Functional or not functional; that's the question: Can we predict the diagnosis functional movement disorder based on...

Area of Science:

• Neurology
• Movement Disorders
• Clinical Diagnostics

Background:

• Functional movement disorders (FMDs) present diagnostic challenges for clinicians.
• Identifying discriminative features is crucial for accurate FMD diagnosis.
• Previous studies suggest several features are associated with FMDs.

Purpose of the Study:

• To identify features that discriminate between FMDs and non-FMDs in a large patient cohort.
• To develop a preliminary predictive model for FMD diagnosis based on differentiating features.

Main Methods:

• Retrospective review of medical records from a hyperkinetic outpatient clinic (2012-2019).
• Comparison of 12 associated features between FMD and non-FMD groups.
• Statistical analyses including t-tests, chi-squared tests, and multivariate logistic regression.

Main Results:

• 874 patients were included (320 FMD, 554 non-FMD).
• Discriminative features included age of onset, sex, psychiatric/family history, multiple motor phenotypes, pain, fatigue, abrupt onset, long-term waxing/waning, and diurnal fluctuations.
• A preliminary predictive model achieved 91% discriminative value.

Conclusions:

• Ten features are identified as discriminative for hyperkinetic FMDs.
• These features can assist clinicians in identifying patients suspected of FMDs.
• Further prospective, multi-center validation of the predictive model is recommended.