The Use of Repetitive Transcranial Magnetic Stimulation to Improve Cognitive Impairment in Patients With Stroke Based on rs-fMRI Findings: Protocol for a Meta-Analysis
Notice bibliographique
Résumé
BACKGROUND: Poststroke cognitive impairment (PSCI) is a chronic form of poststroke cognitive dysfunction that affects approximately one-third of the survivors of stroke. PSCI significantly increases the rates of mortality and functional disabilities, such as limitations in motor function, speech, and activities of daily living. Therefore, effective treatments are needed for patients with PSCI. Repetitive transcranial magnetic stimulation (rTMS) has been shown to exert beneficial behavioral effects in patients with PSCI. More importantly, a limited number of neuroimaging studies with small sample sizes have reported the beneficial effects of rTMS on brain plasticity and its reciprocal influence on cognitive and behavioral performance. Resting-state functional magnetic resonance imaging (rs-fMRI) has been widely used to study changes in brain activity, but there is no consensus regarding which brain regions play pivotal roles in rTMS for patients with PSCI. OBJECTIVE: This study aims to explore the therapeutic effects of rTMS on changes in the brain activity of patients with PSCI, thereby providing robust evidence to elucidate its neuroimaging mechanisms. METHODS: In this meta-analysis, we will systematically search the PubMed, Embase, Cochrane Library, Web of Science, China Biology Medicine, and China National Knowledge Infrastructure databases, VIP Chinese Science and Technology Periodical Database, and the China WanFang Database up to December 2024 to identify randomized controlled trials comparing active rTMS with sham stimulation conditions or conventional control conditions in patients with PSCI. The primary outcomes will include the amplitude of low-frequency fluctuation, fractional amplitude of low-frequency fluctuation, regional homogeneity, and functional connectivity across the whole brain. The secondary outcomes will include the Montreal Cognitive Assessment and Mini-Mental State Examination scores. Statistical analyses will be conducted via Review Manager (version 5.4), Seed-based d Mapping with Permutation of Subject Images (version 6.23), and Stata (version 18.0) software to assess study quality, evaluate the risk of bias, and analyze the outcome measures. RESULTS: The study will offer a comprehensive analysis of the available evidence on the use of rTMS to improve cognitive impairment in patients with stroke based on rs-fMRI findings. The meta-analysis will be conducted from July 2024 to April 2026, following this predefined protocol. The process encompasses database searching and study screening (to be concluded by October 2025), data extraction and synthesis (to be completed by December 2025), and subsequent manuscript preparation and submission (anticipated by April 2026). CONCLUSIONS: This meta-analysis will provide insights into the therapeutic potential of rTMS to improve cognitive impairment in patients with stroke. It will also highlight the strengths and limitations of the existing literature and suggest directions for future research. Ultimately, our study may aid future clinical decision-making concerning PSCI rehabilitation programs and provide evidence-based medical insights into the neuroimaging mechanisms of rTMS treatment for PSCI. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/77931.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,033 | 0,043 |
| Méta-épidémiologie (sens strict) | 0,006 | 0,003 |
| Méta-épidémiologie (sens large) | 0,021 | 0,032 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,004 | 0,003 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,005 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,027 | 0,003 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».