Longitudinal Monitoring of Pain Associated Distress with the Optimal Screening for Prediction of Referral and Outcome Yellow Flag (OSPRO-YF) Tool: Predicting Reduction Pain Intensity and Disability.
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2020-06-26
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OBJECTIVE:To investigate the Optimal Screening for Prediction of Referral and Outcome Yellow Flag (OSPRO-YF) tool for longitudinal monitoring of pain associated distress with the goal of improving prediction of 50% reduction in pain intensity and disability outcomes. DESIGN:Cohort study with 12-month follow-up after initial care episode SETTING: Ambulatory care, participants seeking care from out-patient physical therapy clinics PARTICIPANTS: Participants were seeking care for primary complaint of neck, low back, knee or shoulder pain. This secondary analysis included 440 subjects (62.5% female; mean age 45.1± 17) at baseline with n=279 (63.4%) providing follow-up data at 12 months. INTERVENTIONS:Not applicable MAIN OUTCOME MEASURES: 50% reduction (baseline to 12-month follow-up) in pain intensity and self-reported disability RESULTS: Trends for prediction accuracy were similar for all versions of the OSPRO-YF. For predicting 50% reduction in pain intensity, model fit met the statistical criterion for improvement (i.e., p < 0.05) with each additional time point added from baseline. Model discrimination improved statistically when the 6-month to 12-month change was added to the model (Area Under the Curve = 0.849, p = 0.003). For predicting 50% reduction in disability, there was no evidence of improvement in model fit or discrimination from baseline with the addition of 4-week, 6-month, or 12-month changes (p's > 0.05). CONCLUSIONS:These results suggested that longitudinal monitoring improved prediction accuracy for reduction in pain intensity, but not for disability reduction. Differences in OSPRO-YF item sets (10 vs. 17 items) or scoring methods (simple summary score vs. yellow flag count) did not impact predictive accuracy for pain intensity, providing flexibility for implementing this tool in practice settings.
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George, Steven Z, Cai Li, Sheng Luo, Maggie E Horn and Trevor A Lentz (2020). Longitudinal Monitoring of Pain Associated Distress with the Optimal Screening for Prediction of Referral and Outcome Yellow Flag (OSPRO-YF) Tool: Predicting Reduction Pain Intensity and Disability. Archives of physical medicine and rehabilitation. 10.1016/j.apmr.2020.05.025 Retrieved from https://hdl.handle.net/10161/21215.
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![George](https://scholars.duke.edu/profile-images/thumbnail200/0718420.jpg)
Steven Zachary George
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.
![Luo](https://scholars.duke.edu/profile-images/thumbnail200/0796693.jpg)
Sheng Luo
![Horn](https://scholars.duke.edu/profile-images/thumbnail200/0724263.jpg)
Maggie Elizabeth Horn
![Lentz](https://scholars.duke.edu/profile-images/thumbnail200/0807451.jpg)
Trevor A. Lentz
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