Predictive value of individual serum neurofilament light chain levels in short-term disease activity in relapsing multiple sclerosis
ConclusionIndividual sNFL levels may potentially confirm prior or current disease activity and predict short-term future radiological activity in RMS. These findings underscore its periodic measurement as a valuable tool in RMS management and decision-making, enhancing the precision of clinical evaluation in routine practice. (Source: Frontiers in Neurology)
Source: Frontiers in Neurology - February 14, 2024 Category: Neurology Source Type: research
Sleep duration and perceptions of sleep quality in British Army recruits during basic training - an observational analysis
ConclusionOur findings contribute to the existing evidence that long-term sleep loss is pervasive during initial military training programmes. The average sleep durations indicate chronic and unrecoverable sleep loss which would be expected to significantly impair physical and cognitive military performance, and increase the risk of injury, illness and attrition rates during basic training. Changes in the design and scheduling of basic training programmes to enable, at the least, minimum sleep recommendations to be met, and to improve sleep hygiene in the primary sleeping environment are warranted. (Source: Frontiers in Neurology)
Source: Frontiers in Neurology - February 14, 2024 Category: Neurology Source Type: research
Case report: Tolosa-Hunt syndrome —expanding the neuromyelitis optica spectrum disorder phenotype?
Neuromyelitis optica spectrum disorder (NMOSD) is an autoimmune astrocytopathy caused by the autoantibody of aquaporin-4 (AQP4). Herein, we report a case of Tolosa-Hunt syndrome presenting with abducens palsy and AQP4 antibodies. This was a rare case of AQP4-immunoglobulin G seropositivity in a patient with Tolosa-Hunt syndrome. Our findings may expand the clinical phenotype of NMOSD and indicate that clinicians should consider testing for AQP4 antibodies in patients with Tolosa-Hunt syndrome. (Source: Frontiers in Neurology)
Source: Frontiers in Neurology - February 14, 2024 Category: Neurology Source Type: research
Fine tuned personalized machine learning models to detect insomnia risk based on data from a smart bed platform
This study leverages personalized fine-tuned machine learning algorithms to detect insomnia risk based on questionnaire and longitudinal objective sleep data collected by a smart bed platform.MethodsUsers of the Sleep Number smart bed were invited to participate in an IRB approved study which required them to respond to four questionnaires (which included the Insomnia Severity Index; ISI) administered 6 weeks apart from each other in the period from November 2021 to March 2022. For 1,489 participants who completed at least 3 questionnaires, objective data (which includes sleep/wake and cardio-respiratory metrics) collected...
Source: Frontiers in Neurology - February 14, 2024 Category: Neurology Source Type: research
Voxel- and tensor-based morphometry with machine learning techniques identifying characteristic brain impairment in patients with cervical spondylotic myelopathy
ConclusionCSM may cause widespread and remote impairments in brain structures. This study provided a valuable reference for developing novel diagnostic strategies to identify CSM. (Source: Frontiers in Neurology)
Source: Frontiers in Neurology - February 14, 2024 Category: Neurology Source Type: research
