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Objectives: To create a classifier based on electroencephalography (EEG) to identify spinal cord injured (SCI) participants at risk of developing central neuropathic pain (CNP) by comparing them with patients who had already developed pain and with able bodied controls., Methods: Multichannel EEG was recorded in the relaxed eyes opened and eyes closed states in 10 able bodied participants and 31 subacute SCI participants (11 with CNP, 10 without NP and 10 who later developed pain within 6 months of the EEG recording). Up to nine EEG band power features were classified using linear and non-linear classifiers., Results: Three classifiers (artificial neural networks ANN, support vector machine SVM and linear discriminant analysis LDA) achieved similar average performances, higher than 85% on a full set of features identifying patients at risk of developing pain and achieved comparably high performance classifying between other groups. With only 10 channels, LDA and ANN achieved 86% and 83% accuracy respectively, identifying patients at risk of developing CNP., Conclusion: Transferable learning classifier can detect patients at risk of developing CNP. EEG markers of pain appear before its physical symptoms. Simple and complex classifiers have comparable performance., Significance: Identify patients to receive prophylaxic treatment of CNP., (Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Pain is a common complication in patients following spinal cord injury (SCI), with studies citing up to 80% of patients reporting some form of pain. Neuropathic pain (NP) makes up a substantial percentage of all pain symptoms in patients with SCI and is often complex. Given the high prevalence of NP in patients with SCI, proper identification and treatment is imperative. Indeed, identification of pain subtypes is a vital step toward determining appropriate treatment. A variety of pharmacological and non-pharmacological treatments can be undertaken including antiepileptics, tricyclic antidepressants, opioids, transcranial direct current stimulation, and invasive surgical procedures. Despite all the available treatment options and advances in the field of SCI medicine, providing adequate treatment of NP after SCI continues to be challenging. It is therefore extremely important for clinicians to have a strong foundation in the identification of SCI NP, as well as an understanding of appropriate treatment options. Here, we highlight the definitions and classification tools available for NP identification, and discuss current treatment options. We hope that this will not only provide a better understanding of NP for physicians in various subspecialties, but that it will also help guide future research on this subject., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Purpose: We report the treatment of 9 patients with 9 painful neuromas at the tips of the digits using reverse pedicled island flaps containing subcutaneous nerves that were connected to the digital nerve stumps after removal of the neuromas., Methods: There were 9 patients (7 men and 2 women) with painful cutaneous neuromas at the tips of the digits. The ages of the patients at time of surgery were 21 to 66 years (mean, 46 y). All neuromas were formed in the palmar digital nerves in the hand. Preoperative and postoperative status of the patients with neuromas were assessed and graded using a system modified from previously described grading systems for patients with neuromas. Recovery of sensation in the transplanted skin islands was assessed using the Semmes-Weinstein monofilament test., Results: In the preoperative assessment of patients using the grading system for neuromas, 3 patients were assessed as grade 4 (severe), 5 patients as grade 3 (moderate), and the remaining patient as grade 2 (mild). After surgery, Tinel sign disappeared completely in 6 of 9 patients. According to the grading system for neuromas, 6 patients were assessed as grade 1 (normal), and the other 3 patients were assessed as grade 2 (mild) postoperatively. Using the Semmes-Weinstein monofilament test for assessing recovery of sensation of the skin islands, 3 patients recognized the 2.83 monofilament (normal), 2 patients recognized the 3.22 monofilament (loss of tactile sense), and the remaining 4 patients recognized the 3.66 monofilament applied (loss of tactile sense)., Conclusions: This skin island approach provided us with good pain control and recovery of hand function after painful neuromas., Type of Study/level of Evidence: Therapeutic IV.

Neuropathic pain is the focus of current clinical research, clinical identification, and treatment. It is unique from nociceptive pain and requires evaluation of the relevance and utility of common pain measures created for other painful conditions. This study evaluated the psychometric properties of a modified Brief Pain Inventory (BPI) for patients with painful diabetic peripheral neuropathy (BPI-DPN). Participants were patients with painful DPN (n=255) enrolled in a DPN Burden of Illness survey referred through 17 outpatient settings (primary care physicians, endocrinologists, neurologists, and anesthesiologists). Patients completed the BPI-DPN, and self-report measures of health-related quality of life, mood sleep, and healthcare utilization. Construct, criterion and discriminant validity, and internal consistency reliability were evaluated. Principal axis factoring with oblimin rotation revealed two interpretable factors (eigenvalues>1.0), consistent with most published BPI validation studies; a severity scale comprising the four BPI Severity items and an interference scale comprising the seven Interference items, which satisfied criteria for interpretability and model fit. Cronbach's alpha was high (0.94) for both scales. Mean pain Severity was highly correlated with Bodily Pain from the Medical Outcomes Study Short Form-12, version 2 (rs=0.63, P < 0.001), the Pain/Discomfort item in the Euro-QoL (rs=0.58, P < 0.001), and a verbal rating scale measure of pain severity (rs=0.74, P < 0.001). Individual BPI-DPN Interference domains were moderately correlated (rs's >0.5, P < 0.001) with analogous measures, and the Sleep Interference item had a high, significant association with the three primary Medical Outcome Study-Sleep scale subscales (rs's=0.66-71, P < 0.001). Worst Pain and Interference ratings were significantly associated with hospital utilization and outpatient visits due to DPN. These results replicate, in a pure peripheral neuropathic pain condition, the BPI psychometric characteristics documented in populations with nociceptive or mixed pain conditions. The BPI-DPN is a promising instrument in the evaluation of painful DPN.

Currently, no consensus on the optimal management of neuropathic pain exists and practices vary greatly worldwide. Possible explanations for this include difficulties in developing agreed diagnostic protocols and the coexistence of neuropathic, nociceptive and, occasionally, idiopathic pain in the same patient. Also, neuropathic pain has historically been classified according to its etiology (e.g., painful diabetic neuropathy, trigeminal neuralgia, spinal cord injury) without regard for the presumed mechanism(s) underlying the specific symptoms. A combined etiologic/mechanistic classification might improve neuropathic pain management. The treatment of neuropathic pain is largely empirical, often relying heavily on data from small, generally poorly-designed clinical trials or anecdotal evidence. Consequently, diverse treatments are used, including non-invasive drug therapies (antidepressants, antiepileptic drugs and membrane stabilizing drugs), invasive therapies (nerve blocks, ablative surgery), and alternative therapies (e.g., acupuncture). This article reviews the current and historical practices in the diagnosis and treatment of neuropathic pain, and focuses on the USA, Europe and Japan.