Olfactory Threshold Test as a Quick Screening Tool for Cognitive Impairment: Analysis of Two Independent Cohorts
Bibliographic record
Abstract
BACKGROUND: Olfactory dysfunction appears prior to cognitive decline, and thus it has been suggested to be an early predictor of Alzheimer's disease. However, it is currently not known whether and how olfactory threshold test could serve as a quick screening tool for cognitive impairment. OBJECTIVE: To define olfactory threshold test for screening cognitive impairment in two independent cohorts. METHODS: The participants are comprised of two cohorts in China, 1,139 inpatients with type 2 diabetes mellitus (T2DM, Discovery cohort) and 1,236 community-dwelling elderly (Validation cohort). Olfactory and cognitive functions were evaluated by Connecticut Chemosensory Clinical Research Center test and Mini-Mental State Examination (MMSE), respectively. Regression analyses and receiver operating characteristic (ROC) analyses were carried out to determine the relation and discriminative performance of the olfactory threshold score (OTS) regarding identification of cognition impairment. RESULTS: Regression analysis showed that olfactory deficit (reducing OTS) was correlated with cognitive impairment (reducing MMSE score) in two cohorts. ROC analysis revealed that the OTS could distinguish cognitive impairment from cognitively normal individuals, with mean area under the curve values of 0.71 (0.67, 0.74) and 0.63 (0.60, 0.66), respectively, but it failed to discriminate dementia from mild cognitive impairment. The cut-off point of 3 showed the highest validity for the screening, with the diagnostic accuracy of 73.3% and 69.5%. CONCLUSION: Reducing OTS is associated with cognitive impairment in T2DM patients and the community-dwelling elderly. Therefore, olfactory threshold test may be used as a readily accessible screening tool for cognitive impairment.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".