Clinical efficacy of Baijin pills in the treatment of generalized tonic-clonic seizure epilepsy with cognitive impairment
Bibliographic record
Abstract
BACKGROUND The generalized tonic-clonic seizure (GTCS) is the most usual variety of epileptic seizure. It is mainly characterized by strong body muscle rigidity, loss of consciousness, a disorder of plant neurofunction, and significant damage to cognitive function. The effect of antiepileptic drugs on cognition should also be considered. At present, there is no effective treatment for patients with epilepsy, but traditional Chinese medicine has shown a significant effect on chronic disease with fewer harmful side effects and should, therefore, be considered for the therapy means of epilepsy with cognitive dysfunction. AIM To investigate the clinical efficacy of Baijin pills for treating GTCS patients with cognitive impairment. METHODS This prospective study enrolled patients diagnosed with GTCS between January 2020 and December 2023 and separate them into two groups (experimental and control) using random number table method. The control group was treated with sodium valproate, and the experimental group was Baijin pills and sodium valproate for three months. The frequency and duration of each seizure, the Montreal Cognitive Assessment Scale (MoCA), and the Quality of Life Rating Scale (QOLIE-31) were recorded before and after treatment. RESULTS There were 85 patients included (42 in the control group and 43 in the experimental group). After treatment, the seizure frequency in the experimental group was significantly reduced (P < 0.05), and seizure duration was shortened (P < 0.01). The total MoCA score in the experimental group significantly increased compared to before treatment (P < 0.01), and the sub-item scores, except naming and abstract generalization ability, significantly increased (P < 0.05), whereas the total MoCA score in the control group significantly decreased after treatment (P < 0.05). The QOLIE-31 score of the experimental group increased significantly after treatment compared to before treatment (P < 0.01). CONCLUSION Baijin pills have a good clinical effect on epilepsy with cognitive dysfunction.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".