Verification of the association between cognitive decline and olfactory dysfunction using a DEmentia screening kit in subjects with Alzheimer's dementia, mild cognitive impairment, and normal cognitive function (DESK study): A multicenter, open-label, interventional study
Bibliographic record
Abstract
Background and purpose: Olfactory dysfunction may be an early symptom of degenerative neurological disorders such as mild cognitive impairment (MCI), which may progress to cognitive decline and Alzheimer's disease (AD). We investigated the relationship between cognitive decline and olfactory dysfunction in healthy controls and patients with MCI or AD using the DEmentia Screening Kit (DESK), an olfactory identification assessment tool designed for Japanese populations. Methods: In this multicenter, open-label, interventional study conducted from 16 September 2020 to 30 April 2021, participants underwent olfactory tests using the DESK tool. This included 10 odorants at two concentrations (weak/strong) including toothpaste, butter, and India ink. Results: Among 223 participants, 100, 61, and 62 were healthy controls, MCI patients, and AD patients (mean ages, 57.4, 72.8, and 76.3 years; total DESK olfaction scores, 18.4, 14.7, and 7.4), respectively. Significant differences in total olfaction scores were observed between groups (healthy controls vs MCI, healthy controls vs AD, and MCI vs AD). Significant between-group total score differences were shown for olfaction scores with both the 10 strong and 10 weak odorant varieties. Conclusion: The DESK tool may discriminate between healthy individuals and those with MCI or AD, facilitating early screening for cognitive decline among Japanese patients, although the effect of age on DESK olfaction scores has not been fully explored.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".