Acupuncture for Poststroke Cognitive Impairment Based on Default Mode Network Analysis: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Poststroke cognitive impairment (PSCI) is a prevalent and disabling complication following stroke, affecting critical functions such as memory, attention, language, and executive abilities. Despite the growing clinical burden, standardized and effective treatment strategies for PSCI remain limited. Acupuncture, a key modality in traditional Chinese medicine, has shown promise in improving cognitive outcomes among survivors of stroke. However, the neural mechanisms underlying its efficacy are not well understood. The default mode network (DMN), a brain network implicated in cognition and memory, has been shown to exhibit altered functional and structural connectivity in patients with PSCI. Investigating whether acupuncture modulates DMN activity may provide critical insights into its therapeutic potential. OBJECTIVE: This study aims to evaluate the efficacy of acupuncture in improving cognitive function in patients with PSCI and explore its potential neurobiological mechanisms, particularly those involving changes in the DMN, using multimodal neuroimaging techniques. METHODS: We will conduct a single-blind, randomized controlled trial involving 54 eligible patients with PSCI who will be randomly assigned to either an acupuncture group or a sham acupuncture control group. Both groups will receive conventional rehabilitation therapies. The intervention group will undergo standardized scalp acupuncture targeting Baihui (GV20), Shenting (GV24), and Sishencong (EX-HN1) for 8 weeks. The control group will receive sham acupuncture at nonacupoint locations using placebo needles. Cognitive function will be assessed at baseline and 4 and 8 weeks using the Montreal Cognitive Assessment and Mini-Mental State Examination. Secondary outcomes include activities of daily living, quality of life, and neuroimaging data acquired through resting-state functional magnetic resonance imaging and diffusion tensor imaging. RESULTS: This study is currently in the recruitment phase. All results, including clinical and imaging data, will be reported upon trial completion and publication. CONCLUSIONS: This protocol is designed to investigate the efficacy of acupuncture and its underlying mechanisms in treating PSCI, with a particular focus on functional brain networks. By integrating clinical cognitive assessments and neuroimaging analysis of DMN connectivity, this study seeks to establish objective correlates of cognitive improvement. Findings from this research may advance the understanding of how acupuncture modulates large-scale brain networks and contribute to the development of imaging-based biomarkers for treatment evaluation. If successful, this approach could support the inclusion of acupuncture as a personalized nonpharmacological strategy in the neurorehabilitation of cognitive deficits following stroke. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/74981.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.023 |
| Meta-epidemiology (narrow) | 0.007 | 0.002 |
| Meta-epidemiology (broad) | 0.014 | 0.006 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.070 | 0.009 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".