The diagnostic value of clinical neurophysiology in hyperkinetic movement disorders: A systematic review

Introduction: To guide the neurologist and neurophysiologist with interpretation and implementation of clinical neurophysiological examinations, we aim to provide a systematic review on evidence of electrophysiological features used to differentiate between hyperkinetic movement disorders. Methods: A PRISMA systematic search and QUADAS quality evaluation has been performed in PubMed to identify diagnostic test accuracy studies comparing electromyography and accelerometer features. We included papers focusing on tremor, dystonia, myoclonus, chorea, tics and ataxia and their functional variant. The features were grouped as 1) basic features (e.g., amplitude, frequency), 2) the influence of tasks on basic features (e.g., entrainment, distraction), 3) advanced analyses of multiple signals, 4) and diagnostic tools combining features. Results: Thirty-eight cross-sectional articles were included discussing tremor (n = 28), myoclonus (n = 5), dystonia (n = 5) and tics (n = 1). Fifteen were rated as 'high quality'. In tremor, the basic and task-related features showed great overlap between clinical tremor syndromes, apart from rubral and enhanced physiological tremor. Advanced signal analyses were best suited for essential, parkinsonian and functional tremor, and cortical, noncortical and functional jerks. Combinations of electrodiagnostic features could identify essential, enhanced physiological and functional tremor. Conclusion: Studies into the diagnostic accuracy of electrophysiological examinations to differentiate between hyperkinetic movement disorders have predominantly been focused on clinical tremor syndromes. No single feature can differentiate between them all; however, a combination of analyses might improve diagnostic accuracy.

Automated summary

This article provides a systematic review on electrophysiological features used to differentiate between hyperkinetic movement disorders, focusing mainly on clinical tremor syndromes. Basic and task-related features in tremor syndromes overlap, but advanced signal analyses are more suited for specific types of tremor. Combinations of electrodiagnostic features are helpful in identifying different types of tremor.