William O Tatum1, Lawrence J Hirsch2, Michael A Gelfand3, Emily K Acton3, W Curt LaFrance4, Robert B Duckrow2, David K Chen5, Andrew S Blum4, John D Hixson6, Joe F Drazkowski7, Selim R Benbadis8, Gregory D Cascino9. 1. Department of Neurology, Mayo Clinic, Jacksonville, Florida. 2. Department of Neurology, Yale University, New Haven, Connecticut. 3. Department of Neurology, University of Pennsylvania, Philadelphia. 4. Department of Neurology, Brown University, Providence, Rhode Island. 5. Department of Neurology, Baylor College of Medicine, Houston, Texas. 6. University of California, San Francisco, San Francisco. 7. Department of Neurology, Mayo Clinic, Phoenix, Arizona. 8. Department of Neurology, University of South Florida, Tampa. 9. Department of Neurology, Mayo Clinic, Rochester, Minnesota.
Abstract
Importance: Misdiagnosis of epilepsy is common. Video electroencephalogram provides a definitive diagnosis but is impractical for many patients referred for evaluation of epilepsy. Objective: To evaluate the accuracy of outpatient smartphone videos in epilepsy. Design, Setting, and Participants: This prospective, masked, diagnostic accuracy study (the OSmartViE study) took place between August 31, 2015, and August 31, 2018, at 8 academic epilepsy centers in the United States and included a convenience sample of 44 nonconsecutive outpatients who volunteered a smartphone video during evaluation and subsequently underwent video electroencephalogram monitoring. Three epileptologists uploaded videos for physicians from the 8 epilepsy centers to review. Main Outcomes and Measures: Measures of performance (accuracy, sensitivity, specificity, positive predictive value, and negative predictive value) for smartphone video-based diagnosis by experts and trainees (the index test) were compared with those for history and physical examination and video electroencephalogram monitoring (the reference standard). Results: Forty-four eligible epilepsy clinic outpatients (31 women [70.5%]; mean [range] age, 45.1 [20-82] years) submitted smartphone videos (530 total physician reviews). Final video electroencephalogram diagnoses included 11 epileptic seizures, 30 psychogenic nonepileptic attacks, and 3 physiologic nonepileptic events. Expert interpretation of a smartphone video was accurate in predicting a video electroencephalogram monitoring diagnosis of epileptic seizures 89.1% (95% CI, 84.2%-92.9%) of the time, with a specificity of 93.3% (95% CI, 88.3%-96.6%). Resident responses were less accurate for all metrics involving epileptic seizures and psychogenic nonepileptic attacks, despite greater confidence. Motor signs during events increased accuracy. One-fourth of the smartphone videos were correctly diagnosed by 100% of the reviewing physicians, composed solely of psychogenic attacks. When histories and physical examination results were combined with smartphone videos, correct diagnoses rose from 78.6% to 95.2%. The odds of receiving a correct diagnosis were 5.45 times greater using smartphone video alongside patient history and physical examination results than with history and physical examination alone (95% CI, 1.01-54.3; P = .02). Conclusions and Relevance: Outpatient smartphone video review by experts has predictive and additive value for diagnosing epileptic seizures. Smartphone videos may reliably aid psychogenic nonepileptic attacks diagnosis for some people.
Importance: Misdiagnosis of epilepsy is common. Video electroencephalogram provides a definitive diagnosis but is impractical for many patients referred for evaluation of epilepsy. Objective: To evaluate the accuracy of outpatient smartphone videos in epilepsy. Design, Setting, and Participants: This prospective, masked, diagnostic accuracy study (the OSmartViE study) took place between August 31, 2015, and August 31, 2018, at 8 academic epilepsy centers in the United States and included a convenience sample of 44 nonconsecutive outpatients who volunteered a smartphone video during evaluation and subsequently underwent video electroencephalogram monitoring. Three epileptologists uploaded videos for physicians from the 8 epilepsy centers to review. Main Outcomes and Measures: Measures of performance (accuracy, sensitivity, specificity, positive predictive value, and negative predictive value) for smartphone video-based diagnosis by experts and trainees (the index test) were compared with those for history and physical examination and video electroencephalogram monitoring (the reference standard). Results: Forty-four eligible epilepsy clinic outpatients (31 women [70.5%]; mean [range] age, 45.1 [20-82] years) submitted smartphone videos (530 total physician reviews). Final video electroencephalogram diagnoses included 11 epileptic seizures, 30 psychogenic nonepileptic attacks, and 3 physiologic nonepileptic events. Expert interpretation of a smartphone video was accurate in predicting a video electroencephalogram monitoring diagnosis of epileptic seizures 89.1% (95% CI, 84.2%-92.9%) of the time, with a specificity of 93.3% (95% CI, 88.3%-96.6%). Resident responses were less accurate for all metrics involving epileptic seizures and psychogenic nonepileptic attacks, despite greater confidence. Motor signs during events increased accuracy. One-fourth of the smartphone videos were correctly diagnosed by 100% of the reviewing physicians, composed solely of psychogenic attacks. When histories and physical examination results were combined with smartphone videos, correct diagnoses rose from 78.6% to 95.2%. The odds of receiving a correct diagnosis were 5.45 times greater using smartphone video alongside patient history and physical examination results than with history and physical examination alone (95% CI, 1.01-54.3; P = .02). Conclusions and Relevance: Outpatient smartphone video review by experts has predictive and additive value for diagnosing epileptic seizures. Smartphone videos may reliably aid psychogenic nonepileptic attacks diagnosis for some people.
Authors: Yue-Yung Hu; Sarah E Peyre; Alexander F Arriaga; Robert T Osteen; Katherine A Corso; Thomas G Weiser; Richard S Swanson; Stanley W Ashley; Chandrajit P Raut; Michael J Zinner; Atul A Gawande; Caprice C Greenberg Journal: J Am Coll Surg Date: 2012-01 Impact factor: 6.113
Authors: Simona Alexandra Beniczky; András Fogarasi; Miri Neufeld; Noémi Becser Andersen; Peter Wolf; Walter van Emde Boas; Sándor Beniczky Journal: Epilepsy Behav Date: 2012-05-06 Impact factor: 2.937
Authors: Julian Varghese; Stephan Niewöhner; Iñaki Soto-Rey; Stephanie Schipmann-Miletić; Nils Warneke; Tobias Warnecke; Martin Dugas Journal: Front Neurol Date: 2019-01-30 Impact factor: 4.003
Authors: Christopher J L Murray; Ryan M Barber; Kyle J Foreman; Ayse Abbasoglu Ozgoren; Foad Abd-Allah; Semaw F Abera; Victor Aboyans; Jerry P Abraham; Ibrahim Abubakar; Laith J Abu-Raddad; Niveen M Abu-Rmeileh; Tom Achoki; Ilana N Ackerman; Zanfina Ademi; Arsène K Adou; José C Adsuar; Ashkan Afshin; Emilie E Agardh; Sayed Saidul Alam; Deena Alasfoor; Mohammed I Albittar; Miguel A Alegretti; Zewdie A Alemu; Rafael Alfonso-Cristancho; Samia Alhabib; Raghib Ali; François Alla; Peter Allebeck; Mohammad A Almazroa; Ubai Alsharif; Elena Alvarez; Nelson Alvis-Guzman; Azmeraw T Amare; Emmanuel A Ameh; Heresh Amini; Walid Ammar; H Ross Anderson; Benjamin O Anderson; Carl Abelardo T Antonio; Palwasha Anwari; Johan Arnlöv; Valentina S Arsic Arsenijevic; Al Artaman; Rana J Asghar; Reza Assadi; Lydia S Atkins; Marco A Avila; Baffour Awuah; Victoria F Bachman; Alaa Badawi; Maria C Bahit; Kalpana Balakrishnan; Amitava Banerjee; Suzanne L Barker-Collo; Simon Barquera; Lars Barregard; Lope H Barrero; 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Authors: Wesley T Kerr; Emily A Janio; Andrea M Chau; Chelsea T Braesch; Justine M Le; Jessica M Hori; Akash B Patel; Norma L Gallardo; Corinne H Allas; Amir H Karimi; Ishita Dubey; Siddhika S Sreenivasan; Janar Bauirjan; Eric S Hwang; Emily C Davis; Shannon R D'Ambrosio; Mona Al Banna; Rajarshi Mazumder; Ting Wu; Zachary A DeCant; Michael G Gibbs; Edward Chang; Xingruo Zhang; Andrew Y Cho; Nicholas J Beimer; Jerome Engel; Mark S Cohen; John M Stern Journal: Epilepsy Behav Date: 2020-11-13 Impact factor: 2.937
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