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Record W4414242803 · doi:10.5334/tohm.1095

Medication Adherence in Chinese Patients with Essential Tremor: A Real World Study

2025· article· en· W4414242803 on OpenAlexaboutno aff
Runcheng He, Mingqiang Li, Xun Zhou, Lanqing Liu, Chunyu Wang, Hainan Zhang, Qiying Sun

Bibliographic record

VenueTremor and Other Hyperkinetic Movements · 2025
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedication adherenceMEDLINEAlternative medicineDiseasePatient compliance

Abstract

fetched live from OpenAlex

Background: Medication adherence in essential tremor (ET) remains poorly characterized. This real world study aimed to investigate adherence rates, clinical correlates, and predictors among ET patients in China. Methods: A prospective cohort of 318 ET patients (116 pure ET, 202 ET-plus) was followed for a mean of 22.91 ± 3.86 months. Standardized assessments included the Tremor Research Group Essential Tremor Rating Assessment Scale (TETRAS), Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Non-Motor Symptoms Scale (NMSS). Adherence was defined as daily use of prescribed tremor medications. Logistic regression identified predictors. Results: Only 27.4% (87/318) maintained daily adherence. ET-plus patients showed higher adherence than pure ET (32.2% vs 19.0%, P = 0.011). Arotinolol was the most common medication. Compared to non-adherent patients, adherent patients showed higher urban residency (P = 0.026), head tremor prevalence (P = 0.002), mild cognitive impairment (P = 0.038), higher TETRAS-I (P = 0.047) and TETRAS-II scores (P = 0.008), as well as lower MoCA scores (P = 0.021). Multivariable analysis showed better medication adherence was significantly associated with higher TETRAS-II score (OR = 1.041, 95% CI = 1.001-1.082, P = 0.047), urban residence (OR = 1.775, 95% CI = 1.066-2.957, P = 0.028), and the presence of head tremor (OR = 1.936, 95% CI = 1.125-3.332, P = 0.017). No significant association was found between ET subtypes and adherence (P > 0.05). Conclusion: Medication adherence is alarmingly low in Chinese ET patients, especially in pure ET. Greater tremor severity, presence of head tremor, and urban residence were independently associated with better medication adherence. Highlight: Medication adherence among Chinese essential tremor (ET) patients remains suboptimal (only 27.4% in our cohort). ET plus patients showed higher adherence (32.2%) than pure ET (19.0%). Predictors of adherence included severe tremor (TETRAS-II), urban residence, and head tremor. Arotinolol was the predominant treatment. Findings emphasize the need for personalized interventions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.478

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.285
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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