An Evaluation of Rapidly Progressive Dementia Culminating in a Diagnosis of Creutzfeldt–Jakob Disease
Bibliographic record
Abstract
Rapidly progressive dementia is a curious and elusive clinical description of a pattern of cognitive deficits that progresses faster than typical dementia syndromes. The differential diagnosis and clinical workup for rapidly progressive dementia are quite extensive and involve searching for infectious, inflammatory, autoimmune, neoplastic, metabolic, and neurodegenerative causes. We present the case of a previously highly functional 76-year-old individual who presented with a 6-month history of rapidly progressive dementia. His most prominent symptoms were cognitive impairment, aphasia, visual hallucinations, and ataxia. Following an extensive battery of tests in hospital, the differential diagnosis remained probable CJD versus autoimmune encephalitis. He clinically deteriorated and progressed to akinetic mutism and myoclonus. He passed away 8 weeks after his initial presentation to hospital, and an autopsy confirmed a diagnosis of sporadic CJD. We use this illustrative case as a framework to discuss the clinical and diagnostic considerations in the workup for rapidly progressive dementia. We also discuss CJD and autoimmune encephalitis, the two main diagnostic possibilities in our patient, in more detail.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".