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Olfactory Function Predicts Cognitive Deficits and Decline in Early Parkinson's Disease (S5.007)

2016· article· en· W2464409944 on OpenAlexaboutno aff
Michelle Fullard, Baochan Tran, Sharon X. Xie, Christi Scordia, Carly Linder, Rachael Purri, Daniel Weintraub, John E. Duda, Lana M. Chahine, James F. Morley

Bibliographic record

VenueNeurology · 2016
Typearticle
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionParkinson's diseaseDiseaseCognitive declineNeurosciencePsychologyMedicineDementiaAudiologyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the association of baseline olfaction with both cross-sectional and longitudinal assessments of motor symptoms, non-motor symptoms (NMS) and other biomarkers (radiologic, CSF) in early Parkinson’s disease (PD). BACKGROUND: Biomarkers for diagnosis and prognosis remain a major unmet need in PD research and clinical management. Olfactory impairment is common in PD with a prevalence of 70-90[percnt] and is often one of the first manifestations of the disease, which, along with the ease of assessment, make it an attractive predictive biomarker. METHODS: Parkinson’s Progression Marker’s Initiative (PPMI) participants underwent baseline olfactory testing with the University of Pennsylvania Smell Identification Test (UPSIT). Serial assessments included measures of motor symptoms, NMS, neuropsychological assessment, CSF biomarkers, and dopamine transporter (DAT) imaging. Up to three years follow-up data were included. RESULTS: Worse olfaction was associated with more severe NMS, including anxiety and autonomic symptoms. DAT imaging demonstrated a linear trend toward lower uptake in the putamen and striatum in those with worse olfaction. Aβ1-42 was significantly lower in those with worse olfaction, while Tau/Aβ1-42 ratio was higher. In longitudinal analysis, UPSIT score was associated with greater decline over time in Montreal Cognitive Assessment (MoCA) score (β=0.02, p=0.001), as were composite measures of UPSIT score and Aβ1-42 (β= -0.48, p<0.001) or Tau/Aβ1-42 ratio (β= -0.27, p=0.014). In a Cox proportional hazards model, a composite measure of olfaction and Tau/Aβ1-42 ratio was a significant predictor of conversion to mild cognitive impairment (MCI; MoCA<26), with subjects most affected on both measures being 79[percnt] more likely to develop new-onset MCI compared with the least affected subjects (HR=1.79, p=0.02). CONCLUSIONS: Worse baseline olfaction is associated with future cognitive decline and progression to MCI in early PD. The addition of CSF biomarkers to olfactory testing may increase the likelihood of identifying those at highest risk for cognitive decline.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.079
GPT teacher head0.249
Teacher spread0.170 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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