Octogenarian parkinsonism – Clinicopathological observations
Bibliographic record
Abstract
BACKGROUND: Parkinson's disease is the second most common neurodegenerative disorder for which old age is the best known risk. The proportion of elderly in the world is increasing, resulting in larger pool of people at risk for Parkinson's disease. Several other neurodegenerative disorders also produce Parkinson syndrome. Distinguishing between those variants is only possible with pathological examination of brain. No autopsy confirmed study of 80 years and older onset in parkinsonism cases has been reported. Clinical features of different PS variants, response to treatment and progression of disease in this age group remain to be determined. METHODS: Patients evaluated at Movement Disorders Clinic Saskatchewan are offered a choice of autopsy at no cost. The brain is studied by board certified neuropathologist. RESULTS: Thirty cases with clinical diagnosis of parkinsonism (onset ≥80 years) came to autopsy. Twenty-one (70%) had Parkinson's disease alone and two (6.7%) had an additional movement disorder. The progression of Parkinson's disease was accelerated, and dementia evolved earlier than reported in the younger onset cases. Most cases that tolerated an adequate dose improved on levodopa. CONCLUSION: Parkinson's disease is the most common variant in the octogenarian population. Most patients benefit from levodopa, and should be tried on the drug when diagnosis of parkinsonism is made.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".