Artificial intelligence and machine learning (AI/ML) could enhance the ability to detect patterns of clinical characteristics in low-back pain (LBP) and guide treatment. We …
B Pilz, RA Vasconcelos, FB Marcondes… - Brazilian journal of …, 2014 - SciELO Brasil
Background: Psychosocial factors are not routinely identified in physical therapy assessments, although they can influence the prognosis of patients with low back pain. The" …
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 …
Background Current research emphasizes the high prevalence and costs of low back pain (LBP). The STarT Back Tool was designed to support primary care decision making for …
G Sowden, JC Hill, L Morso, Q Louw… - Brazilian Journal of …, 2018 - Elsevier
Background Low back pain (LBP) is common, however research comparing the effectiveness of different treatments over the last two decades conclude either no or small …
A Lardon, JD Dubois, V Cantin, M Piché… - Applied ergonomics, 2018 - Elsevier
Abstracts Objectives The objective of this study was to identify baseline predictors of disability and absenteeism in workers with a history of non-specific low back pain (LBP) …
Objective. The purpose of this study was to translate and to investigate the reliability and validity of the STarT Back screening tool (SBT) in the primary care setting among patients …
Purpose We aimed to identify and inventory clinical decision support (CDS) tools for helping front-line staff select interventions for patients with musculoskeletal (MSK) disorders …
Objectives Stratified care using prognostic models to estimate the risk profiles of patients has been increasing. A refined version of the popular STarT Back tool, the Keele STarT MSK …