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Record W4403680154 · doi:10.1371/journal.pone.0309233

Daily high-frequency transcranial random noise stimulation (hf-tRNS) for sleep disturbances and cognitive dysfunction in patients with mild vascular cognitive impairments: A study protocol for a pilot randomized controlled trial

2024· article· en· W4403680154 on OpenAlexaboutno aff
Yuqi Gong, Jing Li, Natalie Shu Yang, Zeyan Li, Wai Kwong Tang, Hanna Lu

Bibliographic record

VenuePLoS ONE · 2024
Typearticle
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsnot available
FundersChinese University of Hong Kong
KeywordsRandomized controlled trialMedicineTranscranial magnetic stimulationCognitionEffects of sleep deprivation on cognitive performanceBrain stimulationMontreal Cognitive AssessmentPhysical medicine and rehabilitationAudiologyPsychologyInternal medicineStimulationPsychiatryCognitive impairment

Abstract

fetched live from OpenAlex

BACKGROUND: Poor sleep quality is increasingly considered to be an underlying cause of cerebrovascular diseases. This is a slowly progressing condition that gradually leads to vascular cognitive impairment and stroke during ageing. At present, randomized clinical trials examining the non-pharmacological therapies in the management of this comorbidity are very limited. Transcranial current stimulation (tCS) is a non-invasive technology for promoting cognitive function and treating brain disorders. As advanced modalities of tCS, transcranial random noise stimulation (tRNS) and transcranial alternating current stimulation (tACS), could deliver frequency-specific waveforms of currents that can modulate brain activities in a more specific manner. METHODS AND DESIGN: Chinese individuals between the ages of 60 and 90 years, who are right-handed and have mild vascular cognitive impairment (VCI) with sleep disturbances, will participate in a randomized study. They will undergo a 2-week intervention period where they will be randomly assigned to one of three groups: high-frequency (hf)-tRNS, 40 Hz tACS, or sham tCS. Each group will consist of 15 participants. Before the intervention, high-resolution magnetic resonance imaging (MRI) data will be used to create a computational head model for each participant. This will help identify the treatment target of left inferior parietal lobe (IPL). Throughout the study, comprehensive assessments will be conducted at multiple time points, including baseline, 2nd week, 6th week, and 12th week. These assessments will evaluate various factors such as sleep quality, domain-specific cognitive performance, and actigraphic records. In addition, the participants' adherence to the program and any potential adverse effects will be closely monitored throughout the duration of the intervention. CONCLUSIONS: The primary objective of this study is to examine the safety, feasibility, and effectiveness of hf-tRNS and 40 Hz tACS interventions targeting left IPL in individuals with mild vascular cognitive impairment (VCI) who experience sleep disturbances and cognitive dysfunction. Additionally, the study seeks to evaluate the program's adherence, tolerability, and any potential adverse effects associated with frequency-specific transcranial current stimulation (tCS). The findings from this research will contribute to a deeper understanding of the intricate relationship between oscillation, sleep, and cognition. Furthermore, the results will provide valuable insights to guide future investigations in the field of sleep medicine and neurodegenerative diseases. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT06169254.

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)0.017
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.032
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.010
Meta-epidemiology (narrow)0.0050.002
Meta-epidemiology (broad)0.0100.004
Bibliometrics0.0020.002
Science and technology studies0.0030.003
Scholarly communication0.0020.002
Open science0.0030.002
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0320.006

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 head0.038
GPT teacher head0.285
Teacher spread0.248 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations4
Published2024
Admission routes1
Has abstractyes

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