Clinical observation of hyperbaric oxygen combined with Buyang Huanwu decoction on the treatment of cognitive impairment in patients with acute cerebral infarction
Bibliographic record
Abstract
Objective To observe the clinical efficacy and safety of hyperbaric oxygen combined with Buyang Huanwu decoction on the treatment of cognitive impairment in patients with acute cerebral infarction. Methods120 acute cerebral infarction patients with cognitive impairment were randomly divided into treatment group and control group. 60 cases in control group were treated by hyperbaric oxygen therapy,60 cases of the treatment group received hyperbaric oxygen combined with Buyang Huanwu decoction treatment,After two courses the clinical efficacy of two groups were compared by MMSE,ADL and NIHSS. Results The total effective rate of treatment group is significantly higher than the control group. After treatment MMSE,ADL score in the treatment group was significantly higher than the control group,the NIHSS score was significantly lower than that of the latter( P 0. 05); after treatment,the treatment group plasma viscosity,fibrinogen was significantly lower than that of the control group,the prothrombin time,thrombin time and activated partial thromboplastin time was significantly higher than the latter. Conclusion Hyperbaric oxygen combined with Buyang Huanwu decoction can effectively improve the cognitive impairment in acute cerebral infarction patients ischemic brain damage state,so as to contribute to the recovery of cognitive function,and has important significance to improve the ability of daily life of patients,and good security,no obvious side effect,is worthy of clinical application.
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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".