To characterize fatigue in patients with myasthenia gravis, identify other comorbid factors that contribute to it and propose routine screening recommendations.
Background:
Fatigue is a frequent complaint in patients with myasthenia gravis. However, it is non-specific and often associated with other medical conditions. Some of the most frequent causes of fatigue can be indirectly related to myasthenia and its treatment or another simultaneous condition. With this study, the goal is to guide providers on weather to routinely screen for comorbid, potentially treatable causes of fatigue in MG patients.
Design/Methods:
Patients were recruited from VCU Neurology clinics. Inclusion criteria were adults with a confirmed diagnosis of myasthenia gravis from positive antibodies or electrodiagnostic testing. Enrolled patients had a battery of serum laboratory tests collected that included B12, MMA, CBC, TSH and testosterone levels in men. They also filled out questionnaires including PSQI, Epworth Sleepiness Scale and Neurology QoL surveys for fatigue, depression and anxiety. Patients and their primary neurologists were notified of any abnormal lab results and their participation in the study did not have any influence on management of their disease.
Results:
28 patients were enrolled in this study, completed the questionnaires and had laboratory studies collected. 19 patients were female and 9 were male. 68% of patients had an MGFA post-intervention status of MM3. 61% of patients had a fatigue severity scale >36 and 68% scored >50 on the fatigue portion on the QOL questionnaire. 43% of patients had abnormal laboratory results, mostly either anemia or vitamin D deficiency. Regarding sleep, 75% had a PSQI score >5. For psychiatric comorbidities, 46% scored >50 on the anxiety and 50% scored >50 on the depression portion.
Conclusions:
The results of this study suggest that fatigue in patients with myasthenia gravis is multifactorial and routine screening for other causes is warranted. Disclosure: Dr. Gwathmey has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Alexion Pharmaceuticals. Dr. Gwathmey has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Argenx. Dr. Gwathmey has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Argenx. Dr. Gwathmey has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Strongbridge. Dr. Gwathmey has received personal compensation in the range of $500-$4,999 for serving as a Consultant for UCB. Dr. Gwathmey has received personal compensation in the range of $5,000-$9,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Alexion Pharmaceuticals. Dr. Gwathmey has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Alexion Pharmaceuticals. Dr. Patel has nothing to disclose. Ms. Parolisi has nothing to disclose.
Learning to localize temporal boundaries of procedure steps in instructional videos is challenging due to the limited availability of annotated large-scale training videos. Recent works focus on learning the cross-modal alignment between video segments and ASR-transcripted narration texts through contrastive learning. However, these methods fail to account for the alignment noise, i.e., irrelevant narrations to the instructional task in videos and unreliable timestamps in narrations. To address these challenges, this work proposes a novel training framework. Motivated by the strong capabilities of Large Language Models (LLMs) in procedure understanding and text summarization, we first apply an LLM to filter out task-irrelevant information and summarize task-related procedure steps (LLM-steps) from narrations. To further generate reliable pseudo-matching between the LLM-steps and the video for training, we propose the Multi-Pathway Text-Video Alignment (MPTVA) strategy. The key idea is to measure alignment between LLM-steps and videos via multiple pathways, including: (1) step-narration-video alignment using narration timestamps, (2) direct step-to-video alignment based on their long-term semantic similarity, and (3) direct step-to-video alignment focusing on short-term fine-grained semantic similarity learned from general video domains. The results from different pathways are fused to generate reliable pseudo step-video matching. We conducted extensive experiments across various tasks and problem settings to evaluate our proposed method. Our approach surpasses state-of-the-art methods in three downstream tasks: procedure step grounding, step localization, and narration grounding by 5.9\%, 3.1\%, and 2.8\%.
Abstract: The use of biologics for inflammatory skin disease is increasing. Although manufacturers recommend pneumococcal, influenza and varicella zoster vaccines in patients treated with tumor necrosis factor inhibitors to mitigate the risk of infection, data regarding adherence in this group of patients is limited. The European League Against Rheumatism and American College of Rheumatology also issued the recommendations to advocating for influenza, pneumococcal pneumonia and Zoster for this high-risk patient group. We queried the MarketScan data base (which includes about 47 million people) to determine rates of vaccination and infection. In 2014, we identified 41,607 patients, aged 18–60 on adalimumab, etanercept or infliximab (TNFi) for 6 months or more. Of these patients, only 157 received a pneumococcal vaccine. We will present similar data describing utilization of influenza and zoster vaccination in psoriatic utilizing TNFi, from 2014–2016. Rates of in relevant infection (influenza, pneumonia and varicella) will be compared between vaccinated and unvaccinated biologic users. We hypothesize that immunosuppression due to biologic therapy (specifically TNF-inhibitors) incurs a higher risk of infection. Our preliminary data likely highlight an important practice gap in the use of TNFi within dermatology. Teaching points: biologics are associated with a higher risk of influenza, pneumococcal pneumonia, and varicella zoster. Although infection can lead to significant morbidity and mortality, vaccination prior to the initiation of biologic therapy can mitigate risk. Vaccination is probably underutilized in these patients.
Objective A roadway departure crash is one in which a vehicle crosses an edge line, a centerline, or otherwise leaves the traveled way. These crashes that involve run-off-road and cross-median/centerline head-on collisions tend to be more severe than other crash types. According to the NHTSA Fatality Analysis Reporting System database, a total of 7,833 people perished in crashes involving fixed roadside objects in 2017, accounting for 21 percent of the total number of fatalities in the United States. Several previous studies have reported that rural bridge-related crashes result in more fatalities due to their being mostly the fixed-object crash type. As such, further in-depth investigation of this type of crash is necessary. Due to the lack of a comprehensive database that includes bridge-related crashes and bridge characteristics, identifying the key factors contributing to this type of crash is a challenging task that is addressed in this paper.Method Study team gathered and compiled five years (2011–2015) of crash data from the New Jersey crash database and the characteristics of bridges from the Long-Term Bridge Performance portal. A Firth's penalized-likelihood logistic regression model was developed to examine the impact of explanatory variables on crash severity.Results Based on the five years (2011–2015) of crash data, significant factors (i.e., driver age, weather conditions, surface conditions, lighting conditions, speed limit, roadway characteristics, and direction of traffic) were identified that affect the severity of bridge-related crashes in Middlesex County, New Jersey.Conclusion This model is an appropriate tool for predicting the impact of all the confounding variables on the probability of bridge-related crashes while also considering the rareness of the event. Based on the obtained odds ratio, the various effects of the identified variables are discussed, and recommendations made regarding countermeasures policymakers can establish to reduce the number of these crashes in New Jersey.
