Framework for improving outcome prediction for acute to chronic low back pain transitions.
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2020-03-04
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Abstract
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.
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George, Steven Z, Trevor A Lentz, Jason M Beneciuk, Nrupen A Bhavsar, Jennifer M Mundt and Jeff Boissoneault (2020). Framework for improving outcome prediction for acute to chronic low back pain transitions. Pain reports, 5(2). p. e809. 10.1097/pr9.0000000000000809 Retrieved from https://hdl.handle.net/10161/20716.
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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.
Trevor A. Lentz
Nrupen Bhavsar
I am a quantitative epidemiologist with methodological expertise in the design and analysis of observational studies that leverage data from cohort studies, registries, and the electronic health record (EHR). My background, training, and research is in the measurement and characterization of biomarkers, risk factors and treatment outcomes for chronic disease using real-world datasets. My primary research interests are in the use of novel sources of data, including the EHR, to conduct chronic disease research at the intersection of informatics, biostatistics, and epidemiology. My ongoing work aims to integrate informatics, epidemiology, and biostatistics to reduce the burden of chronic disease. I have topical expertise in multiple chronic diseases, including oncology, cardiovascular disease, and chronic kidney disease. In parallel, I have a portfolio of research that aims to understand the impact of social determinants of health, including dynamic neighborhood changes, such as gentrification, on the health of adults and children.
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