Search

Background: In patients with Multiple Sclerosis (pwMS) disease-modifying therapies (DMTs) are known to affect immune response to antigens and possibly to SARS-CoV2 vaccine. Therefore, post-vaccination serological assessments are needed to evaluate the effect of the vaccine on SARS-CoV-2 antibody response. Methods: We designed a prospective multicenter cohort study enrolling pwMS who were scheduled for SARS-Cov-2 vaccination with mRNA vaccines (BNT162b2, Pfizer/BioNTech, Inc or mRNA-1273, Moderna Tx, Inc). A blood collection for the measure of SARS-CoV-2 antibody before the first vaccine dose and 4 weeks after the second dose was planned, with a centralized serological assessment (electrochemiluminescence immunoassay, ECLIA, Roche Diagnostics). Findings: 780 pwMS (76% BNT162b2 and 24% mRNA-1273) had pre- and 4-week post-vaccination blood assessments. 87 (11·2%) were untreated, 154 (19·7%) on ocrelizumab, 25 (3·2%) on rituximab, 85 (10·9%) on fingolimod, 25 (3·2%) on cladribine and 404 (51·7%) on other DMTs. 677 patients (86·8%) had detectable post-vaccination SARS-CoV-2 antibodies. At multivariate analysis, the antibody levels of patients on ocrelizumab (178-fold decrease, p

Objective: The present study was undertaken to investigate whether a synoptic parameter of quantitative EEG (qEEG), such as the power spectral profile, may be used as a simple marker to stage Alzheimer's disease (AD) in the clinical setting. Methods: To this purpose, the qEEG spectral profile was examined in 48 patients (mean age: 73 years) with probable (NINCDS-ADRDA criteria) AD, who were divided into 4 groups, according to the Global Deterioration Scale (GDS; score: 3–6). The spectral profile of each patient was expressed by the relative power of seven frequency bands (2–3.5, 4–5.5, 6–7.5, 8–9.5, 10–11.5, 12–13.5, 14–22.5 Hz). Mean values in each of the four GDS groups as well as in a control group of 18 healthy elderly subjects underwent multivariate analysis of variance. Results: A normally shaped but shifted-to-the left spectral profile was found in GDS 3 group, whereas a reduced background rhythm with various increase in slow activity power characterized both GDS 4 and 5 groups. Finally, an ‘exponential asymptotic' profile with the highest power in the lowest frequencies was the hallmark of GDS 6 group. Overall, the 4–5.5 Hz and the 10–11.5 Hz band powers showed the highest statistical significance in differentiating the patient groups between one another and from controls ( P Conclusions: These data show that spectral profile is a very simple parameter which can be used to stage the disease on a pathophysiological basis.

This prospective study was planned to assess whether quantitative EEG (qEEG) can give an estimate of the timing of achievement of three endpoints (loss of activities of daily living, incontinence, and death) in 72 consecutive patients (53 females, 19 males; mean age, 70.8) affected with probable Alzheimer's disease, as defined according to the NINCDS-ADRDA criteria. Power-weighted, log-transformed relative values of the four conventional EEG bands were considered in a central-posterior temporal region for each hemisphere. The hypothesis was tested by the lifereg procedure of the Statistical Analysis System package (first significance level accepted, P < or = 0.01). Because patients were in different stages of the disease, the statistical analysis was performed in the entire group as well as in the subgroup of 41 patients (mean age, 69.6) with mild dementia (scoring 3 or 4 on the global deterioration scale). In the whole group, the loss of activities of daily living was predicted by delta power in either side (P = 0.01), incontinence was predicted by alpha power in the right side (P < 0.01), whereas the statistical significance was not reached for death (P < 0.05). In the subgroup of mild demented patients, the loss of activities of daily living was predicted by delta power in the left side (P = 0.01), incontinence by both delta (P < 0.01) and alpha (P < 0.001) power in the right side, and death was not significantly predicted (P = 0.08). Quantitative EEG is a low-cost, discomfort-free technique which may be used to obtain information on the timing of disease evolution. The results showed in mild Alzheimer's disease appear especially interesting to attempt a prediction of the future time course of the disease from its beginning.