Neocortical Lewy Body Pathology Parallels Parkinson's Dementia, but Not Always
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to evaluate the relationship between Parkinson's disease (PD) with dementia and cortical proteinopathies in a large population of pathologically confirmed patients with PD. METHODS: We reviewed clinical data from all patients with autopsy data seen in the Movement Disorders Center at Washington University, St. Louis, between 1996 and 2019. All patients with a diagnosis of PD based on neuropathology were included. We used logistic regression and multivariate analysis of covariance (MANCOVA) to investigate the relationship between neuropathology and dementia. RESULTS: A total of 165 patients with PD met inclusion criteria. Among these, 128 had clinical dementia. Those with dementia had greater mean ages of motor onset and death but equivalent mean disease duration. The delay between motor symptom onset and dementia was 1 year or less in 14 individuals, meeting research diagnostic criteria for possible or probable dementia with Lewy bodies (DLB). Braak Lewy body stage was associated with diagnosis of dementia, whereas severities of Alzheimer's disease neuropathologic change (ADNC) and small vessel pathology did not. Pathology of individuals diagnosed with DLB did not differ significantly from that of other patients with PD with dementia. Six percent of individuals with PD and dementia did not have neocortical Lewy bodies; and 68% of the individuals with PD but without dementia did have neocortical Lewy bodies. INTERPRETATION: Neocortical Lewy bodies almost always accompany dementia in PD; however, they also appear in most PD patients without dementia. In some cases, dementia may occur in patients with PD without neocortical Lewy bodies, ADNC, or small vessel disease. Thus, other factors not directly related to these classic neuropathologic features may contribute to PD dementia. ANN NEUROL 2023;93:184-195.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".