Articles: neuralgia.
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Central poststroke pain (CPSP) is a severe type of neuropathic pain that can develop after stroke and is difficult to treat. Research into its underlying mechanisms and treatment options could benefit from a valid CPSP animal model. Nine different CPSP animal models have been published, but there are relatively few reports on successful reproductions of these models and so far only little advances in the understanding or the management of CPSP have been made relying on these models. ⋯ We compare the different models regarding these types of validity and discuss the robustness, reproducibility, and problems regarding the design and reporting of the articles establishing these models. We conclude with various proposals on how to improve the validity and reproducibility of CPSP animal models. Until further improvements are achieved, prudence is called for in interpreting results obtained through these models.
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The aim of this study was to determine the risk factors of neuropathic pain (NP) in the patient with carpal tunnel syndrome (CTS) before and after the carpal tunnel release. ⋯ We found that 36% and 18% of patients with CTS had neuropathic pain before and 12 weeks after surgery, respectively, and pain was significantly stronger than in those without NP. The PD score of eight hands worsened after surgery. In the "Improved group," the average age at the surgery was younger and the pain score was lower than in the "Unchanged group." Conclusions. The surgery was very effective on NP of CTS; however, the PD in 7% of hands worsened after surgery. Risk factors before surgery that predicted worse NP after surgery were found to be a younger age, weaker pain, and the absence of night pain.
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To examine whether converting from conventional Spinal Cord Stimulation (SCS) to High Density (HD) SCS reduces neuropathic pain over a period of 12 months in patients with failed SCS therapy. ⋯ Neuropathic pain suppression is significantly enhanced after converting from failed conventional SCS to HD SCS in patients with FBSS, CRPS, and NP over a measured period of 12 months. There appears to be a dose-related response between the amount of energy delivered to the spinal cord and clinical effect.
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Clinical therapeutics · Jan 2017
Predictive Modeling of Response to Pregabalin for the Treatment of Neuropathic Pain Using 6-Week Observational Data: A Spectrum of Modern Analytics Applications.
This post hoc analysis used 11 predictive models of data from a large observational study in Germany to evaluate potential predictors of achieving at least 50% pain reduction by week 6 after treatment initiation (50% pain response) with pregabalin (150-600 mg/d) in patients with neuropathic pain (NeP). ⋯ The finding that pain changes by week 1 or weeks 1 and 3 are the best predictors of pregabalin response at 6 weeks suggests that adhering to a pregabalin medication regimen is important for an optimal end-of-treatment outcome. Regarding baseline predictors alone, considerable published evidence supports the importance of high baseline pain score and presence of depression as factors that can affect treatment response. Future research would be required to elucidate why using pregabalin as a monotherapy also had more than a 10% variable importance as a potential predictor.
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E-52862 (S1RA, 4-[2-[[5-methyl-1-(2-naphthalenyl)-1H-pyrazol-3-yl]oxy]ethyl]-morpholine), a novel selective sigma 1 receptor (σ1R) antagonist, has demonstrated efficacy in nociceptive and neuropathic pain models. Our aim was to test if σ1R blockade with E-52862 may modify the signs of neuropathy in Zucker diabetic fatty (ZDF) rats, a type 2 diabetes model. ⋯ Blockade of σ1R avoids the development of diabetic neuropathy in rats, and may represent a potentially useful therapeutic approach to peripheral neuropathies in diabetic patients. WHAT DOES THIS STUDY ADD?: This study presents evidences for the potential usefulness of sigma receptor blockade on diabetic neuropathy in rats. The methodology includes behavioural evidences, electrophysiological data and vascular-isolated models.