Does olfactory dysfunction have the same relationship with limbic system integrity in Alzheimer’s and Parkinson’s disease?
Bibliographic record
Abstract
Abstract Background We have demonstrated that olfactory dysfunction is common in Alzheimer’s disease (AD), and is associated with poorer episodic memory performance and medial temporal lobe (MTL) integrity in groups at risk for AD. Olfactory decline is also common in Parkinson’s disease (PD); however, the difference in pathology between these diseases remains poorly understood. Method Using data from the Comprehensive Assessment of Neurodegeneration in Aging (COMPASS‐ND) study, we compared older adults with subjective cognitive decline (SCD; N=55, Mage =70.1, %female=78), mild cognitive impairment (MCI; N=100, Mage =71.2, %female=45) and AD (N=47, Mage =74.8, %female=31) with those at risk for (PD‐MCI; N=25, Mage =71.4, %female=20) and with Parkinson’s disease (PD; N=34, Mage =66.5, %female=44) on measures of olfaction (Brief Smell Identification Test), cognition (episodic, working and semantic memory), and structural MRI (volume and cortical thickness of the MTL and orbitofrontal cortex). All analyses controlled for age, sex, and education; MRI analyses also controlled for total intracranial volume. Result Our analyses revealed that olfactory function was highest in SCD (M=10.33, SD=1.69), and declined in MCI (M=8.84, SD=2.98), and AD groups (M=6.06, SD=2.73) successively. The PD group (M=7.12, SD=2.78) did not differ from PD‐MCI group (M=5.28, SD=3.26), and was in line with the poor performance of the AD participants. These groups had poorer olfactory performance compared to the SCD and MCI groups. Conclusion Olfactory deficits are present in PD participants regardless of MCI. We will also report on whether olfactory function predicts MTL integrity in PD, as it does in individuals at risk for AD.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".