Cognition in Patients With a Clinical Diagnosis of Parkinson Disease and Scans Without Evidence of Dopaminergic Deficit (SWEDD): 2-Year Follow-Up
Bibliographic record
Abstract
OBJECTIVE AND BACKGROUND: More than 10% of patients clinically diagnosed with Parkinson disease demonstrate normal dopamine uptake on dopamine transporter single-photon emission computed tomography (DaTscan), but little is known about how cognitive function differs between patients with dopamine deficiency on DaTscan and patients with scans without evidence of dopaminergic deficit (SWEDD). We compared the cognitive function of these two groups of patients over 2 years. METHODS: We retrospectively analyzed data obtained from the Parkinson's Progression Markers Initiative on 309 participants clinically diagnosed with idiopathic Parkinson disease who had scored in the normal range on the Montreal Cognitive Assessment at baseline and had completed 1- and 2-year follow-up visits. We compared the Montreal Cognitive Assessment scores at 1 and 2 years between the 42 participants with SWEDD and the 267 with dopamine deficiency. RESULTS: Mean cognitive scores did not differ significantly between groups at 1 year, but at 2 years the participants with SWEDD performed more poorly. At 2 years, 31% of the participants with SWEDD versus 15% of those with dopamine deficiency had statistically reliable cognitive impairment. CONCLUSIONS: This study provides evidence that some individuals clinically diagnosed with idiopathic Parkinson disease but with SWEDD demonstrate early cognitive decline. The results also suggest that recently diagnosed patients with SWEDD may be at even greater risk for cognitive decline than patients with DaTscan-confirmed early-stage Parkinson disease. While patients with SWEDD likely represent a heterogeneous group of etiologies, our results highlight the need to monitor these patients' cognitive function over time.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".