Striatal dopamine transporter imaging correlates with depressive symptoms and tower of London task performance in Parkinson's disease
Bibliographic record
Abstract
We studied whether the (123)I-FP-CIT uptake in the striatum correlates with depressive symptoms and cognitive performance in patients with Parkinson's disease (PD). Twenty patients with PD without major depression and/or dementia (mean age 61.7 +/- 12.7 years) underwent the (123)I-FP-CIT SPECT. Depressive symptoms and cognitive performance were assessed in the ON state. The ratios of striatal to occipital binding for the entire striatum, putamina, and putamen to the caudate (put/caud) index were calculated in the basal ganglia. The association between neuropsychiatric measures and dopamine transporter (DAT) availability was calculated; multiple regression analysis was used to assess association with age and disease duration. We found significant correlations between Montgomery and Asberg Depression Rating Scale (MARDS) and Tower of London (TOL) task scores and (123)I-FP-CIT uptake in various striatal ROIs. Multiple regression analysis confirmed the significant relationship between TOL performance and put/caud ratio (P = 0.001) and to age (P = 0.001), and between MADRS and left striatal (P = 0.005) and putaminal DAT availability (P = 0.003). Our pilot study results demonstrate that imaging with (123)I-FP-CIT SPECT appears to be sensitive for detecting dopaminergic deficit associated with mild depressive symptoms and specific cognitive dysfunction in patients with PD, yet without a current depressive episode and/or dementia.
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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 | 0.000 | 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".