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Background and purpose: The aim was to investigate the neurological complications associated with coronavirus disease 19 (COVID‐19) during the 2022 Omicron wave. Methods and analysis: The medical records of a cohort of people admitted to neurological wards of three participating tertiary centres in Sichuan from 12 December 2022 to 12 January 2023 were reviewed. Demographics and clinical data were obtained and analysed with an interest in COVID‐19‐related new‐onset or worse neurological symptoms. The current data were also compared in two centres with similar data from the same period 12 months earlier. Results: In all, 790 people were enrolled, of whom 436 were positive for COVID‐19. Ninety‐nine had new onset COVID‐related neurological problems, or their known neurological condition deteriorated during the wave. There was a significant difference in demographics from the findings amongst admissions 12 months earlier as there was an increase in the average age, the incidence of encephalitis and encephalopathy, and mortality rates. One hundred and one received COVID‐specific antivirals, intravenous glucocorticoids and intravenous immunoglobulin therapy. No differences were seen between these and those who did not use them. Conclusion: New‐onset neurological conditions, particularly encephalitis and encephalopathy, increased significantly during this period. Deterioration of existing neurological conditions, such as seizure exacerbation, was also observed. A large‐scale treatment trial of people with COVID‐19 infection presenting with neurological disorders is still needed. [ABSTRACT FROM AUTHOR]

Our aim was to clarify the incidence and risk of acute symptomatic seizures in people with coronavirus disease 2019 (COVID‐19). This multicenter retrospective study enrolled people with COVID‐19 from January 18 to February 18, 2020 at 42 government‐designated hospitals in Hubei province, the epicenter of the epidemic in China; Sichuan province; and Chongqing municipality. Data were collected from medical records by 11 neurologists using a standard case report form. A total of 304 people were enrolled, of whom 108 had a severe condition. None in this cohort had a known history of epilepsy. Neither acute symptomatic seizures nor status epilepticus was observed. Two people had seizurelike symptoms during hospitalization due to acute stress reaction and hypocalcemia, and 84 (27%) had brain insults or metabolic imbalances during the disease course known to increase the risk of seizures. There was no evidence suggesting an additional risk of acute symptomatic seizures in people with COVID‐19. Neither the virus nor potential risk factors for seizures seem to be significant risks for the occurrence of acute symptomatic seizures in COVID‐19. [ABSTRACT FROM AUTHOR]

Landslide modeling based on seismic signal characteristics is an effective method to study landslide evolution. The scientific challenge lies in how to systematically characterize and reconstruct the entire landslide evolution process using the recorded seismic data. We selected the 2017 "6.24" Xinmo landslide as a case study. Empirical mode decomposition (EMD) is used to analyze the seismic signals from 14 seismic stations near the landslide area. Numerical simulations using two-dimensional discrete element methods (DEM) are performed to simulate landslide dynamics using the calculated kinetic energy profile. After analyzing the short-time Fourier transform (STFT) and fast Fourier transform (FFT) characteristics of the signal, the landslide process is reconstructed and compared with the DEM simulation. The landslide process is observed to consist of a stationary stage, slipping stage, transition stage, entrainment-transportation stage, and a deposition stage. This is the first study that uses seismic signals to identify a transition stage, which is a feature that is difficult to constrain from field survey and analysis alone. Landslide development and movement in the transition stage are discussed considering the sedimentology of the study area. This study provides improved theoretical guidance for the reconstruction and characterization of landslide processes by seismic signals. • Seismic signals generated by the Xinmo landslide (Sichuan - China) were analyzed. • 5 stages of landslide were recognized from spectral variations of seismic recording. • One transition stage was identified between first slipping and entrainment stage. • Discrete element simulations supported the landslide process reconstruction. [ABSTRACT FROM AUTHOR]