European journal of pain : EJP
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Psychological treatments are known to be effective for chronic pain, but little is understood about which patients are most likely to benefit from which ones. ⋯ Further research is needed to better understand who benefits most from psychological treatments for chronic pain. This study suggests that a flexible, multivariate and theoretical approach to identifying predictors of outcome may be valuable in furthering research in this area.
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Actigraphy is a quantitative method for the investigation of human physical activity and is normally based on accelerometric and/or kinematic data. ⋯ People with chronic pain move differently. Movement quality is difficult to evaluate during daily activities, yet it may prove more informative than quantitative measurements. We proposed a new approach for computing movement complexity and found out that patients' movements get more stereotyped when higher spinal acceleration is required.
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We analysed outcome domains and pain outcome measures in randomized controlled trials of interventions for postoperative pain management in children and adolescents and compared them to the core outcome set recommended by the Pediatric Initiative on Methods, Measurement and Pain Assessment in Clinical Trials (PedIMMPACT). ⋯ Recommended core outcomes have been insufficiently used in randomized controlled trials about postoperative pain in children, which hinders comparability of studies and makes synthesis of evidence difficult.
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Chronic pain is often accompanied by comorbidities like anxiety and depression. The temporal correlations, as well as the underlying mechanisms of these reciprocal correlations, are unclear. Moreover, preclinical studies examining emotional behaviour are very controversial, and a chronological analysis of anxiety-like behaviour in mouse pain models considering both genders has not been performed so far. ⋯ Anxiety-like behaviour is not primarily altered following CFA and SNI in C57BL6 mice, irrespective of the gender, mouse sub-strain, housing conditions or affected body side within the herein investigated time period.
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The prognosis of acute low back pain (LBP) is typically good; however, there is substantial variation in individual patient's outcomes. We recently developed a prediction model that was able to predict the likelihood of pain recovery in patients with acute LBP who continue to have pain approximately 1 week after initially seeking care. The aims of the current study were to (a) re-categorize the variables in the developmental dataset to be able to validate the model in the validation dataset; (b) refit the existing model in the developmental dataset; and (c) validate the model in the validation dataset. ⋯ A clinical prediction model based on five easily collected variables demonstrated reasonable external validity. The prediction model has the potential to inform patients and clinicians of the likely prognosis of individuals with acute LBP but requires impact studies to assess its clinical usefulness.