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Additional file 1: Table S1: Clinical and demographic findings in 35 patients with LOPD

Additional file 4: Table S4: Morphometric analysis of skin biopsies from twenty healthy controls

Additional file 2: Table S2: Self-reported data on pain, anxiety and depression symptoms in 35 patients with LOPD

Additional file 3: Table S3: Morphometric analysis of skin biopsies from 35 patients with LOPD

Supplemental material, Pitarokoili_Supplementary_tables for Neuroimaging markers of clinical progression in chronic inflammatory demyelinating polyradiculoneuropathy by Kalliopi Pitarokoili, Dietrich Sturm, Adnan Labedi, Tineke Greiner, Lynn Eitner, Nina Kumowski, Elena K. Enax-Krumova, Anna Lena Fisse, Christoph Maier, Ralf Gold, Martin Tegenthoff, Tobias Schmidt-Wilcke and Min-Suk Yoon in Therapeutic Advances in Neurological Disorders

Supplemental Digital Content is Available in the Text. Phenotype stratification of patients with peripheral neuropathic pain can be conducted with a novel algorithm based on sensory profiles., In a recent cluster analysis, it has been shown that patients with peripheral neuropathic pain can be grouped into 3 sensory phenotypes based on quantitative sensory testing profiles, which are mainly characterized by either sensory loss, intact sensory function and mild thermal hyperalgesia and/or allodynia, or loss of thermal detection and mild mechanical hyperalgesia and/or allodynia. Here, we present an algorithm for allocation of individual patients to these subgroups. The algorithm is nondeterministic—ie, a patient can be sorted to more than one phenotype—and can separate patients with neuropathic pain from healthy subjects (sensitivity: 78%, specificity: 94%). We evaluated the frequency of each phenotype in a population of patients with painful diabetic polyneuropathy (n = 151), painful peripheral nerve injury (n = 335), and postherpetic neuralgia (n = 97) and propose sample sizes of study populations that need to be screened to reach a subpopulation large enough to conduct a phenotype-stratified study. The most common phenotype in diabetic polyneuropathy was sensory loss (83%), followed by mechanical hyperalgesia (75%) and thermal hyperalgesia (34%, note that percentages are overlapping and not additive). In peripheral nerve injury, frequencies were 37%, 59%, and 50%, and in postherpetic neuralgia, frequencies were 31%, 63%, and 46%. For parallel study design, either the estimated effect size of the treatment needs to be high (>0.7) or only phenotypes that are frequent in the clinical entity under study can realistically be performed. For crossover design, populations under 200 patients screened are sufficient for all phenotypes and clinical entities with a minimum estimated treatment effect size of 0.5.

Background In unilateral neuropathic pain. e.g. after peripheral nerve injury, both positive and negative sensory signs occur often, accompanied by minor but equally directed contralateral sensory changes. To mimic this feature, we experimentally aimed to induce concomitant c-fibre sensitization and block in healthy subjects and analyzed the bilateral sensory changes by quantitative sensory testing (QST) using the protocol of the German Research Network on Neuropathic Pain. Methods Twenty eight healthy subjects were firstly randomized in 2 groups to receive either topical capsaicin (0.6%, 12 cm2, application duration: 15 min.) or a lidocaine/prilocaine patch (25/25 mg, 10 cm2, application duration: 60 min.) on the right volar forearm. Secondly, 7–14 days later in the same area either at first capsaicin (for 15 min.) and immediately afterwards local anesthetics (for 60 min.) was applied (Cap/LA), or in inversed order with the same application duration (LA/Cap). Before, after each application and 7–14 days later a QST was performed bilaterally. Statistics: Wilcoxon-test, ANOVA, p

Clinical and human experimental pain studies often include so-called "healthy" controls in investigations of sensory abnormalities, using quantitative sensory testing (QST) as an outcome measure. However, the criteria for what is considered "healthy" vary among the different studies and between study centers and investigators, partly explaining the high variability of the results. Therefore, several aspects should be considered during inclusion of healthy volunteers in QST-based trials in order to have homogenous groups of healthy controls with less variability between human experimental studies, so that results are less likely to be false negative or false positive due to subject related factors.The EUROPAIN and NEUROPAIN consortia aimed to define factors influencing the variability in selection of healthy subjects in QST-based studies before the start of both projects and to give recommendations how to minimize it based on the current literature and expertise of the participants. The present suggestions for inclusion criteria of healthy volunteers into QST-based trials describe a two-level approach including standardized questionnaires enabling the collection of relevant information on socio-demographic data, medical history, current health status, coping strategies in dealing with pain, and the motivation of the volunteer to participate in the study. These suggestions are believed to help researchers interpret their results in comparison to others and improve the quality of clinical studies including healthy volunteers as controls or in human experimental pain studies. They aim to reduce any confounding factors. Furthermore, the acquired information will allow post-hoc analyses of variance for different potential influencing factors.

Context. Opioid prescriptions from the emergency department (ED) have gradually increased over the last 20 years. Mounting evidence of the potential for abuse of these drugs, even after a transient ED encounter, has fueled a push to curtail the prescriptions of opioids from the ED. Objectives. It is important to analyze the types of etiologies and provider demographics that drive opioid prescription in our emergency departments. Our study aimed to determine which patients in the ED are receiving opioid prescriptions, as well as their strength and quantity. Secondary outcomes included identifying difference in prescribing between provider classes. Methods. We conducted a retrospective study at a tertiary care university-based, level-one trauma ED from November 2017 to October 2018. We identified and analyzed data from 2,259 patients who were sent home with an opioid prescription. We retrieved patient and provider demographics, diagnosis, etiologies, and prescription information. Results. The mean age of a patient receiving an opioid prescription was 45, and 72.7% of patients were white. The most common diagnosis groups associated with an opioid prescription were abdominal pain (18.5%), nonfracture extremity pain (18.4%), and back/neck pain (12.5%). Hydrocodone-acetaminophen 5–325 mg was the most commonly prescribed (67.4%). The median total prescribed milligram morphine equivalent (MME) was highest for extremity fracture (75.0; IQR 54.0–100.0). The median total prescribed amount of pills was highest for patients with extremity fractures (15.0; IQR 12.0–20.0). Conclusions. Our study elucidates the prescribing patterns of an academic level 1 trauma center and should pave the way for future studies looking to maximize effectiveness at ways to curb ED opioid prescription.