Association of Qi-stagnation constitution and subjective sleep characteristics with mild cognitive impairment among elderly in community: A cross-sectional study
Bibliographic record
Abstract
Introduction Depression and sleep disturbance are commonly reported in patients with mild cognitive impairment (MCI). However, it remains unclear whether Qi-stagnation constitution is a risk factor for MCI before older adults suffer from depression. Methods Subjects were recruited from 34 community elderly day care centers in China. Intensive face-to-face interviews were conducted using Montreal cognitive function assessment, AD8 dementia screening questionnaire, Pittsburgh Sleep Quality Index (PSQI), and Traditional Chinese medicine constitution assessment scale. Multi-factor logistical regression was employed to analyze the association among subjective sleep quality, TCM constitution, and MCI. Results A total of 1,071 cases were analyzed in this study, including 314 patients with MCI. The probability of those with Qi-deficiency and Qi-stagnation suffering from MCI was 1.559 times and 1.706 times higher than that of the older adults without Qi-deficiency and Qi-stagnation, respectively ( P <0.05). In the PSQI scale, individuals with MCI had poorer subjective sleep quality, longer sleep latency, shorter sleep duration, and aggravated daytime dysfunction ( P <0.05) compared with those without MCI. The results of multi-factor logistical regression showed that sleep latency (OR=1.168), daytime dysfunction (OR=1.261), and Qi-stagnation (OR=1.449) were risk factors for MCI; the OR of suffering from MCI in the elderly with sleep disturbance and Qi-stagnation was 2.581. (all P <0.05). Conclusion MCI patients have a higher prevalence of sleep disorders and Qi-stagnation, and may show specific changes in their daytime and nighttime sleep characteristics, with the specific manifestations such as difficulty in falling asleep, easily waking up at night/ early morning, and daytime dysfunction, among others. Trial Registration Chinese Clinical Trial Registry ChiCTR2000039411
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".