Integrative medicine in treating post-stroke depression: Study protocol for a multicenter, prospective, randomized, controlled trial
Bibliographic record
Abstract
Background: Post-stroke depression (PSD) is one of the most common neuropsychiatric diseases in patients with stroke, and it can increase the disability rate, mortality, and recurrence rate of stroke. Currently, many clinical studies have indicated that traditional Chinese medicine (TCM), such as acupuncture and herbs, Western medicine, rehabilitation, repeated transcranial magnetic stimulation, and other treatment methods, are effective in treating PSD. However, no study has formulated a comprehensive treatment plan that integrates TCM, Western medicine, and rehabilitation for PSD. Thus, this trial aims to assess the efficacy and safety of integrative medicine for treating PSD. Methods: This multicenter, prospective, randomized, controlled study aims to form a set of effective clinical treatment schemes that integrate TCM, Western medicine, and rehabilitation for PSD. A total of 202 participants recruited from four centers will be randomized into either the integrative medicine or standard care group. Standard care-basic treatment, general nursing care, and exercise therapy-will be provided to all participants. The integrative medicine group will also receive acupuncture, Chinese herbs, and repeated transcranial magnetic stimulation (rTMS). Participants will receive acupuncture and rTMS treatments five times per week for 4 weeks and will be administered Chinese herbs, basic treatment, general nursing care, and exercise therapy for 4 weeks. The primary outcomes include the Hamilton Depression Scale (HAMD), Self-Rating Depression Scale (SDS), and Activity of Daily Living Scale (ADL). And the secondary outcomes include the Montreal Cognitive Assessment Scale, the Fugl-Meyer Assessment (FMA) Scale, and the Pittsburgh Sleep Quality Index (PSQI). All outcome measures will be evaluated at baseline, week 4 (the end of the treatment courses), and week 8 (the end of follow-up). Safety assessments will be performed throughout the study. Discussion: This study is expected to verify the efficacy and safety of integrative medicine for treating PSD, providing an evidence-based clinical reference for the future development of a standardized scheme. Clinical trial registration: ClinicalTrials.gov, identifier: NCT05187975.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.013 | 0.006 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.054 | 0.007 |
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".