Neuroimaging and plasma biomarker differences and commonalities in Lewy body dementia subtypes
Bibliographic record
Abstract
Abstract INTRODUCTION Despite ongoing debate about whether Parkinson’s disease dementia (PDD) and dementia with Lewy bodies (DLB) are separable diseases or a single Lewy body dementia (LBD) spectrum, there are limited neuroimaging investigations of differences between these conditions. METHODS We used fixel-based diffusion MRI and plasma measures to examine white matter integrity and burden of amyloid pathology (using tau phosphorylated at theonine-217 (p-tau217) in 47 patients with DLB, 21 PDD, 29 PD and 23 age-matched controls. RESULTS We show reduced fibre cross-section in LBD versus PD, and increased concentrations of plasma neurofilament light chain and p-tau217; with p-tau217 and fibre cross-section associated with cognition. Fibre density was reduced in PDD versus DLB, but neither plasma measures nor fibre cross-section differed between LBD subtypes. DISCUSSION Our findings suggest differences in white matter integrity between DLB and PDD that are driven by distinct processes from those causing changes in white matter integrity in LBD compared with PD.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".