Comparing <scp>C</scp>erebralcare <scp>G</scp>ranule and aspirin for neurological dysfunction in acute stroke in real‐life practice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Cerebralcare Granule (CG) is a polyherbal Chinese medicine that has been shown to have neuroprotective effects in experimental models of stroke. We compared the efficacy and safety of CG with aspirin in patients with acute stroke. METHODS: For this open-label, controlled trial, we recruited patients with angiographically confirmed strokes and US National Institutes of Health Stroke Scale (NIHSS) scores of 4-22 within 2 weeks of symptom onset; recruitment was performed at 55 sites in China. Patients received CG or aspirin. The primary efficacy end-point was neurological function. Analyses were done by intention to treat. Patients were measured for NIHSS, Montreal Cognitive Assessment, and Mini-Mental State Examination scores and Barthel index at baseline and at 4, 8, and 12 weeks after treatment. RESULTS: Between January 2013 and January 2014, we treated 1963 patients with CG and 1288 patients with aspirin. Baseline NIHSS, Mini-Mental State Examination, and Montreal Cognitive Assessment scores were comparable between the two groups. Patients in the CG group had a greater improvement than the aspirin group in terms of NIHSS (P < 0.01) and Barthel index at 4, 8, and 12 weeks. At 12 weeks, patients in the CG group had a greater improvement than the aspirin group in terms of Mini-Mental State Examination (P < 0.01) and Montreal Cognitive Assessment (P < 0.05). Adverse reactions were similar between the two groups. CONCLUSIONS: This large-scale, controlled trial indicated that CG may be a useful treatment in the management of post-stroke patients.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it