Laryngeal Dystonia: Consensus on terminology, pathophysiology, and research priorities

Neurology ◽  
2021 ◽  
pp. 10.1212/WNL.0000000000011922
Author(s):  
Kristina Simonyan ◽  
Julie Barkmeier-Kraemer ◽  
Andrew Blitzer ◽  
Mark Hallett ◽  
John F Houde ◽  
...  
Keyword(s):  
Clinical Management ◽  
Large Scale ◽  
Clinical Care ◽  
Research Priorities ◽  
Brain Network ◽  
Research Progress ◽  
Diagnostic Tools ◽  
Laryngeal Dystonia ◽  
Critical Nodes ◽  
Structural Brain Network

Objective.To delineate research priorities for improving clinical management of laryngeal dystonia, the NIH convened a multi-disciplinary panel of experts for a one-day workshop to examine the current progress in understanding its etiopathophysiology and clinical care.Methods.The participants reviewed the current terminology of disorder and discussed advances in understanding its pathophysiology since a similar workshop was held in 2005. Clinical and research gaps were identified, and recommendations for future directions were delineated.Results.The panel unanimously agreed to adopt the term “laryngeal dystonia” instead of “spasmodic dysphonia” to reflect the current progress in characterizations of this disorder. Laryngeal dystonia was recognized as a multifactorial, phenotypically heterogeneous form of isolated dystonia. Its etiology remains unknown, whereas the pathophysiology likely involves large-scale functional and structural brain network disorganization. Current challenges include the lack of clinically validated diagnostic markers and outcome measures and the paucity of therapies that address the disorder pathophysiology.Conclusion.Research priorities should be guided by challenges in clinical management of laryngeal dystonia. Identification of disorder-specific biomarkers would allow the development of novel diagnostic tools and unified measures of treatment outcome. Elucidation of the critical nodes within neural networks that cause or modulate symptoms would allow the development of targeted therapies that address the underlying pathophysiology. Given the rarity of laryngeal dystonia, future rapid research progress may be facilitated by multi-center, national and international collaborations.

scholarly journals Adapting to disruption of research during the COVID-19 pandemic while testing nonpharmacological approaches to pain management

2020 ◽  
Vol 10 (4) ◽  
pp. 827-834
Author(s):  
Brian C Coleman ◽  
Jacob Kean ◽  
Cynthia A Brandt ◽  
Peter Peduzzi ◽  
Robert D Kerns
Keyword(s):  
Chronic Pain ◽  
Pain Management ◽  
Large Scale ◽  
Clinical Care ◽  
Research Progress ◽  
Management Interventions ◽  
Study Protocols ◽  
Pragmatic Clinical Trials ◽  
Patient Reported ◽  
The Impact

Abstract The COVID-19 pandemic has slowed research progress, with particularly disruptive effects on investigations of addressing urgent public health challenges, such as chronic pain. The National Institutes of Health (NIH) Department of Defense (DoD) Department of Veterans Affairs (VA) Pain Management Collaboratory (PMC) supports 11 large-scale, multisite, embedded pragmatic clinical trials (PCTs) in military and veteran health systems. The PMC rapidly developed and enacted a plan to address key issues in response to the COVID-19 pandemic. The PMC tracked and collaborated in developing plans for addressing COVID-19 impacts across multiple domains and characterized the impact of COVID-19 on PCT operations, including delays in recruitment and revisions of study protocols. A harmonized participant questionnaire will facilitate later meta-analyses and cross-study comparisons of the impact of COVID-19 across all 11 PCTs. The pandemic has affected intervention delivery, outcomes, regulatory and ethics issues, participant recruitment, and study design. The PMC took concrete steps to ensure scientific rigor while encouraging flexibility in the PCTs, while paying close attention to minimizing the burden on research participants, investigators, and clinical care teams. Sudden changes in the delivery of pain management interventions will probably alter treatment effects measured via PMC PCTs. Through the use of harmonized instruments and surveys, we are capturing these changes and plan to monitor the impact on research practices, as well as on health outcomes. Analyses of patient-reported measures over time will inform potential relationships between chronic pain, mental health, and various socioeconomic stressors common among Americans during the COVID-19 pandemic.

scholarly journals Criticality as a determinant of integrated information Φ in human brain networks

2019 ◽  
Author(s):  
Hyoungkyu Kim ◽  
Anthony G. Hudetz ◽  
George A. Mashour ◽  
UnCheol Lee
Keyword(s):  
Large Scale ◽  
Brain Network ◽  
Functional Network ◽  
Necessary Condition ◽  
Optimal Network ◽  
Functional Brain Network ◽  
Structural Network ◽  
Structural Brain Network ◽  
Variation Of Functional ◽  
Integrated Information

AbstractIntegrated information theory (IIT) postulates that consciousness arises from the cause-effect structure of a system but the optimal network conditions for this structure have not been elucidated. In the study, we test the hypothesis that network criticality, a dynamically balanced state between a large variation of functional network configurations and a large constraint of structural network configurations, is a necessary condition for the emergence of a cause-effect structure that results in a large Φ, a surrogate of integrated information. We also hypothesized that if the brain deviates from criticality, the cause-effect structure is obscured and Φ diminishes. We tested these hypotheses with a large-scale brain network model and high-density electroencephalography (EEG) acquired during various levels of human consciousness during general anesthesia. In the modeling study, maximal criticality coincided with maximal Φ. The constraint of the structural network on the functional network is maximized in the maximal criticality. The EEG study demonstrated an explicit relationship between Φ, criticality, and level of consciousness. Functional brain network significantly correlated with structural brain network only in conscious states. The results support the hypothesis that network criticality maximizes Φ.

Gastroesophageal Reflux Disease: A Gastroenterologist's Perspective

2011 ◽  
Vol 21 (3) ◽  
pp. 89-99
Author(s):  
Michael F. Vaezi
Keyword(s):  
Gastroesophageal Reflux Disease ◽  
Gastroesophageal Reflux ◽  
Reflux Disease ◽  
Best Practice ◽  
Clinical Care ◽  
Diagnostic Testing ◽  
Diagnostic Tools ◽  
Swallowing Function ◽  
Atypical Symptoms

Gastroesophageal reflux disease (GERD) is a commonly diagnosed condition often associated with the typical symptoms of heartburn and regurgitation, although it may present with atypical symptoms such as chest pain, hoarseness, chronic cough, and asthma. In most cases, the patient's reduced quality of life drives clinical care and diagnostic testing. Because of its widespread impact on voice and swallowing function as well as its social implications, it is important that speech-language pathologists (SLPs) understand the nature of GERD and its consequences. The purpose of this article is to summarize the nature of GERD and GERD-related complications such as GERD-related peptic stricture, Barrett's esophagus and adenocarcinoma, and laryngeal manifestations of GERD from a gastroenterologist's perspective. It is critical that SLPs who work with a multidisciplinary team understand terminology, diagnostic tools, and treatment to ensure best practice.

scholarly journals Patient Experience in Home Respiratory Therapies: Where We Are and Where to Go

2019 ◽  
Vol 8 (4) ◽  
pp. 555 ◽  
Author(s):  
Cátia Caneiras ◽  
Cristina Jácome ◽  
Sagrario Mayoralas-Alises ◽  
José Ramon Calvo ◽  
João Almeida Fonseca ◽  
...  
Keyword(s):  
Clinical Research ◽  
Patient Experience ◽  
Clinical Care ◽  
Research Priorities ◽  
Specific Patient ◽  
Quality Healthcare ◽  
Body Of Knowledge ◽  
Number Of Patients ◽  
Patient Reported ◽  
System Sustainability

The increasing number of patients receiving home respiratory therapy (HRT) is imposing a major impact on routine clinical care and healthcare system sustainability. The current challenge is to continue to guarantee access to HRT while maintaining the quality of care. The patient experience is a cornerstone of high-quality healthcare and an emergent area of clinical research. This review approaches the assessment of the patient experience in the context of HRT while highlighting the European contribution to this body of knowledge. This review demonstrates that research in this area is still limited, with no example of a prescription model that incorporates the patient experience as an outcome and no specific patient-reported experience measures (PREMs) available. This work also shows that Europe is leading the research on HRT provision. The development of a specific PREM and the integration of PREMs into the assessment of prescription models should be clinical research priorities in the next several years.

A new method to predict anomaly in brain network based on graph deep learning

2020 ◽  
Vol 31 (6) ◽  
pp. 681-689
Author(s):  
Jalal Mirakhorli ◽  
Hamidreza Amindavar ◽  
Mojgan Mirakhorli
Keyword(s):  
Deep Learning ◽  
Large Scale ◽  
Brain Plasticity ◽  
Brain Network ◽  
High Order ◽  
Brain Diseases ◽  
Simultaneous Occurrence ◽  
Generative Adversarial Network ◽  
The Brain ◽  
Brain Connections

AbstractFunctional magnetic resonance imaging a neuroimaging technique which is used in brain disorders and dysfunction studies, has been improved in recent years by mapping the topology of the brain connections, named connectopic mapping. Based on the fact that healthy and unhealthy brain regions and functions differ slightly, studying the complex topology of the functional and structural networks in the human brain is too complicated considering the growth of evaluation measures. One of the applications of irregular graph deep learning is to analyze the human cognitive functions related to the gene expression and related distributed spatial patterns. Since a variety of brain solutions can be dynamically held in the neuronal networks of the brain with different activity patterns and functional connectivity, both node-centric and graph-centric tasks are involved in this application. In this study, we used an individual generative model and high order graph analysis for the region of interest recognition areas of the brain with abnormal connection during performing certain tasks and resting-state or decompose irregular observations. Accordingly, a high order framework of Variational Graph Autoencoder with a Gaussian distributer was proposed in the paper to analyze the functional data in brain imaging studies in which Generative Adversarial Network is employed for optimizing the latent space in the process of learning strong non-rigid graphs among large scale data. Furthermore, the possible modes of correlations were distinguished in abnormal brain connections. Our goal was to find the degree of correlation between the affected regions and their simultaneous occurrence over time. We can take advantage of this to diagnose brain diseases or show the ability of the nervous system to modify brain topology at all angles and brain plasticity according to input stimuli. In this study, we particularly focused on Alzheimer’s disease.

scholarly journals Identifying a Common Functional Framework for Apathy Large-Scale Brain Network

2021 ◽  
Vol 11 (7) ◽  
pp. 679
Author(s):  
Vincenzo Alfano ◽  
Mariachiara Longarzo ◽  
Giulia Mele ◽  
Marcello Esposito ◽  
Marco Aiello ◽  
...  
Keyword(s):  
Large Scale ◽  
Brain Magnetic Resonance Imaging ◽  
Brain Network ◽  
Neural Pathways ◽  
Resonance Imaging ◽  
Daily Life Activities ◽  
Functional Differences ◽  
Central Gyrus ◽  
Magnetic Resonance Imaging Mri ◽  
Disease Specific

Apathy is a neuropsychiatric condition characterized by reduced motivation, initiative, and interest in daily life activities, and it is commonly reported in several neurodegenerative disorders. The study aims to investigate large-scale brain networks involved in apathy syndrome in patients with frontotemporal dementia (FTD) and Parkinson’s disease (PD) compared to a group of healthy controls (HC). The study sample includes a total of 60 subjects: 20 apathetic FTD and PD patients, 20 non apathetic FTD and PD patients, and 20 HC matched for age. Two disease-specific apathy-evaluation scales were used to measure the presence of apathy in FTD and PD patients; in the same day, a 3T brain magnetic resonance imaging (MRI) with structural and resting-state functional (fMRI) sequences was acquired. Differences in functional connectivity (FC) were assessed between apathetic and non-apathetic patients with and without primary clinical diagnosis revealed, using a whole-brain, seed-to-seed approach. A significant hypoconnectivity between apathetic patients (both FTD and PD) and HC was detected between left planum polare and both right pre- or post-central gyrus. Finally, to investigate whether such neural alterations were due to the underlying neurodegenerative pathology, we replicated the analysis by considering two independent patients’ samples (i.e., non-apathetic PD and FTD). In these groups, functional differences were no longer detected. These alterations may subtend the involvement of neural pathways implicated in a specific reduction of information/elaboration processing and motor outcome in apathetic patients.

scholarly journals Challenges and opportunities for ovarian cancer management in the epidemic of Covid-19: lessons learned from Wuhan, China

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Zhilan Chen ◽  
Chun Zhang ◽  
Jiu Yin ◽  
Xin Xin ◽  
Hemei Li ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Large Scale ◽  
Treatment Plan ◽  
Clinical Care ◽  
Gynecologic Cancer ◽  
Treatment Phase ◽  
Tumor Stage ◽  
Current Treatment ◽  
Lessons Learned ◽  
Cancer Management

AbstractChina and the rest of the world are experiencing an outbreak of the 2019 novel coronavirus disease (COVID-19). Patients with cancer are more susceptible to viral infection and are more likely to develop severe complications, as compared to healthy individuals. The growing spread of COVID-19 presents challenges for the clinical care of patients with gynecological malignancies. Ovarian debulking surgery combined with the frequent need for chemotherapy is most likely why ovarian cancer was rated as the gynecologic cancer most affected by COVID-19. Therefore, ovarian cancer presents a particular challenging task. Concerning the ovarian cancer studies with confirmed COVID-19 reported from large-scale general hospitals in Wuhan, we hold that the treatment plan was adjusted appropriately and an individualized remedy was implemented. The recommendations discussed here were developed mainly based on the experience from Wuhan. We advise that the management strategy for ovarian cancer patients should be adjusted in the light of the local epidemic situation and formulated according to the pathological type, tumor stage and the current treatment phase. Online medical service is an effective and convenient communication platform during the pandemic.

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