Nonmotor-Related Quality of Life in Parkinson’s Patients with Subjective Memory Complaints: Comparison with PDQ-39
Bibliographic record
Abstract
BACKGROUND: Parkinson's disease (PD) is associated with cognitive decline, progressing from subjective memory complaints (SMC) via mild cognitive impairment (MCI) to dementia. SMC are only measurable by an interview and thus rely on individuals reporting a subjectively perceived worsening of cognitive functioning. Cognitive decline is accompanied by a reduction in quality of life (QoL); however, the extent to which SMC manifest a reduction of QoL remains unclear. OBJECTIVE: To determine the association between SMC and deterioration of QoL in patients suffering from PD. METHODS: A total of 46 cognitively unimpaired PD patients (29 men and 17 women) completed PDQ-39, two assessments to measure SMC (Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) and a Self-Assessment questionnaire), Beck Depression Inventory (BDI), and Beck Anxiety Inventory (BAI). Multiple regression modelling was conducted to investigate the confounding effect of depression and anxiety. RESULTS: = 0.55). CONCLUSION: In our study, SMC is significantly related to a reduction of cognitive QoL. In addition, we observed significant relation to anxiety and depression levels. In contrast to our main hypothesis, we found no association with overall QoL; this lack of association could be due to unstandardized questionnaires and emphasizes the need of validated tools for evaluating SMC.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Study of quality of life and memory complaints in Parkinson's patients; the call for validated tools is a clinical instrument note, not metaresearch.
This studies quality of life and memory complaints in Parkinson’s patients, not research itself.
Clinical study linking Parkinson's subjective memory complaints to quality of life; patient outcomes, not research practice.
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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".