Efficacy of Combined XingZhi‐YiNao Granules and Hyperbaric Oxygen Therapy for Cognition and Motor Dysfunction in Patients with Delayed Encephalopathy after Acute Carbon Monoxide Poisoning
Bibliographic record
Abstract
Purpose. To investigate the efficacy of XingZhi‐YiNao (XZYN) granules and hyperbaric oxygenation (HBO) for cognition and motor dysfunction in patients with delayed encephalopathy after acute carbon monoxide poisoning (DEACMP). Methods. Eighty‐nine patients with DEACMP were randomly divided into control group (n = 19), HBO group (n = 32), and XZYN group (n = 38). All patients received conventional treatment. HBO group received HBO therapy once daily. XZYN group received extra XZYN granules plus HBO treatment. The related indexes including activity of daily living (ADL) scale, Montreal cognitive assessment (MoCA) scale, and mini mental state examination (MMSE) scale were measured. Cerebral white matter injury, age related white matter changes (ARWMC) scale, and the amplitude and latency of P300 were assessed. Results. Compared with control group, the neurological function scores of ADL, MoCA, and MMSE in HBO and XZYN groups were significantly improved, the impairment degree of brain white matter and cognition function were obviously alleviated, the latencies of P300 were significantly shortened, and the amplitudes of P300 were evidently increased (P < 0.05). Treatment efficacy of XZYN group was superior to that of HBO group (P < 0.05). Conclusion. Combined XZYN granules and HBO can significantly improve cognition and motor functions in patients with DEACMP.
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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 | 0.000 |
| 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) | 0.000 | 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 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".