Efficacy and safety of compound porcine cerebroside and ganglioside injection (CPCGI) versus piracetam on cognition and functional outcomes for adults with traumatic brain injury: A study protocol for randomized controlled trial
Bibliographic record
Abstract
Background: Traumatic brain injury (TBI) is a common neurosurgical disease in emergency rooms with poor prognosis, imposing severe burdens on patients and their families. Evidence indicates that piracetam and compound porcine cerebroside and ganglioside injection (CPCGI) can improve cognitive levels in TBI patients to enhance functional prognosis, but there is still a research gap regarding the efficacy of CPCGI. This study aims to determine the effectiveness and safety of CPCGI in improving cognitive and functional outcomes in TBI patients. Methods: This study is a multicenter, randomized, parallel-group, double-blind trial aiming to recruit 900 adult patients with mild to moderate TBI. After providing informed consent, 600 patients will be randomly assigned to the CPCGI group (20 ml/d, for 14 days), and 300 patients will be randomized to the piracetam group as a control (20 ml/d, for 14 days), followed up for 3 months after treatment. The primary outcome is the change in the Montreal Cognitive Assessment (MoCA) score from baseline after 3 months. The main secondary outcome measures include Mini-Mental State Examination (MMSE) scores, Glasgow Outcome Scale-Extended (GOS-E), and the Barthel Index at 1 and 3 months. Discussion: This multi-center clinical trial aims to provide high-quality evidence on the efficacy and safety of CPCGI in improving cognitive and functional outcomes in mild to moderate TBI patients. Trial registration: ChiCTR2000040466, date of registration: November 28, 2020.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.020 | 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".