Articles: pain-clinics.
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The efficacy of acupuncture in treating pain diseases has been recognized in clinical practice, and its mechanism of action has been a hot topic in academic acupuncture research. Previous basic research on acupuncture analgesia has focused mostly on the nervous system, with few studies addressing the immune system as a potential pathway of acupuncture analgesia. In this study, we investigated the effect of electroacupuncture (EA) on the β-endorphins (β-END) content, END-containing leukocyte type and number, sympathetic neurotransmitter norepinephrine (NE), and chemokine gene expression in inflamed tissues. ⋯ Flow cytometry and immunofluorescence staining revealed that the EA-induced increase in β-END was derived from opioid-containing ICAM-1 + /CD11b + immune cells in inflamed tissue. In addition, EA treatment increased the NE content and expression of β2 adrenergic receptor (ADR-β2) in inflammatory tissues and upregulated Cxcl1 and Cxcl6 gene expression levels. These findings provide new evidence for the peripheral analgesic effect of acupuncture treatment by recruiting β-END-containing ICAM-1 + /CD11b + immune cells and increasing the β-END content at the site of inflammation.
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Randomized Controlled Trial
Behavioral cancer pain intervention dosing: results of a Sequential Multiple Assignment Randomized Trial.
Behavioral pain management interventions are efficacious for reducing pain in patients with cancer. However, optimal dosing of behavioral pain interventions for pain reduction is unknown, and this hinders routine clinical use. A Sequential Multiple Assignment Randomized Trial (SMART) was used to evaluate whether varying doses of Pain Coping Skills Training (PCST) and response-based dose adaptation can improve pain management in women with breast cancer. ⋯ Varying PCST doses led to pain reduction over time. Intervention sequences demonstrating the most durable decreases in pain reduction included PCST-Full. Pain Coping Skills Training with intervention adjustment based on response can produce sustainable pain reduction.
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Randomized Controlled Trial
No effect of social interaction on experimental pain sensitivity: a randomized experimental study.
Quantitative sensory testing (QST) is a commonly applied paradigm to investigate pain, which is a subjective experience influenced by a myriad of social and contextual factors. Therefore, it is important to consider the potential sensitivity of QST to the test setting and the social interaction that naturally is a part of it. This may particularly be the case in clinical settings where patients have something at stake. ⋯ All 3 setups consisted of the same pain tests in the same order, including pressure pain threshold and cold pressor tests. We found no statistically significant differences between setups on the primary outcome of conditioned pain modulation nor any secondary QST outcomes. While this study is not without limitations, the results indicate that QST procedures are robust enough not to be influenced by social interaction to an appreciable degree.
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Current automated pain assessment methods only focus on infants or youth. They are less practical because the children who suffer from postoperative pain in clinical scenarios are in a wider range of ages. In this article, we present a large-scale Clinical Pain Expression of Children (CPEC) dataset for postoperative pain assessment in children. ⋯ The CPANN achieves 82.1% accuracy and 73.9% macro-F1 score on the testing set of CPEC. The CPANN is faster, more convenient, and more objective compared with using pain scales according to the specific type of pain or children's condition. This study demonstrates the effectiveness of deep learning-based method for automated pain assessment in children.
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Pain is the leading cause of disability worldwide, imposing an enormous burden on personal health and society. Pain is a multifactorial and multidimensional problem. Currently, there is (some) evidence that genetic factors could partially explain individual susceptibility to pain and interpersonal differences in pain treatment response. ⋯ However, replication studies with consistent phenotype definitions and sufficient statistical power are required to validate these pain-associated genes further. Our review also highlights the need for bioinformatic tools to elucidate the function of identified genes/loci. We believe that a better understanding of the genetic background of pain will shed light on the underlying biological mechanisms of pain and benefit patients by improving the clinical management of pain.