Long-Term Levodopa Use In Normal Substantia Nigra Cases (P3.081)
Bibliographic record
Abstract
Objective: To determine the clinical and pathological profile of levodopa (LD) treated cases that have normal substantia nigra. Background: Parkinson disease (PD) is characterized by a combination of bradykinesia, rigidity, and tremor. Some of those also manifest in other disorders. Definite diagnosis of PD is only possible on pathological studies showing marked substantia nigra neuronal loss. Even in cases carefully selected for drug trials, Dopamine Transporter (DAT) imaging studies are normal in 4 to 15% of cases. While several neurological disorders are known to have normal DAT, most have predominant tremor and are assumed to have essential tremor (ET). There is no autopsy verification of underlying pathology in these cases. Design/Methods: Since 1968, all cases seen at Movement Disorder Clinics Saskatchewan have been offered autopsy at no cost to the family or estate; 491 cases have come to autopsy. Twenty-one individuals that had normal substantia nigra at autopsy and were treated with levodopa were identified. Results: Six cases received LD for < 1 year, six for 1 - 4 years, five for 5 - 10 years, and four for > 10 years. The drug was continued for life in 11 cases for subjective benefit or patient concern of symptomatic worsening. The most common adverse effects were nausea, vomiting, and “feeling sick” in five cases. No cases had objective motor symptom benefit, dyskinesia, or motor response fluctuations. In cases where LD was discontinued, there was no symptom worsening. The most common final diagnosis was ET with or without other pathology in 12 of 15 (80%) long-term treated case. Other diagnoses included ALS, Alzheimer’s disease, and vascular parkinsonism. Conclusions: Patients with normal substantia nigra had no objective symptomatic benefit on levodopa and no dyskinesia or motor response fluctuations. Levodopa is not toxic to substantia nigra.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".