Dopamine transporter imaging is associated with long‐term outcomes in Parkinson's disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Dopamine (DA) transporter (DAT) imaging has been studied as a diagnostic tool for degenerative parkinsonism. Our aim was to measure the prognostic value of imaging for motor and nonmotor outcomes in Parkinson's disease (PD). We prospectively evaluated a Parkinson's cohort after enrollment in a de novo clinical trial with a battery of motor (UPDRS), cognitive (Montreal Cognitive Assessment), and behavioral measures. DAT imaging with [(123)I][β]-CIT and single-photon emission computerized tomography (SPECT) was performed at baseline and after 22 months. In total, 491 (91%) of the 537 subjects had evidence of DA deficiency on their baseline scan, consistent with PD, and were included in the analyses. The cohort was followed for 5.5 (0.8) years, with a mean duration of diagnosis of 6.3 (1.2). Lower striatal binding at baseline was independently associated with higher risk for clinical milestones and measures of disease severity, including motor-related disability, falling and postural instability, cognitive impairment, psychosis, and clinically important depressive symptoms. Subjects in the bottom quartile for striatal binding, compared to the top quartile, had an odds ratio (95% confidence interval) of 3.3 (1.7, 6.7) for cognitive impairment and 12.9 (2.6, 62.4) for psychosis. Change from baseline in imaging after 22 months was also independently associated with motor, cognitive, and behavioral outcomes. DAT imaging with [(123)I][β]-CIT and SPECT, shortly after the diagnosis of PD, was independently associated with clinically important long-term motor and nonmotor outcomes. These results should be treated as hypothesis generating and require confirmation.
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.
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 | 0.000 |
| 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) | 0.000 | 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 it