Electrophysiology in Distinguishing Functional Tremor from Organic Tremor: A Systematic Review and Meta-Analysis of...

Functional tremor is the most common functional movement disorder. Delayed diagnosis can negatively impact outcomes, highlighting the need for early and accurate identification. Electrophysiological testing may support diagnosis when clinical assessment is inconclusive. However, the pooled diagnostic performance of electrophysiological tests has not been systematically synthesized, as most studies are based on limited samples.

The aim was to synthesize the diagnostic accuracy of electrophysiological tests in differentiating functional tremor from organic tremor.

The PubMed and Scopus databases were searched from inception to February 2025. Study quality was assessed using Quality Assessment of Diagnostic Accuracy Studies version 2 (QUADAS-2). Electrophysiological tests were categorized into four major groups-task-free tests, task-based tests, coherence-based tests, and test batteries-comprising 14 test subgroups. Pooled sensitivity and specificity, both overall and by subgroup, were estimated using a random-effects univariate model. Heterogeneity was assessed statistically.

Ten studies encompassing 37 separate index test evaluations across 14 test subgroups were included. The overall pooled sensitivity and specificity were 0.63 (95% confidence interval [CI]: 0.51-0.75) and 0.93 (95% CI: 0.91-0.95), respectively. Sensitivity ranged from 30% to 100%, and specificity from 68% to 100% across test subgroups. Significant heterogeneity was observed for both sensitivity (P < 0.001) and specificity (P = 0.038). Test batteries A and B demonstrated relatively high diagnostic accuracy, and frequency shift and frequency peak width during mental tasks also exhibited good performance.

Electrophysiological tests demonstrate variable diagnostic accuracy in distinguishing functional tremor from organic tremor. Test batteries appear to provide superior performance and may represent a standardized assessment approach. Frequency-based analyses with mental-task distraction are also promising but require more rigorous evaluation. Further studies are needed to strengthen evidence regarding their test properties.