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Background and objective: In previous studies, data deriving from Google Trends showed promising correlation with disease incidence trends assessed with public health control systems. The aim of this work is to use search engine query data to investigate seasonal dynamics in Guillain-Barré syndrome (GBS) in the USA. Methods: Average Google monthly search volumes for GBS from 2008 to 2017 were analysed for the USA overall and on regional base with generalized estimating equation models. Association with monthly historical temperature variations was tested. Results: Monthly search volume for GBS displayed the greatest positive anomaly for October, clustering with September and November. Region-wide analysis confirmed this pattern and showed secondary spring (Feb/Apr) subpeaks in Pacific and Midwest. Association of GBS search volume with month-to-month temperature variations showed J-shaped relationship, with the highest peak occurring in months with greatest temperature falls, and subpeak in months with sharpest temperature rises. Conclusions: This study represents the first approach in investigating digital epidemiology of GBS and establishing possible links with traditional epidemiology. Cold season GBS peak has been observed by some traditional studies; hypothetical pathogenic relationship with infectious antecedents is supported from finding GBS peaks clustering with greatest temperature change. Further studies are needed to compare these findings to traditional public health approaches.

Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is a potentially fatal autoimmune disease, characterized by autoantibody-mediated neurotransmission impairment in multiple brain locations. The course of this condition often comprises altered mental status, autonomic dysfunctions, refractory seizures and hyperkinetic movement disorders. Available disease-modifying therapies include corticosteroids, i.v. immunoglobulins, plasma exchange, rituximab and cyclophosphamide. In a subgroup of patients not responding to B-cell depletion, bortezomib, a proteasome inhibitor, has shown promising evidence of efficacy. The time course of recovery from acute phase may be very slow (weeks/months), and only few data are available in literature about the concurrent management of encephalitis-associated movement disorders. We report a case of severe anti-NMDAR encephalitis in a 29-year-old woman, not responsive to first- and second-line treatments, with persistent involuntary motor manifestations. Starting three months after symptom onset, four cycles of bortezomib have been administered; subsequently we observed a progressive improvement of neurological status. Meanwhile, motor manifestations were controlled after the administration of tramadol, a non-competitive NMDA receptor antagonist.

Social media have become a common way for people to express their personal viewpoints, including sentiments about health topics. We present the results of an opinion mining analysis on vaccination performed on Twitter from September 2016 to August 2017 in Italy. Vaccine-related tweets were automatically classified as against, in favor or neutral in respect of the vaccination topic by means of supervised machine-learning techniques. During this period, we found an increasing trend in the number of tweets on this topic. According to the overall analysis by category, 60% of tweets were classified as neutral, 23% against vaccination, and 17% in favor of vaccination. Vaccine-related events appeared able to influence the number and the opinion polarity of tweets. In particular, the approval of the decree introducing mandatory immunization for selected childhood diseases produced a prominent effect in the social discussion in terms of number of tweets. Opinion mining analysis based on Twitter showed to be a potentially useful and timely sentinel system to assess the orientation of public opinion toward vaccination and, in future, it may effectively contribute to the development of appropriate communication and information strategies.

Early recognition and treatment of autoimmune encephalitis (AE) are crucial for patients, but diagnosis is often difficult and time-consuming. For this purpose, a syndrome-based diagnostic approach was published by Graus et al. (Lancet Neurol 15:391–404, 2016), but very little is known in the literature about its application in clinical practice. Our aims are to test the feasibility of such approach in a real-world single-centre setting and to analyse the most relevant factors in criteria fulfilment. We retrospectively applied these criteria to our cohort of patients discharged from our hospital with diagnosis of autoimmune encephalitis (n = 33, 58% antibody-positive). All the subjects fulfilled criteria for possible AE (pAE), with EEG and MRI playing a central role in diagnosis, while CSF was useful mainly to rule out other conditions. Three patients respected criteria for probable anti-NMDA-R encephalitis (pNMDA). Definite anti-NMDAR encephalitis was diagnosed in 4 patients with detection of the autoantibody but, surprisingly, none of these subjects had fulfilled criteria for pNMDA. 18 patients were diagnosed with definite limbic AE (15 patients were antibody-positive, three antibody-negative). Need for MRI bilateral involvement in antibody-negative limbic AE limited diagnosis. One patient fulfilled criteria for probable antibody-negative AE, while ten patients remained classified as pAE. From our retrospective analysis, some suggestions for a better definition of the criteria may emerge. Larger studies on prospective cohorts may be more helpful to explore possible important issues.

Early detection of neuromyelitis optica spectrum disorders (NMOSD), especially after optic neuritis, a presenting manifestation commonly observed also in multiple sclerosis (MS), is crucial for timely treatment and prognosis. Integrated visual pathway assessment with optical coherence tomography (OCT) and visual evoked potentials (VEP) may help in this task, showing in vivo different pathophysiological backgrounds. We evaluated combined VEP and OCT in a cross-sectional, single-centre study assessing 50 consecutive NMOSD patients, 57 MS patients and 52 healthy controls. After optic neuritis, VEP were more frequently absent in NMOSD compared to MS; most NMOSD eyes with recordable VEP showed prolonged latency, but extreme latency delays were less common than in MS. OCT showed predominantly axonal involvement in NMOSD, with 88% eyes (95% CI: 69–97%) displaying retinal nerve fibre layer thickness

Background: Neuroretinal atrophy is associated with whole-brain atrophy and disease activity in multiple sclerosis (MS). Recent findings support that subclinical visual pathway involvement might also occur in neuromyelitis optica spectrum disorders (NMOSDs). Objective: The objective of this study is to assess retinal thinning in MS and NMOSD and its association with disease activity. Methods: In total, 27 NMOSD and 54 propensity-score-matched MS patients underwent optical coherence tomography, visual acuity, and visual-evoked potentials at 2.4 years apart, in addition to routine clinical and magnetic resonance imaging (MRI) assessment. We excluded eyes with acute optic neuritis. Results: In NMOSD, we detected peripapillary retinal nerve fiber layer (pRNFL) thinning in patients with disease activity during follow-up (−0.494 µm/year), but not in stable patients (−0.012 µm/year). Macular ganglion cell-inner plexiform layer (GCIPL) thinning occurred instead in all patients (−0.279 µm/year). Relapsing–remitting multiple sclerosis (RRMS) meeting NEDA-3 criteria had no pRNFL or GCIPL thinning during follow-up. Active-disease RRMS and progressive MS, both active and stable, displayed pRNFL (−0.724, −0.586, −0.556 µm/year, respectively) and GCIPL loss. Conclusion: In MS, neuroretinal atrophy was associated with disease activity but occurred in progressive MS even when achieving NEDA-3 criteria. In NMOSD, pRNFL thinning was associated with non-ocular relapses due to a spreading of inflammatory activity. GCIPL thinning was found in all patients, supporting a primary retinal pathology targeting AQP4-rich structures.