Clinical and imaging characteristics of Parkinson’s disease with negative alpha-synuclein seed amplification assay
Bibliographic record
Abstract
Abstract Background The CSF alpha-synuclein seed amplification assay (CSFasynSAA) detects alpha-synuclein aggregation in over 90% of individuals with sporadic PD (sPD). However, the clinical characteristics of sPD with negative CSFasynSAA remain undefined. Objectives Describe clinical and neuroimaging characteristics of CSFasynSAA negative sPD individuals in the Parkinson’s Progression Markers Initiative (PPMI). Methods We identified sPD PPMI participants with a negative CSFasynSAA (SAA negative, n=80) or positive CSFasynSAA (SAA positive, n=856) result at baseline. For comparative analysis between groups we used a reduced dataset (n=79 SAA negative and n=237 SAA positive) propensity-score matched on age, sex, and time since clinical diagnosis. Clinical parameters, DAT-SPECT, and MRI brain volumetrics were analyzed. Results The SAA negative and matched SAA positive groups had similar motor performance on the MDS-UPDRS-part III and similar cognitive performance on the MoCA at baseline. The proportion with severe hyposmia was 12% for SAA negative versus 73% for SAA positive ( p < 0.001). Per PPMI enrollment criteria all participants were classified as having an abnormal DAT-SPECT. There were no significant differences in median quantitative DAT-SPECT measures between groups. The SAA negative group showed a higher degree of atrophy in subcortical brain regions including substantia nigra. Longitudinally, 14.3% of SAA negative participants had a change in diagnosis, versus 0.9% of SAA positive participants. Conclusions At baseline, SAA negative sPD PPMI participants have a substantially lower rate of hyposmia, but otherwise cannot be readily distinguished from SAA positive participants based on clinical characteristics. However, SAA negative participants have a greater degree of subcortical brain atrophy, and approximately 1 out of 6 SAA negative participants received a change in diagnosis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".