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A Quantitative Study of Factors Influencing Myasthenia Gravis Telehealth Examination Score
Author(s) -
Garbey Marc,
Lesport Quentin,
Girma Helen,
Öztosun Gülşen,
Kaminski Henry J.
Publication year - 2025
Publication title -
muscle and nerve
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.025
H-Index - 145
eISSN - 1097-4598
pISSN - 0148-639X
DOI - 10.1002/mus.28394
Subject(s) - myasthenia gravis , telemedicine , telehealth , activities of daily living , medicine , physical therapy , reliability (semiconductor) , physical medicine and rehabilitation , neuromuscular disease , disease , health care , power (physics) , physics , quantum mechanics , economics , economic growth
ABSTRACT Introduction/Aims The adoption of telemedicine is generally considered as advantageous for patients and physicians, but there is limited rigorous assessment of examination strengths and limitations. We set out to perform a quantitative assessment of the limitations of a standardized examination of subjects with myasthenia gravis (MG) during video‐taped telemedicine sessions. Methods We utilized a video bank containing recordings from 51 MG patients who completed two telemedicine‐based examinations with neuromuscular experts; each recording included the MG core examination (MG‐ CE ) and the MG activities of daily living (MG‐ADL). We then applied artificial intelligence (AI) algorithms from computer vision and speech analysis to natural language processing to generate and assess the reproducibility and inter‐rater reliability of the MG‐ CE and MG‐ADL. Results We successfully developed a technology to assess video examinations. While overall MG‐ CE scores were consistent across examiners, individual metrics showed significant variability, with up to a 25% variation in scoring within the MG‐ CE 's range. Additionally, there was wide variability in adherence to MG‐ADL instructions. These variations were attributed to differences in examiner instructions, video recording limitations, and patient disease severity. Discussion We were able to develop a system of digital analysis of neuromuscular examinations in order to assess variability in individual scoring measures of the MG‐ADL and MG‐ CE . Our approach enabled post hoc quantitative analysis of neuromuscular examinations. Further refinement of this technology could enhance examiner training and reduce variability in clinical trial outcome measures.