Functional deficit of sense organs as a risk factor for cognitive functional disorder in Chinese community elderly people
Bibliographic record
Abstract
Objective To explore the relationship between mild cognitive impairment (MCI) and sense organs functional deficit in community elderly people. Methods A total of 3095 community elderly people above 60 years in Hebei Province were selected by cross-sectional random cluster sampling method, who were evaluated face-to-face for general demographic data, the condition of sense organs functional deficit (vision, hearing, gustation, olfactory sensation, taste) and cognitive function by Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Results A total of 3075 valid questionnaires were obtained. (a) 1368 old people (44.49%) were defined with sense organs functional deficit (defined as one or more of glaucoma, fundus disease, hearing impairment, olfactory disorder and taste disorder) in 3095 elderly people. According to questionnaires, MCI was diagnosed in 689 of 3075 participants (22.41%). The hearing disorder and glaucoma of MCI group were higher than that of the normal control group (X2 were 5.998 and 7.430, respectively, P were .014 and .006, respectively). (b) The MMSE score of the hearing disorder were significantly lower than those of non-hearing disorder group (t = 2.046, P = .041). (c) Multinomial logistics regression analysis was applied by MCI as the dependent variable and the various sensory organs defects as independent variables. The hearing impairment (Wald = 8.582, P = .003, OR = 1.485, 95% CI: 1.140-1.934) and glaucoma (Wald = 8.020, P = .005, OR = 1.847, 95% CI: 1.208-2.824) were associated with MCI. Conclusion The sensory organs functional defects is associated with the mild cognitive impartment in Chinese elderly, especially in vision and hearing disorder.
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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 | 0.001 | 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) | 0.002 | 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".