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Assessing features of centralized pain may prove to be clinically meaningful in pediatric populations. However, we are currently limited by the lack of validated pediatric measures.
Learn More >Chronic low back pain (cLBP) is associated with widespread functional and structural changes in the brain. This study aims to investigate the resting state functional connectivity (rsFC) changes of visual networks in cLBP patients and the feasibility of distinguishing cLBP patients from healthy controls using machine learning methods. cLBP (n = 90) and control individuals (n = 74) were enrolled and underwent resting-state BOLD fMRI scans. Primary, dorsal, and ventral visual networks derived from independent component analysis were used as regions of interest to compare resting state functional connectivity changes between the cLBP patients and healthy controls. We then applied a support vector machine classifier to distinguish the cLBP patients and control individuals. These results were further verified in a new cohort of subjects. We found that the functional connectivity between the primary visual network and the somatosensory/motor areas were significantly enhanced in cLBP patients. The rsFC between the primary visual network and S1 was negatively associated with duration of cLBP. In addition, we found that the rsFC of the visual network could achieve a classification accuracy of 79.3% in distinguishing cLBP patients from HCs, and these results were further validated in an independent cohort of subjects (accuracy = 66.7%). Our results demonstrate significant changes in the rsFC of the visual networks in cLBP patients. We speculate these alterations may represent an adaptation/self-adjustment mechanism and cross-model interaction between the visual, somatosensory, motor, attention, and salient networks in response to cLBP. Elucidating the role of the visual networks in cLBP may shed light on the pathophysiology and development of the disorder.
Learn More >Over 100 million Americans live with chronic pain, and adults with chronic pain may be more likely to experience alcohol-related problems or Alcohol Use Disorder. An evolving conceptual model posits that bidirectional effects between pain and alcohol exacerbate both pain and drinking. Pain has been shown to motivate alcohol urge and consumption, and drinking for pain-coping predicts escalations in alcohol use over time. Pain-related anxiety is a transdiagnostic vulnerability factor that has been implicated in both pain and substance-related (i.e., tobacco, opioids, cannabis) outcomes, but has not yet been studied in relation to alcohol use.
Learn More >General practitioners' (GPs) views about deprescribing prescription opioid analgesics (POAs) may influence the care provided for patients experiencing chronic noncancer pain (CNCP). There are limited data addressing GPs' beliefs about deprescribing, including their decisions to deprescribe different types of POAs.
Learn More >The aim of this study was to identify the clinical characteristics, treatment usage, and health outcomes of US adults diagnosed with neuropathic pain (NeP) by experienced physicians.
Learn More >Open-label placebos (OLPs) have been found to elicit significant and clinical meaningful effects, but in comparison to deceptive placebo administration there is a lack of research regarding possible predictors. This study sets out to examine the effects of optimism and other personality-related variables on OLP responses.
Learn More >It has been suggested that patients with chronic non-specific low back pain (CNSLBP) perform poorly in postural tasks when compared to healthy individuals. Despite its importance in posture and alignment of the trunk in relation to the head, neck proprioception has not been examined in patients with low back pain. The purpose of this study was to compare neck proprioception in patients with CNSLBP with healthy individuals.
Learn More >To evaluate, in vivo, the impact of ongoing chronic migraine (CM) attacks on the endogenous μ-opioid neurotransmission.
Learn More >Chronic pain, such as low-back pain, can be a highly disabling condition degrading people's quality of life (QoL). Not every patient responds to pharmacological therapies, thus alternative treatments have to be developed. The chronicity of pain can lead to a somatic dysperception, meaning a mismatch between patients' own body perception and its actual physical state. Since clinical evaluation of pain relies on patients' subjective reports, a body image disruption can be associated with an incorrect pain rating inducing incorrect treatment and a possible risk of drug abuse. Our aim was to reduce chronic low-back pain through a multimodal neurorehabilitative strategy using innovative technologies to help patients regain a correct body image.
Learn More >High dose monotherapies or drug combinations are used to achieve sufficient analgesia for the treatment of severe chronic low back pain, before invasive therapy options are considered. In order to demonstrate an alternative for an empirical treatment approach, the authors' primary aim was to present an algorithm for the objective identification of treatment predictors. Additionally, the study identified baseline-characteristics in chronic low back pain patients prior to tapentadol PR treatment, as well as scrutinized those patients, either benefitting from a medium/high dose tapentadol PR monotherapy or a combination therapy (medium dose tapentadol PR + pregabalin). The statistical approach included data of a previously published randomized, double blind, phase 3b study which compared the effectiveness and safety of tapentadol PR vs. a combination of tapentadol PR and pregabalin. In total, 46 clinical parameters were included in the statistical prediction models which were applied separately either to 50 patients who already responded well during the titration period (i.e., medium dose tapentadol PR) or to 261 patients with in the comparative treatment period [i.e., monotherapy (high dose tapentadol PR) or combination therapy (medium dose tapentadol PR/pregabalin)]. The first statistical model identified three co-variables (NRS-3, PDQ, SQ) with predictive effects on patients responding well ("optimal responders") to a medium dose tapentadol PR titration. Those patients presented low baseline pain intensity scores, good sleep quality and high painDETECT scores. The second statistical model identified eight co-variables (PDQ, numbness, SF-12 MCS, SF-12 PCS, VAS, HADS-A, HADS-D, SQ) with predictive effects on patients responding to high dose tapentadol PR monotherapy vs. a combination therapy (tapentadol PR + pregabalin). The high dose tapentadol PR responders indicated high painDETECT scores, little numbness and a good mental health status. Whereas, the combination therapy (tapentadol PR + pregabalin) responders were characterized by severe sleep disturbances and little anxiety. The statistical analysis characterized chronic low back pain patients and identified factors contributing to a treatment response. Thus, this retrospective statistical algorithm represents an elegant method, which may contribute to future strategies toward a more individualized and improved mechanism based pain therapy.
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