Bibliographic record
Abstract
Abstract Background A 42‐year‐old woman presented with a 1‐year history of head tremors, visual hallucinations, and concentration difficulty. On initial evaluation by a neurologist, she was told that her symptoms were due to anxiety, and no further workup was done. After seeking a second opinion, further workup was pursued. Method The patient underwent cognitive testing, with Montreal Cognitive Assessment revealing a normal score of 29/30. MRI Brain revealed a midline frontal meningioma without mass effect. Routine EEG revealed no evidence of seizure tendency. Due to persistent head tremors and visual hallucinations, further testing was considered. Result PET‐FDG CT Brain revealed bilateral parietotemporal and occipital hypometabolism with preserved cingulate gyrus metabolism, consistent with Lewy body dementia. Another PET‐FDG MRI Brain performed 13 months later revealed a similar hypometabolism pattern. Genetic testing revealed a heterozygous mutation for the PRKN gene. Conclusion In this case, a patient showing clinical signs of a potential neurodegenerative disorder was initially dismissed as having anxiety, but further workup with appropriate neurological studies revealed a genetic basis for early‐onset Lewy body dementia. This case demonstrates a unique association with the PRKN gene mutation with Lewy body dementia even though it is typically associated with Parkinson’s disease. This case also highlights the underrepresentation of young patients with neurodegenerative diseases, which is reinforced by biases against pursuing appropriate workup for young patients showing relevant clinical signs.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".