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Record W4409346897

Therapeutic effect of levodopa-carbidopa-entacapone combined with rTMS in Parkinson's disease.

2025· article· en· W4409346897 on OpenAlexaboutno aff
Kefei Zhang, Bin Wang, Qing-Yun Yu, Xiaorui Cui, Liying Zhang

Bibliographic record

VenuePubMed · 2025
Typearticle
Languageen
FieldMaterials Science
TopicConducting polymers and applications
Canadian institutionsnot available
Fundersnot available
KeywordsEntacaponeLevodopaCarbidopaParkinson's diseaseMedicineDiseasePsychologyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Parkinson's disease (PD) is a neurodegenerative disorder characterized by progressive tissue deterioration. This study evaluated the effects of levodopa-carbidopa-entacapone (LCE) combined with high-frequency repetitive transcranial magnetic stimulation (HF-rTMS) in elderly PD patients. Participants were divided into an observation group (HF-rTMS + LCE) and a control group (HF-rTMS alone). Motor and cognitive function, quality of life, and adverse effects were assessed before treatment and at 8 weeks, 16 weeks and 6 months post-treatment. Both groups showed no significant differences in baseline data. However, post-treatment, the observation group demonstrated superior clinical improvements. The Unified Parkinson's Disease Rating Scale-III (UPDRS-III) score significantly decreased from 43.40±3.94 to 34.73±5.05 at 6 months (P<0.01), while the Berg Balance Scale (BBS) score increased from 30.97±5.17 to 46.35±5.75 (P<0.01). The Timed Up and Go test (TUGT) time reduced from 13.12±2.23 seconds to 8.62±2.50 seconds (P<0.01) and the Parkinson's Disease Questionnaire (PDQ-39) score decreased from 37.32±3.69 to 25.75±4.59 (P<0.01). Additionally, the Montreal Cognitive Assessment (MoCA) score increased from 22.05±2.24 to 28.15±1.99 (P<0.001). Adverse effects were similar between groups (16.7% vs. 15%, P>0.05). These results suggest HF-rTMS combined with LCE enhances motor function, balance, cognition, and quality of life in elderly PD patients without increasing adverse effects.

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 score0.246
Threshold uncertainty score0.299

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 head0.013
GPT teacher head0.234
Teacher spread0.221 · 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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