The Effect of <i>Dangguijagyag-san</i> on Mild Cognitive Impairment
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to evaluate the safety and the effect of dangguijagyag-san (DJS) on mild cognitive impairment (MCI). METHODS: This study examined the administration of DJS ([Formula: see text]; angelica and peony formula) and was conducted at Uijeongbu Health Center in Gyeonggi-do, Korea, in 2013. Ninety-five of 118 patients diagnosed with MCI were followed up for 1 year after the study ended, and their medical records were analyzed. RESULTS: The patients included 36 men (37.9%) and 59 women (62.1%). When the results from before the study began were compared with the results 1 year after the study ended, the overall average score according to the Korean-Montreal Cognitive Assessment (K-MOCA) showed a statistically significant increase, from 15.46 ± 5.30 to 18.54 ± 5.11, respectively. Both male and female patients recorded a significant increase in K-MOCA scores for all sections, including the visuospatial/executive section, the naming section, the attention section, the language section, the abstraction section, the delayed recall section, and the orientation section. Scores assessed by the Mini-Mental State Examination for Dementia Screening (MMSE-DS) showed a statistically significant increase, from 21.84 ± 3.59 before the study to 24.43 ± 3.13 after the study, but decreased slightly to 23.04 ± 3.36 at the 1-year follow-up. However, MMSE-DS scores measured before the study began increased significantly when compared with scores measured 1 year after the study ended. CONCLUSIONS: DGJYS improved the cognitive skills of patients diagnosed with MCI, and no adverse effects were observed. In the future, the efficacy of DGJYS must be objectively verified by using a randomized controlled trial.
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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) | 0.000 | 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".