Headache and Status Epilepticus in the Postpartum Period; Posterior Reversible Encephalopathy Syndrome or Cerebral Venous Thrombosis?

We report a case of a young woman, with a history of a miscarriage and a molar pregnancy, who developed headache and status epilepticus in postpartum day three. Posterior reversible encephalopathy syndrome (PRES) and cerebral venous and sinus thrombosis (CVST) can present with identical clinical picture; however, the imaging findings can help the clinician to make the correct diagnosis and initiate the appropriate treatment. Both PRES and CVST are medical emergencies and fully reversible entities especially when treatment initiation is immediate

Machine Learning in Pain Medicine:An Up-To-Date Systematic Review

Introduction: Pain is the unpleasant sensation and emotional experience that leads to poor quality of life for millions of people worldwide. Considering the complexity in understanding the principles of pain and its significant impact on individuals and society, research focuses to deliver innovative pain relief methods and techniques. This review explores the clinical uses of machine learning (ML) for the diagnosis, classification, and management of pain. Methods: A systematic review of the current literature was conducted using the PubMed database library. Results: Twenty-six papers related to pain and ML research were included. Most of the studies used ML for effectively classifying the patients’ level of pain, followed by use of ML for the prediction of manifestation of pain and for pain management. A less common reason for performing ML analysis was for the diagnosis of pain. The different approaches are thoroughly discussed. Conclusion: ML is increasingly used in pain medicine and appears to be more effective compared to traditional statistical approaches in the diagnosis, classification, and management of pain

Burnout in Medical Residents: A Study Based on the Job Demands-Resources Model

Purpose. Burnout is a prolonged response to chronic emotional and interpersonal stressors on the job. The purpose of our cross-sectional study was to estimate the burnout rates among medical residents in the largest Greek hospital in 2012 and identify factors associated with it, based on the job demands-resources model (JD-R). Method. Job demands were examined via a 17-item questionnaire assessing 4 characteristics (emotional demands, intellectual demands, workload, and home-work demands’ interface) and job resources were measured via a 14-item questionnaire assessing 4 characteristics (autonomy, opportunities for professional development, support from colleagues, and supervisor’s support). The Maslach Burnout Inventory (MBI) was used to measure burnout. Results. Of the 290 eligible residents, 90.7% responded. In total 14.4% of the residents were found to experience burnout. Multiple logistic regression analysis revealed that each increased point in the JD-R questionnaire score regarding home-work interface was associated with an increase in the odds of burnout by 25.5%. Conversely, each increased point for autonomy, opportunities in professional development, and each extra resident per specialist were associated with a decrease in the odds of burnout by 37.1%, 39.4%, and 59.0%, respectively. Conclusions. Burnout among medical residents is associated with home-work interface, autonomy, professional development, and resident to specialist ratio

Non-Pharmacological Management of Painful Peripheral Neuropathies: A Systematic Review.

Peripheral neuropathic pain (PNP) is defined as the neuropathic pain that arises either acutely or in the chronic phase of a lesion or disease affecting the peripheral nervous system. PNP is associated with a remarkable disease burden, and there is an increasing demand for new therapies to be used in isolation or combination with currently available treatments. The aim of this systematic review was to evaluate the current evidence, derived from randomized controlled trials (RCTs) that assess non-pharmacological interventions for the treatment of PNP.After a systematic Medline search, we identified 18 papers eligible to be included.The currently best available evidence (level II of evidence) exist for painful diabetic peripheral neuropathy. In particular, spinal cord stimulation as adjuvant to conventional medical treatment can be effectively used for the management of patients with refractory pain. Similarly, adjuvant repetitive transcranial magnetic stimulation of the motor cortex is effective in reducing the overall pain intensity, whereas adjuvant static magnetic field therapy can lead to a significant decrease in exercise-induced pain. Weaker evidence (level III of evidence) exists for the use of acupuncture as a monotherapy and neurofeedback, either as an add-on or a monotherapy approach, for treatment of painful chemotherapy-induced peripheral neuropathy CONCLUSIONS: Future RCTs should be conducted to shed more light in the use of non-pharmacological approaches in patients with PNP

Transglutaminase 6 antibodies in gluten neuropathy

BACKGROUND: TG6 antibodies have been shown to be a marker of gluten ataxia but their presence in the context of other neurological manifestations of gluten sensitivity has not been explored. We investigated the presence of TG6 antibodies in gluten neuropathy (GN), defined as as an otherwise idiopathic peripheral neuropathy associated with serological markers of gluten sensitivity (one or more of antigliadin IgG and/or IgA, endomysial and transglutaminase-2 antibodies). METHODS: This was a cross-sectional study conducted at the Sheffield Institute of Gluten Related Diseases, Royal Hallamshire Hospital, Sheffield, UK. Blood samples were collected whilst the patients were on a gluten containing diet. Duodenal biopsies were performed to establish the presence of enteropathy. RESULTS: Twenty-eight patients were recruited (mean age 62.5±13.7 years). Fifteen (53.6%) had sensory ganglionopathy, 12 (42.9%) had symmetrical axonal neuropathy and 1 had mononeuritis multiplex. The prevalence of TG6 antibodies was 14 of 28 (50%) compared to 4% in the healthy population. TG6 antibodies were found in 5/15 (33.3%) patients with sensory ganglionopathy and in 8/12 (66.7%) with symmetrical axonal neuropathy. Twenty-four patients underwent duodenal biopsy 11 (45.8%) of which had enteropathy. The prevalence of TG6 was not significantly different when comparing those with or without enteropathy. CONCLUSIONS: We found a high prevalence of antibodies against TG6 in patients with GN. This suggests that TG6 involvement is not confined to the central nervous system. The role of transglutaminase 6 in peripheral nerve function remains to be determined but TG6 antibodies may be helpful in the diagnosis of GN

Increased oxidative stress as a risk factor in chronic idiopathic axonal polyneuropathy

Chronic idiopathic axonal polyneuropathy (CIAP) is a disorder with insidious onset and slow progression, where no etiology is identified despite appropriate investigations. We aimed to investigate the role of oxidative stress as a risk factor for the pathogenesis of CIAP. Sera of patients with CIAP were tested for protein carbonyl (PC) and 8-hydroxydeoxyguanosine (8H). As a control group, we recruited patients with gluten neuropathy. Twenty-one patients with CIAP and 21 controls were recruited. The two groups did not differ significantly regarding demographics or clinical characteristics (i.e., neuropathy type or disease severity). After adjusting for gender, having CIAP was positively correlated with both the 8H titer (standardized beta coefficient 0.349, p = 0.013) and the PC titer (standardized beta coefficient 0.469, p = 0.001). Oxidative stress appears to be increased in CIAP and might have a role in the pathogenesis of the disease

EEG recordings as biomarkers of pain perception: where do we stand and where to go?

Introduction: The universality and complexity of pain, which is highly prevalent, yield its significance to both patients and researchers. Developing a non-invasive tool that can objectively measure pain is of the utmost importance for clinical and research purposes. Traditionally electroencephalography (EEG) has been mostly used in epilepsy; however, over the recent years EEG has become an important non-invasive clinical tool that has helped increase our understanding of brain network complexities and for the identification of areas of dysfunction. This review aimed to investigate the role of EEG recordings as potential biomarkers of pain perception. Methods: A systematic search of the PubMed database led to the identification of 938 papers, of which 919 were excluded as a result of not meeting the eligibility criteria, and one article was identified through screening of the reference lists of the 19 eligible studies. Ultimately, 20 papers were included in this systematic review. Results: Changes of the cortical activation have potential, though the described changes are not always consistent. The most consistent finding is the increase in the delta and gamma power activity. Only a limited number of studies have looked into brain networks encoding pain perception. Conclusion: Although no robust EEG biomarkers of pain perception have been identified yet, EEG has potential and future research should be attempted. Designing strong research protocols, controlling for potential risk of biases, as well as investigating brain networks rather than isolated cortical changes will be crucial in this attempt

Using interictal seizure-free EEG data to recognise patients with epilepsy based on machine learning of brain functional connectivity

Most seizures in adults with epilepsy occur rather infrequently and as a result, the interictal EEG plays a crucial role in the diagnosis and classification of epilepsy. However, empirical interpretation, of a first EEG in adult patients, has a very low sensitivity ranging between 29-55%. Useful EEG information remains buried within the signals in seizure-free EEG epochs, far beyond the observational capabilities of any specialised physician in this field. Unlike most of the existing works focusing on either seizure data or single-variate method, we introduce a multi-variate method to characterise sensor level brain functional connectivity from interictal EEG data to identify patients with generalised epilepsy. A total of 9 connectivity features based on 5 different measures in time, frequency and time frequency domains have been tested. The solution has been validated by the K-Nearest Neighbour algorithm, classifying an epilepsy group (EG) vs healthy controls (HC) and subsequently with another cohort of patients characterised by non-epileptic attacks (NEAD), a psychogenic type of disorder. A high classification accuracy (97%) was achieved for EG vs HC while revealing significant spatio temporal deficits in the frontocentral areas in the beta frequency band. For EG vs NEAD, the classification accuracy was only about 73%, which might be a reflection of the well-described coexistence of NEAD with epileptic attacks. Our work demonstrates that seizure-free interictal EEG data can be used to accurately classify patients with generalised epilepsy from HC and that more systematic work is required in this direction aiming to produce a clinically useful diagnostic method