Automated characterization and detection of fibromyalgia using slow wave sleep EEG signals with glucose pattern and D'hondt pooling technique.

Fibromyalgia is a soft tissue rheumatism with significant qualitative and quantitative impact on sleep macro and micro architecture. The primary objective of this study is to analyze and identify automatically healthy individuals and those with fibromyalgia using sleep electroencephalography (EEG) signals. The study focused on the automatic detection and interpretation of EEG signals obtained from fibromyalgia patients. In this work, the sleep EEG signals are divided into 15-s and a total of 5358 (3411 healthy control and 1947 fibromyalgia) EEG segments are obtained from 16 fibromyalgia and 16 normal subjects. Our developed model has advanced multilevel feature extraction architecture and hence, we used a new feature extractor called GluPat, inspired by the glucose chemical, with a new pooling approach inspired by the D'hondt selection system. Furthermore, our proposed method incorporated feature selection techniques using iterative neighborhood component analysis and iterative Chi2 methods. These selection mechanisms enabled the identification of discriminative features for accurate classification. In the classification phase, we employed a support vector machine and k-nearest neighbor algorithms to classify the EEG signals with leave-one-record-out (LORO) and tenfold cross-validation (CV) techniques. All results are calculated channel-wise and iterative majority voting is used to obtain generalized results. The best results were determined using the greedy algorithm. The developed model achieved a detection accuracy of 100% and 91.83% with a tenfold and LORO CV strategies, respectively using sleep stage (2 + 3) EEG signals. Our generated model is simple and has linear time complexity.

Stimulus-Induced Motor Afterdischarges in CASPR2 (Contactin-Associated Protein-Like 2)-Positive Peripheral Nerve Hyperexcitability Syndrome.

Peripheral nerve hyperexcitability is an uncommon but treatable condition in neurology. Voltage-gated potassium channelopathies, especially contactin-associated protein-like 2 (CASPR2) antibody, are commonly implicated. We present the case of a 16-year-old boy with tremulousness of both feet and twitching of muscles all over the body for three months. Examination revealed irregular, arrhythmic, small-amplitude twitching movements of the toes along with fasciculations in both thighs. Nerve conduction studies were within normal limits. F-wave studies showed a prolonged polyphasic large-amplitude discharge following the compound muscle action potential and obscuring the F waves. Electromyography showed extensive myokymic discharges. The serum autoimmune antibody profile showed strong positivity for CASPR2. He started lacosamide as a symptomatic treatment. In view of the good symptomatic response, further immunomodulation was deferred and he remains on follow-up. We present this case to highlight the role of motor afterdischarges as a diagnostic clue to peripheral nerve hyperexcitability and to review the literature on this interesting finding.

Study Protocol: IMPETUS: Implementing a Uniform Stroke Care Pathway in Medical Colleges of India: IMPETUS Stroke.

Introduction: In India, a national program for stroke (national programme for the control of cardiovascular diseases, diabetes, cancer, and stroke) and stroke management guidelines exist. Its successful implementation would need an organized system of stroke care in practice. However, many challenges exist including lack of awareness, prehospital notification systems, stroke ready hospitals, infrastructural weaknesses, and rehabilitation. We present here a protocol to investigate the feasibility and fidelity of implementing a uniform stroke care pathway in medical colleges of India. Methods and Analysis: This is a multicentric, prospective, multiphase, mixed-method, quasi-experimental implementation study intended to examine the changes in a select set of stroke care-related indicators over time within the sites exposed to the same implementation strategy. We shall conduct process evaluation of the implementation process as well as evaluate the effect of the implementation strategy using the interrupted time series design. During implementation phase, education and training about standard stroke care pathway will be provided to all stakeholders of implementing sites. Patient-level outcomes in the form of modified Rankin Scale score will be collected for all consecutive patients throughout the study. Process evaluation outcomes will be collected and reported in the form of various stroke care indicators. We will report level and trend changes in various indicators during the three study phases. Discussion: Acute stroke requires timely detection, management, and secondary prevention. Implementation of the uniform stroke care pathway is a unique opportunity to promote the requirements of homogenous stroke care in medical colleges of India.

Mobile application as a complementary tool for differential diagnosis in Neuro-ophthalmology: A multicenter cross-sectional study.

Purpose: Drawing differential diagnoses to a Neuro-ophthalmology clinical scenario is a difficult task for a neurology trainee. The authors conducted a study to determine if a mobile application specialized in suggesting differential diagnoses from clinical scenarios can complement clinical reasoning of a neurologist in training. Methods: A cross-sectional multicenter study was conducted to compare the accuracy of neurology residents versus a mobile medical app (Neurology Dx) in drawing a comprehensive list of differential diagnoses from Neuro-ophthalmology clinical vignettes. The differentials generated by residents and the App were compared with the Gold standard differential diagnoses adjudicated by experts. The prespecified primary outcome was the proportion of correctly identified high likely gold standard differential diagnosis by residents and App. Results: Neurology residents (n = 100) attempted 1500 Neuro-ophthalmology clinical vignettes. Frequency of correctly identified high likely differential diagnosis by residents was 19.42% versus 53.71% by the App (P < 0.0001). The first listed differential diagnosis by the residents matched with that of the first differential diagnosis adjudicated by experts (gold standard differential diagnosis) with a frequency of 26.5% versus 28.3% by the App, whereas the combined output of residents and App scored a frequency of 41.2% in identifying the first gold standard differential correctly. The residents correctly identified the first three and first five gold standard differential diagnosis with a frequency of 17.83% and 19.2%, respectively, as against 22.26% and 30.39% (P < 0.0001) by the App. Conclusion: A ruled based app in Neuro-ophthalmology has the potential to complement a neurology resident in drawing a comprehensive list of differential diagnoses.

Characterization of fibromyalgia using sleep EEG signals with nonlinear dynamical features.

Fibromyalgia is an intense musculoskeletal pain causing sleep, fatigue, and mood problems. Sleep studies have suggested that 70%-80% of fibromyalgia patients complain of non-restorative sleep. The abnormalities in sleep have been implicated as both a cause and effect of the disease. In this paper, the electroencephalogram (EEG) signals of sleep stages 2 and 3 are used to classify the normal and fibromyalgia classes automatically. We have used various nonlinear parameters, namely sample entropy (SampEn), fractal dimension (FD), higher order spectra (HOS), largest Lyapunov exponent (LLE), Kolmogorov complexity (KC), Hurst exponent (HE), energy, and power in various frequency bands from the EEG signals. Then these features are subjected to Student's t-test to select the clinically significant features, and are classified using the support vector machine (SVM) classifier. Our proposed method can classify normal and fibromyalgia subjects using the stage 2 sleep EEG signals with an accuracy of 96.15%, sensitivity and specificity of 96.88% and 95.65%, respectively. Performance of the developed system can be improved further by adding more subjects in each class, and can be employed for clinical use.

Clinical profile of patients with nascent alcohol related seizures.

AIM: The aim of this study is to characterize the clinical profile of patients with alcohol related seizures (ARS) and to identify the prevalence of idiopathic generalized epilepsy (IGE) in the same. MATERIALS AND METHODS: 100 consecutive male patients presenting to a tertiary care center in South India with new onset ARS were analyzed with alcohol use disorders identification test (AUDIT) score. All underwent 19 channel digital scalp electroencephalography (EEG) and at least computed tomography (CT) scan. RESULTS: A total of 27 patients (27%) who had cortical atrophy on CT had a mean duration of alcohol intake of 23.62 years compared with 14.55 years in patients with no cortical atrophy (P < 0.001). Twenty-two patients (22%) had clustering in the current episode of whom 18 had cortical atrophy. Nearly, 88% patients had generalized tonic clonic seizures while 12% who had partial seizures underwent magnetic resonance imaging (MRI), which identified frontal focal cortical dysplasia in one. Mean lifetime duration of alcohol intake in patients presenting with seizures within 6 hours (6H-gp) of intake of alcohol was significantly lower (P = 0.029). One patient in the 6H-gp with no withdrawal symptoms had EEG evidence for IGE and had a lower AUDIT score compared with the rest. CONCLUSION: CT evidence of cortical atrophy is related to the duration of alcohol intake and portends an increased risk for clustering. Partial seizures can be a presenting feature of ARS and those patients may benefit from MRI to identify underlying symptomatic localization related epilepsy (8.3% of partial seizures). IGE is more likely in patients presenting with ARS within first 6 hours especially if they do not have alcohol withdrawal symptoms and scalp EEG is helpful to identify this small subgroup (~1%) who may require long-term anti-epileptic medication.

Recurrent meningitis due to epidermoid.

Aseptic meningitis is characterized by noninfective serous inflammation of the meninges. It can occur in a recurrent fashion when associated with dermoid and epidermoid cysts due to rupture of cyst contents into subarachnoid space resulting in aseptic chemical meningitis. Bacterial meningitis in association with these tumors is commonly related to a coexisting dermal sinus tract and the most common organism is Staphylococcus aureus.