Authors
Daniel Kratovil, Seung Yeon Jung, Sonia Stoica, Matthew Roy, Alia C Stanciu, M Cosmin Sandulescu
Published in
Tremor and other hyperkinetic movements (New York, N.Y.). Volume 16. Pages 45. Epub Jul 16, 2026.
Abstract
Essential tremor (ET) is one of the most common movement disorders, yet reported prevalence estimates vary widely, likely because of differences in ascertainment strategies, which can influence data validity and comparability. Electronic healthcare records (EHRs) offer an opportunity to estimate prevalence at the population level. However, the impact of these strategies remains incompletely understood, raising questions about the accuracy and generalizability of the resulting estimates.
We conducted a retrospective, population-based cross-sectional study using EHR data from the Geisinger Health System (GHS) to identify cases of ET. Cases were mapped to a census-defined population of 1,081,934 individuals aged ≥10 years in Northeast-Central Pennsylvania on April 1, 2020. ET prevalence was assessed using two ascertainment strategies: (1) the neurology cohort and (2) the all-specialties cohort. Age-threshold, age-specific, and sex-stratified prevalence estimates were calculated, along with age-standardized rates based on the 2020 U.S. population.
Crude prevalence of ET was 0.261% (95% CI, 0.252-0.271) in the neurology cohort and 0.653% (95% CI, 0.638-0.668) in the all-specialties cohort. Age-standardized prevalence was 0.40% (95% CI, 0.39-0.41) and 1.01% (95% CI, 1.00-1.02), respectively. Prevalence increased progressively with age across both ascertainment strategies, and sex-stratified analyses demonstrated similar age-related patterns with a modest female predominance, particularly in the all-specialties cohort.
ET prevalence estimates vary substantially depending on ascertainment strategy, with broader EHR-based definitions identifying more than twice as many cases as neurologist-restricted approaches. These findings highlight the importance of standardization in improving comparability across studies.
PMID:
42491880
Bibliographic data and abstract were imported from PubMed on 24 Jul 2026.
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