Search

Your search keyword '"Galetta, Steven"' showing total 3,464 results
Start Over Author "Galetta, Steven"
3,464 results on '"Galetta, Steven"'

2. MOG Antibody–Associated Disease and Thymic Hyperplasia

Author

Hurtubise, Brigitte, Frohman, Elliot M, Galetta, Steven, Balcer, Laura J, Frohman, Teresa C, Lisak, Robert P, Newsome, Scott D, Graves, Jennifer S, Zamvil, Scott S, and Amezcua, Lilyana

Subjects
Biomedical and Clinical Sciences, Immunology, Autoimmune Disease, Neurosciences, Multiple Sclerosis, Neurodegenerative, Rare Diseases, Brain Disorders, 2.1 Biological and endogenous factors, Aetiology, Inflammatory and immune system, Humans, Myelin-Oligodendrocyte Glycoprotein, Thymus Hyperplasia, Autoantibodies, Optic Neuritis, Immune System Diseases
Abstract

Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is a recently described CNS inflammatory disorder that may manifest with optic neuritis, myelitis, seizures, and/or acute disseminated encephalomyelitis. While MOG-specific antibodies in patients with MOGAD are IgG1, a T-cell-dependent antibody isotype, immunologic mechanisms of this disease are not fully understood. Thymic hyperplasia can be associated with certain autoimmune diseases. In this report we describe a case of MOGAD associated with thymic hyperplasia in a young adult.

Published
2023

9. Artificial intelligence extension of the OSCAR‐IB criteria

Author

Petzold, Axel, Albrecht, Philipp, Balcer, Laura, Bekkers, Erik, Brandt, Alexander U, Calabresi, Peter A, Deborah, Orla Galvin, Graves, Jennifer S, Green, Ari, Keane, Pearse A, Bijvank, Jenny A Nij, Sander, Josemir W, Paul, Friedemann, Saidha, Shiv, Villoslada, Pablo, Wagner, Siegfried K, Yeh, E Ann, Aktas, Orhan, Antel, Jack, Asgari, Nasrin, Audo, Isabelle, Avasarala, Jagannadha, Avril, Daly, Bagnato, Francesca R, Banwell, Brenda, Bar‐Or, Amit, Behbehani, Raed, Manterola, Arnaldo Belzunce, Bennett, Jeffrey, Benson, Leslie, Bernard, Jacqueline, Bremond‐Gignac, Dominique, Britze, Josefine, Burton, Jodie, Calkwood, Jonathan, Carroll, William, Chandratheva, Arvind, Cohen, Jeffrey, Comi, Giancarlo, Cordano, Christian, Costa, Silvana, Costello, Fiona, Courtney, Ardith, Cruz‐Herranz, Anes, Cutter, Gary, Crabb, David, Delott, Lindsey, De Seze, Jerome, Diem, Ricarda, Dollfuss, Helene, Ayoubi, Nabil K El, Fasser, Christina, Finke, Carsten, Fischer, Dominik, Fitzgerald, Kathryn, Fonseca, Pedro, Frederiksen, Jette L, Frohman, Elliot, Frohman, Teresa, Fujihara, Kazuo, Cuellar, Iñigo Gabilondo, Galetta, Steven, Garcia‐Martin, Elena, Giovannoni, Gavin, Glebauskiene, Brigita, Suárez, Inés González, Jensen, Gorm Pihl, Hamann, Steffen, Hartung, Hans‐Peter, Havla, Joachim, Hemmer, Bernhard, Huang, Su‐Chun, Imitola, Jaime, Jasinskas, Vytautas, Jiang, Hong, Kafieh, Rahele, Kappos, Ludwig, Kardon, Randy, Keegan, David, Kildebeck, Eric, Kim, Ungsoo Samuel, Klistorner, Sasha, Knier, Benjamin, Kolbe, Scott, Korn, Thomas, Krupp, Lauren, Lagrèze, Wolf, Leocani, Letizia, Levin, Netta, Liskova, Petra, Preiningerova, Jana Lizrova, Lorenz, Birgit, May, Eugene, Miller, David, Mikolajczak, Janine, Saïd, Saddek Mohand, Montalban, Xavier, Morrow, Mark, Mowry, Ellen, and Murta, Joaquim

Subjects
Biomedical and Clinical Sciences, Neurosciences, Bioengineering, Biomedical Imaging, Autoimmune Disease, Neurodegenerative, Aging, Brain Disorders, Neurological, Algorithms, Artificial Intelligence, Big Data, Cohort Studies, Humans, Nervous System Diseases, Retina, Tomography, Optical Coherence, IMSVISUAL, ERN-EYE Consortium, Clinical Sciences, Clinical and health psychology
Abstract

Artificial intelligence (AI)-based diagnostic algorithms have achieved ambitious aims through automated image pattern recognition. For neurological disorders, this includes neurodegeneration and inflammation. Scalable imaging technology for big data in neurology is optical coherence tomography (OCT). We highlight that OCT changes observed in the retina, as a window to the brain, are small, requiring rigorous quality control pipelines. There are existing tools for this purpose. Firstly, there are human-led validated consensus quality control criteria (OSCAR-IB) for OCT. Secondly, these criteria are embedded into OCT reporting guidelines (APOSTEL). The use of the described annotation of failed OCT scans advances machine learning. This is illustrated through the present review of the advantages and disadvantages of AI-based applications to OCT data. The neurological conditions reviewed here for the use of big data include Alzheimer disease, stroke, multiple sclerosis (MS), Parkinson disease, and epilepsy. It is noted that while big data is relevant for AI, ownership is complex. For this reason, we also reached out to involve representatives from patient organizations and the public domain in addition to clinical and research centers. The evidence reviewed can be grouped in a five-point expansion of the OSCAR-IB criteria to embrace AI (OSCAR-AI). The review concludes by specific recommendations on how this can be achieved practically and in compliance with existing guidelines.

Published
2021

11. Tele-Neuro-Ophthalmology During the Age of COVID-19.

Author

Lai, Kevin, Ko, Melissa, Rucker, Janet, Odel, Jeffrey, Sun, Linus, Winges, Kimberly, Ghosh, Arko, Bindiganavile, Shruthi, Bhat, Nita, Wendt, Sydney, Scharf, Jackson, Dinkin, Marc, Rasool, Nailyn, Galetta, Steven, and Lee, Andrew

Subjects
Betacoronavirus, COVID-19, Coronavirus Infections, Delivery of Health Care, Eye Diseases, Health Plan Implementation, Humans, Neurology, Ophthalmology, Pandemics, Patient Selection, Pneumonia, Viral, Remote Consultation, SARS-CoV-2, Telemedicine
Abstract

Supplemental Digital Content is Available in the Text.

Published
2020

18. Life stressors significantly impact long-term outcomes and post-acute symptoms 12-months after COVID-19 hospitalization

Author

Agarwal, Shashank, Andino, Andres, Arena, Vito, Baskharoun, Samuel, Bauman, Kristie, Bell, Lena, Berger, Stephen, Bhagat, Dhristie, Bokhari, Matthew, Bondi, Steven, Canizares, Melanie, Chervinsky, Alexander, Czeisler, Barry M., Dygert, Levi, Fang, Taolin, Flusty, Brent, Friedman, Daniel, Friedman, David, Fuchs, Benjamin, Granger, Andre, Gratch, Daniel, Gurin, Lindsey, Gutman, Josef, Hasanaj, Lisena, Holmes, Manisha, Horng, Jennifer, Huang, Joshua, Ishii, Haruki, Jauregui, Ruben, Ji, Yuan, Kahn, D. Ethan, Koch, Ethan, Krieger, Penina, Kvernland, Alexandra, Lalchan, Rebecca, Lillemoe, Kaitlyn, Lin, Jessica, Liu, Susan B., Madhavan, Maya, Medicherla, Chaitanya, Millar-Vernetti, Patricio, Morgan, Nicole, Olivera, Anlys, Omari, Mirza, Park, George, Patel, Palak, Ristic, Milan, Rosenthal, Jonathan, Sonson, Michael, Snyder, Thomas, Stainman, Rebecca S., Sunwoo, Brian, Talmasov, Daniel, Tamimi, Michael, Thomas, Betsy, Valdes, Eduard, Zhou, Ting, Zhu, Yingrong, Frontera, Jennifer A., Sabadia, Sakinah, Yang, Dixon, de Havenon, Adam, Yaghi, Shadi, Lewis, Ariane, Lord, Aaron S., Melmed, Kara, Thawani, Sujata, Balcer, Laura J., Wisniewski, Thomas, and Galetta, Steven L.

Published
2022
Full Text
View/download PDF

19. MICK (Mobile Integrated Cognitive Kit) app: Feasibility of an accessible tablet-based rapid picture and number naming task for concussion assessment in a division 1 college football cohort

Author

Bell, Carter A., Rice, Lionel, Balcer, Marc J., Pearson, Randolph, Penning, Brett, Alexander, Aubrey, Roskelly, Jensyn, Nogle, Sally, Tomczyk, Chris P., Tracey, Allie J., Loftin, Megan C., Pollard-McGrandy, Alyssa M., Zynda, Aaron J., Covassin, Tracey, Park, George, Rizzo, John-Ross, Hudson, Todd, Rucker, Janet C., Galetta, Steven L., Balcer, Laura, Kaufman, David I., and Grossman, Scott N.

Published
2022
Full Text
View/download PDF

23. A young man in “double-trouble”: Hallucinations and cranial nerve palsies: From the National Multiple Sclerosis Society Case Conference Proceedings

Author

Bradshaw, Michael J, Lisak, Robert P, Meltzer, Ethan, Melamed, Esther, Lucas, Ashlea, Freeman, Leorah, Frohman, Teresa C, Costello, Kathleen, Balcer, Laura, Galetta, Steven, Chitnis, Tanuja, Zamvil, Scott S, and Frohman, Elliot M

Subjects
Biomedical and Clinical Sciences, Ophthalmology and Optometry, Adolescent, Anti-N-Methyl-D-Aspartate Receptor Encephalitis, Brain, Congresses as Topic, Cranial Nerve Diseases, Diagnosis, Differential, Encephalitis, Hallucinations, Humans, Male, Neurosciences
Published
2019

24. Toxic Metabolic Encephalopathy in Hospitalized Patients with COVID-19

Author

Frontera, Jennifer A., Melmed, Kara, Fang, Taolin, Granger, Andre, Lin, Jessica, Yaghi, Shadi, Zhou, Ting, Lewis, Ariane, Kurz, Sebastian, Kahn, D. Ethan, de Havenon, Adam, Huang, Joshua, Czeisler, Barry M., Lord, Aaron, Meropol, Sharon B., Troxel, Andrea B., Wisniewski, Thomas, Balcer, Laura, and Galetta, Steven

Published
2021
Full Text
View/download PDF

25. Long-term outcomes in patients presenting with optic neuritis: Analyses of the MSBase registry

Author

Kenney, Rachel, Liu, Mengling, Patil, Sachi, Alroughani, Raed, Ampapa, Radek, Bergamaschi, Roberto, Boz, Cavit, Butzkueven, Helmut, Gomez, Jose Cabrera, Cartechini, Elisabetta, Madueño, Sara Eichau, Ferraro, Diana, Grand-Maison, Francois, Granella, Franco, Horakova, Dana, Izquierdo Ayuso, Guillermo, Kalincik, Tomas, Lizrova Preiningerova, Jana, Lugaresi, Alessandra, Onofrj, Marco, Ozakbas, Serkan, Patti, Francesco, Sola, Patrizia, Soysal, Aysun, Spitaleri, Daniele Litterio A., Terzi, Murat, Turkoglu, Recai, van Pesch, Vincent, Saidha, Shiv, Thorpe, Lorna E., Galetta, Steven L., Balcer, Laura J., Kister, Ilya, and Spelman, Tim

Published
2021
Full Text
View/download PDF

26. Normative Data and Conversion Equation for Spectral-Domain Optical Coherence Tomography in an International Healthy Control Cohort

Author

Kenney, Rachel, Liu, Mengling, Hasanaj, Lisena, Joseph, Binu, Al-Hassan, Abdullah A., Balk, Lisanne, Behbehani, Raed, Brandt, Alexander U., Calabresi, Peter A., Frohman, Elliot M., Frohman, Teresa, Havla, Joachim, Hemmer, Bernhard, Jiang, Hong, Knier, Benjamin, Korn, Thomas, Leocani, Letizia, Martínez-Lapiscina, Elena H., Papadopoulou, Athina, Paul, Friedemann, Petzold, Axel, Pisa, Marco, Villoslada, Pablo, Zimmermann, Hanna, Ishikawa, Hiroshi, Schuman, Joel S., Wollstein, Gadi, Chen, Yu, Saidha, Shiv, Thorpe, Lorna E., Galetta, Steven L., and Balcer, Laura J.

Published
2022
Full Text
View/download PDF

28. A prospective study of long-term outcomes among hospitalized COVID-19 patients with and without neurological complications

Author

Frontera, Jennifer A., Yang, Dixon, Lewis, Ariane, Patel, Palak, Medicherla, Chaitanya, Arena, Vito, Fang, Taolin, Andino, Andres, Snyder, Thomas, Madhavan, Maya, Gratch, Daniel, Fuchs, Benjamin, Dessy, Alexa, Canizares, Melanie, Jauregui, Ruben, Thomas, Betsy, Bauman, Kristie, Olivera, Anlys, Bhagat, Dhristie, Sonson, Michael, Park, George, Stainman, Rebecca, Sunwoo, Brian, Talmasov, Daniel, Tamimi, Michael, Zhu, Yingrong, Rosenthal, Jonathan, Dygert, Levi, Ristic, Milan, Ishii, Haruki, Valdes, Eduard, Omari, Mirza, Gurin, Lindsey, Huang, Joshua, Czeisler, Barry M., Kahn, D. Ethan, Zhou, Ting, Lin, Jessica, Lord, Aaron S., Melmed, Kara, Meropol, Sharon, Troxel, Andrea B., Petkova, Eva, Wisniewski, Thomas, Balcer, Laura, Morrison, Chris, Yaghi, Shadi, and Galetta, Steven

Published
2021
Full Text
View/download PDF

30. MICK (Mobile Integrated Cognitive Kit) App for Concussion Assessment in a Youth Ice Hockey League.

Author

Hyman, Sara, Blacker, Mason, Bell, Carter A., Balcer, Marc J., Joseph, Binu, Galetta, Steven L., Balcer, Laura J., and Grossman, Scott N.

Abstract

Background: Visual symptoms are common after concussion. Rapid automatized naming (RAN) tasks are simple performance measures that demonstrate worse time scores in the setting of acute or more remote injury. Methods: We evaluated the capacity for the Mobile Universal Lexicon Evaluation System (MULES) and Staggered Uneven Number (SUN) testing to be feasibly administered during preseason testing in a cohort of youth ice hockey athletes using a novel computerized app, the Mobile Integrated Cognitive Kit (MICK). Participants from a youth hockey league underwent preseason testing. Results: Among 60 participants, the median age was 13 years (range 6–17). The median best time for the MULES was 49.8 seconds (range = 34.2–141.0) and the median best time for the SUN was 70.1 (range = 36.6–200.0). As is characteristic of timed performance measures, there were learning effects between the first and second trials for both the MULES (median improvement = 10.6 seconds, range = −32.3 to 92.0, P < 0.001, Wilcoxon signed-rank test) and SUN (median improvement = 2.4 seconds, range= −8.0 to 15.1, P = 0.001, Wilcoxon signed-rank test). Age was a predictor of best baseline times, with longer (worse) times for younger participants for MULES (P < 0.001, r s = −0.67) and SUN (P < 0.001, r s = −0.54 Spearman rank correlation). Degrees of learning effect did not vary with age (P > 0.05, r s = −0.2). Conclusions: Vision-based RAN tasks, such as the MULES and SUN, can be feasibly administered using the MICK app during preseason baseline testing in youth sports teams. The results suggest that more frequent baseline tests are necessary for preadolescent athletes because of the relation of RAN task performance to age. [ABSTRACT FROM AUTHOR]

Published
2025
Full Text
View/download PDF

31. Neuro-Ophthalmic Manifestations of Adult Polyglucosan Body Disease.

Author

Dugue, Andrew G., Abreu, Nicolas J., Pillai, Cinthi, Galetta, Steven L., and Grossman, Scott N.

Abstract

Supplemental Digital Content is Available in the Text. Background: Adult polyglucosan body disease (APBD) is caused by a deficiency in glycogen branching enzyme that leads to polyglucosan accumulation in multiple organs. It has a progressive clinical course with prominent neurologic manifestations. We aim to describe the neuro-ophthalmic manifestations of APBD. Methods: This is a case series of 3 individuals with genetically proven APBD. Written informed consent was provided by the brothers. We also performed a literature review on the current state of knowledge on APBD through PubMed. Results: Brother 1 developed gait imbalance and length-dependent polyneuropathy in his 40s followed by progressive urinary symptoms in his 50s. He reported diplopia and blurry vision in his 60s. Neuro-ophthalmic assessment revealed bilateral optic neuropathy, convergence insufficiency, and a right fourth nerve palsy. Genetic testing showed a homozygous pathogenic variant in GBE1 c.986A>C p.Tyr329Ser. Brother 2 developed progressive urinary symptoms in his 40s that were followed by cognitive deficits, length-dependent polyneuropathy, and lower extremity weakness in his 50s and 60s. He reported blurred vision, and neuro-ophthalmic evaluation revealed bilateral optic neuropathy. Genetic testing revealed the same variant as Brother 1, GBE1 c.986A>C p.Tyr329Ser. Brother 3 developed progressive urinary urgency and lower extremity weakness in his 50s followed by a length-dependent polyneuropathy in his 60s. He reported diplopia and blurry vision in his 70s. Neuro-ophthalmic assessment revealed bilateral optic neuropathy and convergence insufficiency. Genetic testing revealed the same variant as Brothers 1 and 2, GBE1 c.986A>C p.Tyr329Ser. Conclusions: There is an array of afferent and efferent neuro-ophthalmic manifestations in APBD. Neuro-ophthalmic evaluation is crucial in evaluating and treating patients with APBD, particularly in those with visual dysfunction. [ABSTRACT FROM AUTHOR]

Published
2025
Full Text
View/download PDF

38. AI in Neuro-Ophthalmology: Current Practice and Future Opportunities.

Author

Kenney, Rachel C., Requarth, Tim W., Jack, Alani I., Hyman, Sara W., Galetta, Steven L., and Grossman, Scott N.

Abstract

Background: Neuro-ophthalmology frequently requires a complex and multi-faceted clinical assessment supported by sophisticated imaging techniques in order to assess disease status. The current approach to diagnosis requires substantial expertise and time. The emergence of AI has brought forth innovative solutions to streamline and enhance this diagnostic process, which is especially valuable given the shortage of neuro-ophthalmologists. Machine learning algorithms, in particular, have demonstrated significant potential in interpreting imaging data, identifying subtle patterns, and aiding clinicians in making more accurate and timely diagnosis while also supplementing nonspecialist evaluations of neuro-ophthalmic disease. Evidence Acquisition: Electronic searches of published literature were conducted using PubMed and Google Scholar. A comprehensive search of the following terms was conducted within the Journal of Neuro-Ophthalmology: AI, artificial intelligence, machine learning, deep learning, natural language processing, computer vision, large language models, and generative AI. Results: This review aims to provide a comprehensive overview of the evolving landscape of AI applications in neuro-ophthalmology. It will delve into the diverse applications of AI, optical coherence tomography (OCT), and fundus photography to the development of predictive models for disease progression. Additionally, the review will explore the integration of generative AI into neuro-ophthalmic education and clinical practice. Conclusions: We review the current state of AI in neuroophthalmology and its potentially transformative impact. The inclusion of AI in neuro-ophthalmic practice and research not only holds promise for improving diagnostic accuracy but also opens avenues for novel therapeutic interventions. We emphasize its potential to improve access to scarce subspecialty resources while examining the current challenges associated with the integration of AI into clinical practice and research. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

39. Hereditary Optic Neuropathies: An Updated Review.

Author

Lee, Samuel K., Mura, Caroline, Abreu, Nicolas J., Rucker, Janet C., Galetta, Steven L., Balcer, Laura J., and Grossman, Scott N.

Subjects
GENETIC disorders, VISION disorders, MOLECULAR diagnosis, ATROPHY, DIFFERENTIAL diagnosis
Abstract

Hereditary optic neuropathies (HONs) are a class of genetic disorders that may lead to vision loss due to either acute or progressive injury to the optic nerve. Although HONs may commonly manifest as isolated optic atrophy, these disorders can also have a variety of characteristic clinical features and time courses that may narrow the differential diagnosis. While the two most prevalent HONs are Leber Hereditary Optic Neuropathy (LHON) and Dominant Optic Atrophy (DOA), the phenotypic spectrum of these conditions, as well as genetic landscape of less common optic neuropathies, have been better characterized through advances in molecular diagnostic testing. Treatment targeting various pathogenic mechanisms has been investigated, although studies of clinical applicability remain nascent. Present management largely remains supportive. In this review, we discuss the clinical features, molecular diagnosis, current treatment, and future directions for HONs. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results