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Record W4394685394 · doi:10.3389/fnins.2024.1375234

Effect of high-frequency repetitive transcranial magnetic stimulation on cognitive impairment in WD patients based on inverse probability weighting of propensity scores

2024· article· en· W4394685394 on OpenAlexaboutno aff
Hong Chen, Xie Wang, Juan Zhang, Daojun Xie

Bibliographic record

VenueFrontiers in Neuroscience · 2024
Typearticle
Languageen
FieldNursing
TopicTrace Elements in Health
Canadian institutionsnot available
FundersAnhui UniversityNational Natural Science Foundation of China
KeywordsTranscranial magnetic stimulationWeightingCognitive impairmentMedicineNeuroscienceInverseCognitionAudiologyPropensity score matchingPhysical medicine and rehabilitationPsychologyStimulationMathematicsInternal medicineRadiology

Abstract

fetched live from OpenAlex

Background Hepatolenticular degeneration [Wilson disease (WD)] is an autosomal recessive metabolic disease characterized by copper metabolism disorder. Cognitive impairment is a key neuropsychiatric symptom of WD. At present, there is no effective treatment for WD-related cognitive impairment. Methods In this study, high-frequency repetitive transcranial magnetic stimulation (rTMS) was used to treat WD-related cognitive impairment, and inverse probability weighting of propensity scores was used to correct for confounding factors. The Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Auditory Verbal Learning Test (AVLT), Boston Naming Test (BNT), Clock Drawing Test (CDT) and Trail Making Test (TMT) were used to evaluate overall cognition and specific cognitive domains. Results The MMSE, MoCA and CDT scores after treatment were significantly different from those before treatment (MMSE: before adjustment: OR = 1.404, 95% CI: 1.271–1.537; after adjustment: OR = 1.381, 95% CI: 1.265–1.497, p < 0.001; MoCA: before adjustment: OR = 1.306, 95% CI: 1.122–1.490; after adjustment: OR = 1.286, 95% CI: 1.104; AVLT: OR = 1.161, 95% CI: 1.074–1.248; after adjustment: OR = 1.145, 95% CI: 1.068–1.222, p < 0.05; CDT: OR = 1.524, 95% CI: 1.303–1.745; after adjustment: OR = 1.518, 95% CI: 1.294–1.742, p < 0.001). The BNT and TMT scores after adjustment were not significantly different from those before adjustment (BNT: before adjustment: OR = 1.048, 95% CI: 0.877–1.219; after adjustment: OR = 1.026, 95% CI: 0.863–1.189, p > 0.05; TMT: before adjustment: OR = 0.816, 95% CI: 1.122–1.490; after adjustment: OR = 0.791, 95% CI: 0.406–1.176, p > 0.05). Conclusion High-frequency rTMS can effectively improve cognitive impairment, especially memory and visuospatial ability, in WD patients. The incidence of side effects is low, and the safety is good.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.270
Teacher spread0.257 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations1
Published2024
Admission routes1
Has abstractyes

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