Abstract

There has been a concerted move in recent times to shift from an exclusionary to a positive diagnosis of functional movement disorders (FMDs). To date, most of the focus has been on defining positive physical signs. Here the focus was on the diagnostic specificity of specific symptoms and patient characteristics. For this prospective cohort study, newly referred patients in the Netherlands and Australia were recruited before their first neurology appointment. Participants completed questionnaires within 2 months prior to their visit at one of the six different clinics. Directly following the first consultation, physicians received a questionnaire about their diagnostic process. Patients were excluded if the diagnosis was not a movement disorder. Univariate and multivariate regression analyses were conducted to identify predictors of FMDs. Subsequently, a predictive model was constructed and assessed using the area under the receiver operating curve. Between 1 March 2021 and 1 March 2023, 465 patients were eligible for inclusion, of whom 171 (37%) had an FMD and 294 (63%) a non-FMD. Distinguishing factors amongst these groups included age at onset, gender, history or family history of a functional and psychiatric disorder, sudden onset, specific triggers, fluctuation patterns throughout the day and over an extended period, pain, fatigue, depression, anxiety and dissociation. Using these, a predictive model was developed, yielding a discriminative accuracy of 88%. Specific symptoms and patient characteristics have high diagnostic discriminative value between FMDs and non-FMDs, providing an additional tool in positive diagnosis.

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