Cognitive Complaints in Nondemented Parkinson’s Disease Patients and Their Close Contacts do not Predict Worse Cognitive Outcome
Bibliographic record
Abstract
OBJECTIVES: The main purpose of this study was to investigate 4 methods of eliciting subjective cognitive complaints (SCCs) in Parkinson's disease (PD) patients without dementia and determine the relationship between their SCC and cognitive performance. DESIGN: This study was a retrospective analysis of a prospective cohort study. SETTING: Six North American movement disorder clinics. MEASUREMENTS: SCCs were elicited through a modified Neurobehavioral Inventory administered to patients and close contacts, a general complaint question, and Movement Disorders Society Unified Parkinson's Disease Rating Scale item question 1.1 administered to patients. Clinical evaluation, formal neuropsychological testing and Disability Assessment for Dementia were conducted in Ontario state. Agreement between SCCs eliciting methods was calculated. Associations between SCC, cognitive testing, and mild cognitive impairment (MCI) were assessed. RESULTS: Of 139 participating nondemented PD patients, 42% had PD-MCI at baseline. Agreement between SCC eliciting methods was low. Neither patient-reported nor close contact-reported SCCs were associated with impaired baseline cognitive testing or PD-MCI nor were they associated with cognitive decline over time. In PD patients with normal baseline cognition, 26% of patients with 1-year follow-up and 20% of patients with 2-year follow-up met MCI criteria. CONCLUSIONS: Agreement between SCC eliciting methods is poor and no SCC method was associated with cognitive testing or decline over time. With no clear superior method for eliciting SCCs, clinicians should consider performing regular screening.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".