Effect of Specific mode electroacupuncture stimulation combined with NGF during the ischaemic stroke: Study protocol for a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: The emergence of the Nerve Growth Factor (NGF) has promoted the development of neuroprotective therapy; however, it has little effect on cerebral ischemia because of its poor Blood-Brain Barrier (BBB) permeability. Specific Mode Electroacupuncture Stimulation (SMES) can open BBB safely and effectively; however, it has shown inconclusive clinical effects and indirect clinical evidence in the recovery phase. Hence, the authors conducted a multicentre, randomized, placebo-controlled, assessor-blinded clinical trial to assess the effectiveness and safety of SMES combined with NGF treatment used during ischaemic stroke recovery. METHODS: A total of 288 stroke patients from three hospitals will be recruited and randomly allocated to four groups: acupuncture + placebo, acupuncture + NGF, SMES + placebo, and SMES + NGF, in a 1:1:1:1 ratio. Assessment data will be collected at baseline, 2-weeks, and 4-weeks during the treatment period, as well as at the 4-week and 8-week follow-up after treatment completion. The primary outcome measure will be the basic cure rate. The secondary outcome measures include the simplified Modified Barthel Index, Timed Up and Go Test, Fugl-Meyer Assessment of Motor Function Score, Tinetti Performance Oriented Mobility Assessment, Montreal Cognitive Assessment, and Loewenstein Occupational Therapy Cognitive Assessment. Moreover, resting-state functional magnetic resonance imaging and Functional near-infrared spectroscopy can detect changes in cerebral blood flow and brain function and investigate the relationship between the clinical efficacy and mechanism of the prescribed interventions. CONCLUSION: This study will provide clinical evidence for the efficacy and safety of SMES combined with NGF in the treatment of stroke patients.
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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 | 0.017 | 0.018 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.017 | 0.005 |
| 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 | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.048 | 0.008 |
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".