Parkinson's disease is associated with hippocampal atrophy
Bibliographic record
Abstract
Patients with Parkinson's disease (PD) may have hippocampal atrophy compared with controls. We compared hippocampal, and extra-hippocampal volumes between PD, PDD (patients with PD who have mild cognitive impairment or dementia), Alzheimer's disease (AD) and controls using volumetric magnetic resonance imaging (MRI). Participants (10 patients with PD, 10 with PDD, 11 with AD, and 12 control subjects) had an informant interview, neurological examination, and psychometric testing. Established, reliable methods were used to measure the hippocampus, parahippocampal gyrus, temporal, frontal, and parieto-occipital lobes. Correction for intracranial volume was carried out before comparison. There was no age difference between groups (mean age, 74 years). On the Clinical Dementia Rating scale (CDR) cognitive impairment was mild (CDR = 0.5) in the majority of PDD and AD patients. Hippocampal (P < 0.0004) volumes were smaller in the patient groups. Effect sizes compared with the control group were: PD, 0.66; PDD, 1.22; and AD, 1.81. The other volumes did not differ significantly. Among PD and PDD patients, recognition memory (r = 0.54, P = 0.015) and Mini-Mental State Examination scores (r = 0.56, P = 0.01) correlated with left, but not right hippocampal volume. In conclusion, hippocampal volume showed a pattern (Control > PD > PDD > AD) suggesting progressive hippocampal volume loss in PD. Volumetric MRI imaging might provide an early marker for dementia in 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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".