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Record W4385728325 · doi:10.21203/rs.3.rs-3211475/v1

Computer-aided Cognitive Training Combined with tDCS Can Improve Cognitive Function and Cerebrovascular Reactivity After Ischemic Stroke: A Randomized Controlled Trial

2023· preprint· en· W4385728325 on OpenAlexaboutno aff
Yin Chen, Ziqi Zhao, Jiapeng Huang, Tingting Wang, Yun Qu

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsnot available
FundersWest China Hospital, Sichuan UniversityHealth Commission of Sichuan ProvinceSichuan UniversityMinistry of Science and Technology of the People's Republic of China
KeywordsMontreal Cognitive AssessmentTranscranial direct-current stimulationCognitive trainingCognitionRehabilitationPhysical medicine and rehabilitationStroke (engine)Physical therapyCognitive rehabilitation therapyMedicineActivities of daily livingRandomized controlled trialPsychologyCognitive impairmentInternal medicineStimulationPsychiatry

Abstract

fetched live from OpenAlex

Abstract Background Cognitive impairment after stroke is one of the main functional disorders after stroke, with an incidence of up to 80%, which is the focus and difficulty of poststroke rehabilitation intervention. Computer-aided cognitive training (CACT) refers to the use of smartphones, tablet computers and other electronic devices to provide targeted training content for different cognitive function impairments. Transcranial direct current stimulation (tDCS), as a noninvasive brain stimulation technique, has shown some efficacy in the rehabilitation of cognitive impairment after stroke. This study examined the effectiveness of computer-assisted cognitive training and tDCS in the treatment of poststroke cognitive dysfunction and explored whether the combination of the two is better than any single therapy. Methods A total of 72 patients with PSCI admitted to the Department of Rehabilitation Medicine, West China Hospital, Sichuan University from November 2021 to September 2022 were randomly divided into the control group (n=18) that patients received conventional cognitive training, tDCS group (n=18), CACT group (n=18), and CACT plus tDCS group (n=18). All four groups were given conventional drugs and rehabilitation treatment. Each group received corresponding 20-minute treatment 15 times a week for 3 consecutive weeks. The main outcome was the Montreal Cognitive Assessment (MoCA) to assess patients' cognitive function, and the secondary outcomes were the Instrumental Activities of Daily Living Scale (IADL) to assess activities of daily living and cerebral vesselfunction tested by transcranial Doppler ultrasound (TCD). Assessment is at baseline and posttreatment. Results Compared with baseline, the MoCA and IADL scores significantly increased after treatment (P<0.01) in all groups, but thecombined group showed better improvement than the other three groups (P=0.006, 0.002, 0.011), and there were no significant differences within the control group, CACT group and tDCS group. Only CACT combined with tDCS group showed an advantage in improving vasomotor reactivity (p ≤ 0.05). Conclusion The combination of CACT and tDCS could more effectively improve PSCI and the ability of daily living in patients with cognitive impairment after stroke, and that may be associated with cerebrovascular function. Trial registration number The study was registered in Chinese Registry of Clinical Trials (ChiCTR2100054063). Registration date: 12/08/2021.

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)0.002
metaresearch head score (Gemma)0.002
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.075
GPT teacher head0.344
Teacher spread0.269 · 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
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
Published2023
Admission routes1
Has abstractyes

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