Corticobasal degeneration or hepatic encephalopathy, False positive and/or congruence between clinic and PET‐FDG imaging
Bibliographic record
Abstract
Abstract Background to put into perspective the relative clinical evidence meeting the criteria of corticobasal degeneration but modified by the treatment of a metabolic disease Method Multidisciplinary clinical follow‐up of a patient meeting the cognitive, speech and neurological criteria for a degenerative disease by documenting the evolution of both functional, cognitive and functional imaging during the treatment of hepatic encephalopathy Result Pt of 82 y/o presents with a deterioration over 6 months of a left extrapyramidal syndrome with dystonia of this hemibody, with a dysphasia‐dysphonia spastic and ataxic documented in speech therapy compatible with corticobasal degeneration. MRI shows mild leukoaraiosis, The FDG PET‐Scan is also compatible with corticobasal degeneration. EEG done for abnormal movements is suggestive of hepatic encephalopathy in the absence of laboratory abnormality except for a very slight increase in ammonia. Ultrasound suggests the onset of liver disease. After 6 months of treatment of encephalopathy there is a slight clinical improvement. After one year of treatment the patient becomes totally autonomous with complete regression of neurological signs, dysexecutive disorders and social cognition deficits and PET‐FDG has normalized. 36 months later he is totally autonomous and is back to works as a historical tour guide. Conclusion It is impossible for us after 36months of follow‐up to determine whether the metabolic disease has unmasked a degenerative disease early or has simulated it. We review some possible false positive situations on FDG PET‐Scan. DAT‐Scan will be done.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".