Effects of dopaminergic depletion and brain atrophy on neuropsychiatric symptoms in de novo Parkinson’s disease
Bibliographic record
Abstract
BACKGROUND: Neuropsychiatric symptoms impact the patients' quality of life and caregivers' burdens in Parkinson's disease (PD). We aimed to investigate the effects of striatal dopaminergic depletion and brain atrophy on the neuropsychiatric symptoms of patients with PD. METHODS: Two hundred and seven patients with de novo drug-naïve PD underwent dopamine transporter (DAT) positron emission tomography and brain MRI scanning. In addition, the patients were assessed with caregiver-administered neuropsychiatric inventory (NPI) questionnaires. To evaluate the effects of DAT uptake, subcortical volume and cortical thinning on the patients' neuropsychiatric symptoms, we performed logistic regression and negative binomial regression analyses on the NPI data after controlling for possible confounders. RESULTS: Frontal cortical thinning was associated with the presence of nighttime behaviour and irritability, and the thinning correlated with the severity of the nighttime behaviour. Temporal cortical thinning was associated with the presence of aggression/agitation, and it correlated with the severity of the aggression/agitation. Subcortical atrophy in the accumbens was associated with the presence of disinhibition and correlated with the severity of the disinhibition. Putamen atrophy and insular thinning were independently associated with the presence of apathy, but only insular thinning correlated with the severity of the apathy. Of the predictors, only frontal cortical thinning correlated with the total NPI score. CONCLUSIONS: The results of this study suggested that accumbens atrophy and frontotemporal cortical thinning, especially frontal cortical thinning, independently contributed to neuropsychiatric symptoms in patients with PD, while DAT uptake did not affect the neuropsychiatric symptoms.
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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 | 0.000 |
| 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) | 0.001 | 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".