Data-Driven Fatigue Trajectories in Multiple Sclerosis and Their Predictors
Abstract
Fatigue is one of the most disabling symptoms of multiple sclerosis (MS), yet its longitudinal trajectories and determinants remain poorly characterized. We aimed to identify trajectories of cognitive and physical fatigue in relapsing-remitting MS (RRMS) and to determine baseline clinical and MRI predictors of worsening fatigue.
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Authors: Alessandro Cruciani, Emanuele Olivieri, Ronja Christensen, Sarmad Al‐Araji, Samih Fourali, Weaam Hamed, Anna He, Baris Kanber, Davide Maccarrone, Suraya Mohamud, Riccardo Nistri, Anestis Passalis, Valeria Pozzilli, Ferrán Prados, Charmaine Yam, Marios Yiannakas, Alan J. Thompson, Frederik Barkhof, Ahmed Toosy, Olga Ciccarelli
Institutions: Karolinska Institutet, Amsterdam University Medical Centers, University College London, Monash University, University of Amsterdam, University of Brescia, Great Ormond Street Hospital, Sapienza University of Rome, Queen Mary University of London, Università Campus Bio-Medico, Universitat Oberta de Catalunya, Amsterdam UMC Location Vrije Universiteit Amsterdam, Amsterdam UMC Location University of Amsterdam, University Hospitals Coventry and Warwickshire NHS Trust, Azienda Ospedaliera San Camillo-Forlanini, UCL Biomedical Research Centre, Cleveland Clinic London