abstract

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 (NPRS) and Oswestry Disability Index (ODI). Exploratory hierarchical agglomerative cluster analysis identified empirically derived subgroups based on physical impairment measures. Independent samples t testing and chi-square analysis assessed 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 ODI scores but not for NPRS 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.

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10.1093/ptj/pzaa179

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Beneciuk, Jason M, and Steven Z George (2020). Adding Physical Impairment to Risk Stratification Improved Outcome Prediction in Low Back Pain. Physical therapy. 10.1093/ptj/pzaa179 Retrieved from https://hdl.handle.net/10161/21564.

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George

Steven Zachary George

Laszlo Ormandy Distinguished Professor of Orthopaedic Surgery

Dr. George’s primary interest is research involving biopsychosocial models for the prevention and treatment of chronic musculoskeletal pain disorders.  His long term goals are to 1) improve accuracy for predicting who is going to develop chronic pain; and 2) identify non-pharmacological treatment options that limit the development of chronic pain conditions.  Dr. George is an active member of the American Physical Therapy Association, United States Association of the Study of Pain, and International Association for the Study of Pain. 

Dr. George’s research projects have been supported by the National Institutes of Health, Department of Defense, and Orthopaedic Academy of the American Physical Therapy Association.  Dr. George and his collaborators have authored over 330 peer-reviewed publications in leading medical, orthopaedic surgery, physical therapy, rehabilitation, and pain research journals.  He currently serves as Editor-in-Chief for the Physical Therapy & Rehabilitation Journal. Dr. George has also been involved with clinical practice guideline development for the Academy of Orthopaedic Physical Therapy and the American Psychological Association. 

Dr. George has been recognized with prestigious research awards from the American Physical Therapy Association, American Pain Society, and International Association for the Study of Pain. For example from the American Physical Therapy Association: he was named the  21st John H.P. Maley Lecturer, recognized as a Catherine Worthingham Fellow in 2017, and selected for the Marian Williams Award for Research in Physical Therapy in 2022.    


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