Vagus nerve stimulation for treatment-resistant mood disorders: a long-term naturalistic study

BACKGROUND: Limited therapeutic options are available for patients with treatment-refractory major depression who do not respond to routinely available therapies. Vagus nerve stimulation showed adjunctive antidepressant effect in chronic treatment resistant depression, even though available studies rarely exceed 2-year follow up. We report a naturalistic 5-year follow up of five patients who received VNS implant for resistant depression (3 patients with major depressive disorder and 2 with bipolar disorder). METHODS: Response was defined as a reduction of the 17-item HDRS total score 6550% with respect to baseline, remission as a score 647. RESULTS: Response and remission rates were both 40% (2/5) after 1 year, and 60% (3/5) at 5 years. Two patients withdrew from the study because of side effects or inefficacy of stimulation. CONCLUSIONS: Our case series showed that long-term VNS may be effective in reducing severity of depression in a small but significant minority of patients, although two patients had stimulation terminated because of adverse effects and/or refusal to continue the study

Nosographic classification of mood disorders: from symptoms to diagnosis and treatment

Mood disorders represent a main health concern, due to their high prevalence in the general population and because they are related to a severe worsening of quality of life and psychosocial functioning of those who are affected. Because of the importance of such diseases, that, according to WHO, might become the major cause of morbidity by 2020, an efficacious, targeted and precise approach is essential in everyday clinical practice. This article reviews the methods of diagnostic approach, with the aim of describing the different phases of nosographic classification of mood disorders and their meaning. In particular, the most reliable classification distinguishes between unipolar (major depressive disorder) and bipolar (type I and II) disorders: the right differential diagnosis is important because there are great differences in the optimal management of these conditions (antidepressants vs. mood stabilizers) and diagnostic errors can potentially worsen the patient's prognosis. In conclusion, the right nosographic classification allows the right therapeutic and prognostic approach. This may result in higher rates of remission and response, thus improving patient's quality of life and overall wellness.http://dx.doi.org/10.7175/rhc.v3i3.20

Positivity to p-ANCA in patients with status epilepticus

BACKGROUND: Status epilepticus (SE) may occur in the setting of several internal or neurologic diseases. Anti-neutrophilic cytoplasmic antibodies (ANCA) are a group of Ig that may be observed in patients with different autoimmune disorders but are particularly associated with systemic vasculitis named ANCA-associated-vasculities (AAV). We herein report 3 patients with SE and positivity to p-ANCA. CASE PRESENTATION: One patient had a catastrophic evolution and died 5 months after disease onset. The other two patients had a good outcome and remained seizure-free at 30 months and 5 years of follow-up respectively. CONCLUSION: This report highlights the importance of considering ANCA dosage in patients with SE of unclear origin

Severe obsessive-compulsive disorder (OCD): socio-demographic and clinical features

Aim: the aim of the study is to evaluate the socio-demographic and clinical features with prognostic value in predicting evolution in severe OCD.Materials and methods: patients with a main diagnosis of OCD were recruited according to DSM-IV criteria. Socio-demographic and clinical features were assessed by mean of a semi-structured interview and clinical rating scales (Y-BOCS, HAM-A, HAM-D and SCID-II). Two subgroups were compared according to the severity of symptoms (severe vs mild-moderate).Results: the total sample was made up of 450 OCD subjects aged 34.5±12.1, with a mean age of onset 22.3±9.1; 215 subjects (47.8%) were females. Patients with severe OCD (Y-BOCS ≥ 32) showed a more insidious onset and a more chronic course compared to patients with mild-moderate symptoms. Other predictors of increased OCD severity were washing and hoarding compulsions. Lastly, the severity of the obsessive-compulsive condition was higher when it was associated either with mood disorders or with Axis II disorders (particularly Cluster A).Discussion: our study shows a correlation between severe OCD and severity predictors such as functional impairment and mood disorders. Furthermore washing and hoarding symptoms, lifetime comorbity with mood disorders and Cluster A personality disorders seem to predict OCD severity

Cerebrospinal Fluid Pressure-Related Features in Chronic Headache: A Prospective Study and Potential Diagnostic Implications

Objective: To identify the pressure-related features of isolated cerebrospinal fluid hypertension (ICH) in order to differentiate headache sufferers with ICH from those with primary headache disorder.Methods: In this prospective study, patients with refractory chronic headaches and suspected of having cerebrospinal fluid-pressure elevation without papilledema or sixth nerve palsy, together with controls, underwent 1-h lumbar cerebrospinal fluid pressure monitoring via a spinal puncture needle.Results: We recruited 148 consecutive headache patients and 16 controls. Lumbar cerebrospinal fluid pressure monitoring showed high pressure and abnormal pressure pulsations in 93 (63 %) patients with headache: 37 of these patients with the most abnormal pressure parameters (opening pressure above 250 mm H2O, mean pressure 301 mm H2O, mean peak pressure 398 mm H2O, and severe abnormal pressure pulsations) had the most severe headaches and associated symptoms (nocturnal headache, postural headache, transient visual obscuration); 56 patients with the less abnormal pressure parameters (opening pressure between 200 and 250 mm H2O, mean pressure 228 mm H2O, mean peak pressure 316 mm H2O, and abnormal pressure pulsations) had less severe headaches and associated symptoms.Conclusions: Nocturnal and postural headache, and abnormal pressure pulsations are the more common pressure-related features of ICH in patients with chronic headache. Abnormal pressure pulsations may be considered a marker of ICH in chronic headache

An Exploratory Study of Field Failures

Field failures, that is, failures caused by faults that escape the testing phase leading to failures in the field, are unavoidable. Improving verification and validation activities before deployment can identify and timely remove many but not all faults, and users may still experience a number of annoying problems while using their software systems. This paper investigates the nature of field failures, to understand to what extent further improving in-house verification and validation activities can reduce the number of failures in the field, and frames the need of new approaches that operate in the field. We report the results of the analysis of the bug reports of five applications belonging to three different ecosystems, propose a taxonomy of field failures, and discuss the reasons why failures belonging to the identified classes cannot be detected at design time but shall be addressed at runtime. We observe that many faults (70%) are intrinsically hard to detect at design-time

A Machine Learning Approach Involving Functional Connectivity Features to Classify Rest-EEG Psychogenic Non-Epileptic Seizures from Healthy Controls

Until now, clinicians are not able to evaluate the Psychogenic Non-Epileptic Seizures (PNES) from the rest-electroencephalography (EEG) readout. No EEG marker can help differentiate PNES cases from healthy subjects. In this paper, we have investigated the power spectrum density (PSD), in resting-state EEGs, to evaluate the abnormalities in PNES affected brains. Additionally, we have used functional connectivity tools, such as phase lag index (PLI), and graph-derived metrics to better observe the integration of distributed information of regular and synchronized multi-scale communication within and across inter-regional brain areas. We proved the utility of our method after enrolling a cohort study of 20 age- and gender-matched PNES and 19 healthy control (HC) subjects. In this work, three classification models, namely support vector machine (SVM), linear discriminant analysis (LDA), and Multilayer perceptron (MLP), have been employed to model the relationship between the functional connectivity features (rest-HC versus rest-PNES). The best performance for the discrimination of participants was obtained using the MLP classifier, reporting a precision of 85.73%, a recall of 86.57%, an F1-score of 78.98%, and, finally, an accuracy of 91.02%. In conclusion, our results hypothesized two main aspects. The first is an intrinsic organization of functional brain networks that reflects a dysfunctional level of integration across brain regions, which can provide new insights into the pathophysiological mechanisms of PNES. The second is that functional connectivity features and MLP could be a promising method to classify rest-EEG data of PNES form healthy controls subjects