Since the coronavirus disease 2019 (COVID-19) pandemic began in 2020, several studies from various countries have described changes in the epidemiology of Guillain-Barr & eacute; syndrome (GBS); however, it remains unclear whether the incidence and clinical profiles were altered by the pandemic. This study aimed to elucidate the impact of the COVID-19 pandemic on the epidemiology and clinical profile of GBS in Japan. We conducted a nationwide survey on the incidence of GBS between 2017 and 2022, encompassing the pre-pandemic (2017-2019) and pandemic (2020-2022) periods. Questionnaires were sent to the neurology and paediatrics departments at hospitals throughout Japan. A primary questionnaire was used to estimate the number of patients and incidence, and a second questionnaire was administered to collect detailed clinical information. The annual number of newly diagnosed GBS cases and their incidence were estimated at 1885 [95% confidence interval (CI), 1766-2004] and 1.49 (95% CI, 1.40-1.58) per 100 000 population, respectively, during the pre-pandemic, 1603 (95% CI, 1463-1743) and 1.28 (95% CI, 1.17-1.39) per 100 000 population during the pandemic periods; the relative risk for GBS incidence during the pandemic period was 0.91 (95% CI, 0.83-0.99; 9% reduction). Detailed clinical profiles were available for 2623 patients (1420 during the pre-pandemic period and 1203 during the pandemic period). Compared with patients in the pre-pandemic period, those diagnosed during the pandemic period were older (median age, 56 years versus 53 years; P = 0.02), had a higher proportion of cases without antecedent infectious episodes (38.2% versus 24.5%; P < 0.0001), longer time to reach nadir (median, 8 days versus 7 days; P = 0.0418) and higher frequency of the demyelinating subtype of GBS (37.8% versus 32.6%; P = 0.0068). No significant differences were observed in the outcomes at 6 months post-onset. The Japanese national registry data showed a markedly reduced number of Campylobacter-related enteritis cases following the pandemic. This study demonstrated a decrease in the overall incidence of GBS during the earlier phase of the COVID-19 pandemic in Japan. The increased number of GBS cases without infectious episodes or demyelinating subtypes during the pandemic period may be caused by reduced exposure to conventional infectious triggers of GBS, such as C. jejuni and increased asymptomatic COVID-19-related demyelinating GBS.
Objective Artificial intelligence (AI) classifies routine electroencephalograms (EEGs) with expert-level accuracy, but interpretation of long-term EEG monitoring (LTM) remains reliant on time-intensive visual review. We evaluated whether autoSCORE, a clinically approved implementation of SCORE-AI integrated into an EEG reader, achieves expert-level diagnostic accuracy for LTM interpretation and whether expert-supervised use reduces review time versus conventional analysis. Methods A fixed-and-frozen AI model was tested on an independent single-center dataset of 78 adult patient LTM recordings (52 normal, 26 abnormal), with epilepsy monitoring unit discharge diagnosis as the external reference standard. The AI model was benchmarked against two expert panels (three readers each); Panel 1 reviewed autoSCORE EEG detections (hybrid approach), and Panel 2 interpreted full recordings (conventional approach). Diagnostic accuracy and time to diagnostic decision were assessed for fully automated, hybrid, and conventional approaches. Interrater reliability (Gwet's AC1) was evaluated for hybrid and conventional interpretation. Results Interrater reliability was significantly higher for hybrid than conventional approach (AC1 = .81, 95% confidence interval [CI] = .73-.89 vs. AC1 = .43, 95% CI = .32-.53; p < .001). Review time was markedly reduced (median [interquartile range (IQR)] = 2.2 [.5-4.3] vs. 52.4 [33.2-62.9] min, mean [95% CI] = 2.9 [2.5-3.2] vs. 50.8 [46.5-55.2] min, p < .001), a 95.8% median reduction (IQR = 95.6-96.3). Diagnostic performance comparisons were adjusted for multiple comparisons using the Holm-Bonferroni procedure across all 63 tests. The hybrid approach showed significantly higher sensitivity than conventional interpretation (.88, 95% CI = .77-.97 vs. .69, 95% CI = .57-.81; adjusted p = .006). Its numerically higher diagnostic accuracy versus conventional interpretation (.75, 95% CI = .66-.83 vs. .68, 95% CI = .61-.74) was nonsignificant after correction (adjusted p > .99). Hybrid approach diagnostic accuracy was significantly greater than fully automated analysis (.75, 95% CI = .66-.83 vs. .55, 95% CI = .44-.65; adjusted p < .001). Significance Expert oversight of AI-assisted categorization of interictal epileptiform and nonepileptiform EEG abnormalities improves interrater reliability and efficiency, increases diagnostic sensitivity versus conventional interpretation, and increases diagnostic accuracy versus fully automated analysis in adult LTM.
Demyelination, the loss of the myelin sheath from around otherwise intact axons, occurs in several diseases, most notably multiple sclerosis (MS). Demyelinated axons that are not remyelinated are vulnerable to irreversible degeneration and therefore therapies that enhance remyelination have been sought. However, there remains a paucity of suitable outcome measures to assess their efficacy. MRI is a non-invasive imaging modality that is used both preclinically and clinically for the assessment of anatomy and tissue function. Here we describe an MRI technique for following the differentiation of oligodendrocyte progenitor cells (OPCs) into oligodendrocytes during the spontaneous regenerative process of remyelination in vivo.OPCs were transduced in situ with a lentiviral vector expressing an organic anion transporting polypeptide (OATP1A1) under the control of the differentiation-specific myelin basic protein (MBP) promoter. OATP1A1 mediates cell uptake of a gadolinium-based MRI contrast agent (Primovist), allowing detection of the cells in T1-weighted MR images. Uptake of the contrast agent is restricted to MBP-expressing cells, which is most highly expressed during myelin sheath formation, thereby allowing progenitor-mediated, and potentially oligodendrocyte-mediated, remyelination to be monitored non-invasively in vivo using MRI.These findings provide the foundation for the development of direct methods for assessing the efficacy of pro-remyelination therapies. Brechb & uuml;hl et al. present a new MRI technique for tracking the differentiation of oligodendrocyte progenitor cells into oligodendrocytes during remyelination in vivo. This approach lays the foundation for non-invasive evaluation of pro-remyelination therapies for multiple sclerosis and other demyelinating disorders.
