Differences in Olfactory Performance and Neuropsychiatric Symptoms in Subjective Cognitive Decline
Bibliographic record
Abstract
BACKGROUND: The presence of olfactory dysfunction and neuropsychiatric symptoms, such as anxiety and depression, is believed to be strongly associated with the progression from mild cognitive impairment (MCI) to Alzheimer's Disease (AD). However, less is known if such impairments are already present in subjective cognitive decline (SCD) - a preclinical stage of AD characterized by self-reported memory complaints and no objective cognitive deficits on standard neuropsychological tests. This study aims to characterize olfactory function, anxiety, and depression in individuals with SCD, compared to healthy controls. METHOD: A total of 110 participants aged 60 and older were recruited, including 59 with SCD (42 women) and 51 healthy controls (35 women). Participants completed anxiety (GAI) and depression (GDS) questionnaires and underwent olfactory testing with the Sniffin' Sticks battery (threshold, discrimination, and identification). RESULT: The SCD group exhibited significantly lower global olfactory performance than controls. Anxiety and depression scores were significantly higher in the SCD group compared to healthy controls. No significant differences were found in specific olfactory submeasures. Combining global olfactory performance with anxiety and depression scores improved SCD status prediction and classification accuracy. CONCLUSION: These findings highlight subtle but significant and objective lower olfactory performance in individuals with SCD. Olfactory event related potentials should be explored to better understand possible underlying neurophysiological mechanisms.
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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 | 0.000 |
| Science and technology studies | 0.000 | 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, 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".