Relationships between Cognitive Function and Odor Identification, Balance Capability, and Muscle Strength in Middle-Aged Persons with and without Type 2 Diabetes
Bibliographic record
Abstract
AIM: We investigated the relationship between cognitive function and olfactory and physical functions in middle-aged persons with and without type 2 diabetes (T2D) to examine the potential of olfactory and physical functions as biomarkers for early cognitive impairment. METHODS: Enrolled were 70 T2D patients (age 40 to <65 y) and 81 age-matched control participants without diabetes. Cognitive function was assessed by the Montreal Cognitive Assessment (MoCA), Trail Making Test parts A and B (TMT-A/-B), Wisconsin Card Sorting Test (WCST), Quick Inventory of Depressive Symptomatology Self-Report (QIDS), and Starkstein Apathy Scale (SAS). Multiple linear regression analyses were performed. RESULTS: Odor identification was an independent determinant shown in the results of the TMT-A in the entire participant group and was independently associated with the MoCA and TMT-B in the T2D group. Balance capability assessed with a stabilometer was independently associated with all cognitive function tests except for QISD and SAS in the entire participant group and the T2D group and was independently associated with TMT-A in the control group. Knee extension strength was independently associated with the SAS in the entire participant group and the T2D group. CONCLUSIONS: Odor identification, balance capability, and knee extension strength were potential markers for cognitive decline in middle-aged persons with T2D.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".