Acupuncture for ischemic stroke: where are we now?
Bibliographic record
Abstract
Acupuncture is an effective treatment for ischemic stroke (IS) and plays a key role in neurological rehabilitation after IS. Acupuncture can improve the clinical symptoms of various complications after IS, including motor dysfunction, swallowing disorders, speech disorders, cognitive impairment, depression, insomnia, and fatigue. However, the mechanisms underlying the effects of acupuncture in IS remain unclear. Available evidence suggests that acupuncture may exert neuroprotective effects through neuroplasticity (neurogenesis and synaptogenesis), angiogenesis, cell proliferation and apoptosis, and regulation of oxidative stress, inflammation, and immunity. Further studies should be conducted to improve the high-quality evidence-based system of acupuncture intervention for IS, by focusing on the clinical and basic research design, increasing the sample size, standardizing and quantifying the standards of acupuncture operations, using multidisciplinary techniques and methods to systematically explore the key targets of acupuncture intervention for IS, and reveal the efficacy and mechanism of acupuncture in the treatment of IS.
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 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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".