Neural correlates of self‐awareness of cognitive deficits in non‐demented patients with Parkinson's disease
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The aim was to investigate the neural correlates of impaired self-awareness of cognitive deficits (IACd) in non-demented patients with Parkinson's disease (PD). METHODS: This cross-sectional study enrolled 153 drug-naïve and non-demented PD patients who underwent brain magnetic resonance imaging, dopamine transporter (DAT) positron emission tomography, detailed neuropsychological testing, and the Cognitive Complaints Interview at baseline. Based on the presence of mild cognitive impairment and subjective cognitive complaints, patients were grouped into those with IACd (PD-IACd+, n = 33) and those with normal recognition of cognitive function (n = 82) or underestimation of cognitive function (n = 38). Cortical thickness, white matter (WM) integrity, DAT availability and cognitive function were compared between the groups. RESULTS: The prevalence of IACd was 21.6% in drug-naïve patients with PD. The PD-IACd+ group had a lower z-score in the Stroop color reading test than the other groups. Patients in the PD-IACd+ group had WM disintegrity, especially in the genu of the corpus callosum and anterior limb of the internal capsule, compared to those without IACd, whilst cortical thickness or striatal DAT availability was comparable regardless of the presence of IACd. Amongst patients with mild cognitive impairment, those with IACd had more severe WM disintegrity than those without IACd. CONCLUSION: Structural connectivity between and from the frontal lobes is closely associated with self-awareness of cognitive deficits in PD. Evaluating frontal structural connectivity from the early stages of PD will be important in assessing the actual cognitive and daily life performance of patients with PD.
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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 | 0.000 | 0.001 |
| 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".