Unawareness of Hyposmia in Elderly People With and Without Parkinson's Disease
Bibliographic record
Abstract
BACKGROUND: Hyposmia is common in Parkinson's disease (PD) and is also observed with normal aging. It can be ascertained through objective testing, but it is unclear whether patients are aware of deficits and whether this has implications for cognitive status. METHODS: Subjects in the Arizona Study of Aging and Neurodegenerative Disorders were studied with annual motor and cognitive testing with objective smell testing (University of Pennsylvania Smell Identification Test; UPSIT) done every third year beginning in 2002. Those with a baseline UPSIT <25th percentile (hyposmia) were studied for presence of unawareness of hyposmia and cognitive status. RESULTS: There were 75 subjects with PD and 143 nonparkinsonian controls with hyposmia. Lack of awareness of hyposmia was present in 16% of PD subjects and 47% of those without PD. In PD, there was no increase in unawareness in PD with dementia. In non-PD controls, unawareness was correlated with presence of dementia. Unawareness of hyposmia correlated most strongly with the neuropsychiatric tests of learning and memory. In controls without dementia or PD, 48% were unaware. CONCLUSIONS: Querying patients about anosmia might be useful in parkinsonian disorders without objective testing. However, in elderly controls, it should be followed by objective testing and lack of awareness has implications for worsened cognitive status.
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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 | 0.001 | 0.003 |
| 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".