Articles: pain-clinics.
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Acute postoperative pain (APP) is the main cause of postoperative dissatisfaction; however, traditional methods of pain assessment provide limited insights into the dynamics and development of APP. This study used the experience sampling method to understand the dynamics of APP over time in relation to various patient factors. ⋯ Using the experience sampling method data combined with multilevel analysis, we were able to evaluate the postoperative pain course while considering inter-individual differences in the baseline pain level and nonlinear pain course over time. The findings of this study could aid clinicians in personalizing the treatment for APP.
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Historical Article
Introduction and a brief historical overview of the International Association for the Study of Pain.
The mission of the International Association for the Study of Pain (IASP) is "to bring together scientists, clinicians, healthcare providers, and policymakers to stimulate and support the study of pain and to translate that knowledge into improved pain relief worldwide." The IASP will celebrate its 50th anniversary next year, and the series of articles published in this special issue of its flagship journal PAIN highlights the IASP's achievements over the past 5 decades. This article provides a brief historical overview of the IASP's 50-year journey, including the key "players," events, and initiatives leading to its formation and contributing to its progress. It complements the other articles outlining the contributions that the IASP has made and likely will continue to make to advances in pain education, research, management and advocacy, and its value to the IASP members.
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Observing someone experience pain relief or exacerbation after an intervention may induce placebo hypoalgesia or nocebo hyperalgesia. Understanding the factors that contribute to these effects could help in the development of strategies for optimizing treatment of chronic pain conditions. We systematically reviewed and meta-analyzed the literature on placebo hypoalgesia and nocebo hyperalgesia induced by observational learning (OL). ⋯ Overall, the meta-analysis demonstrates that OL can shape placebo hypoalgesia and nocebo hyperalgesia. More research is needed to identify predictors of these effects and to study them in clinical populations. In the future, OL could be an important tool to help maximize placebo hypoalgesia in clinical settings.
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Paediatric chronic pain was a public health emergency before the novel coronavirus (COVID-19) pandemic, and this problem is predicted to escalate. Pain tends to occur intergenerationally in families, and youth with chronic pain and their parents have high rates of mental health issues, which can further exacerbate pain. Siblings of youth with chronic pain have been largely overlooked in research, as well as the impact of the pandemic on posttraumatic stress disorder (PTSD) symptoms and healthcare utilization. ⋯ This study examined pain, mental health, substance use and healthcare utilization in youth with chronic pain, siblings and parents during the COVID-19 pandemic. Greater personal impact of the pandemic was not largely associated with poorer pain outcomes; however, it was associated with mental health, with the largest effect on PTSD symptoms. The high rates and significant association of COVID-19 impact with PTSD symptoms underscore the importance of including PTSD assessment as part of routine screening practices in pain clinics.
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Multicenter Study
Brain morphology predicts individual sensitivity to pain: a multicenter machine learning approach.
Sensitivity to pain shows a remarkable interindividual variance that has been reported to both forecast and accompany various clinical pain conditions. Although pain thresholds have been reported to be associated to brain morphology, it is still unclear how well these findings replicate in independent data and whether they are powerful enough to provide reliable pain sensitivity predictions on the individual level. In this study, we constructed a predictive model of pain sensitivity (as measured with pain thresholds) using structural magnetic resonance imaging-based cortical thickness data from a multicentre data set (3 centres and 131 healthy participants). ⋯ Analysis of model coefficients suggests that the most robust cortical thickness predictors of pain sensitivity are the right rostral anterior cingulate gyrus, left parahippocampal gyrus, and left temporal pole. Cortical thickness in these regions was negatively correlated to pain sensitivity. Our results can be considered as a proof-of-concept for the capacity of brain morphology to predict pain sensitivity, paving the way towards future multimodal brain-based biomarkers of pain.