Acquired hepatocerebral degeneration: clinical characteristics and MRI findings
Bibliographic record
Abstract
OBJECTIVE: To determine the prevalence of acquired hepatocerebral degeneration (AHD), its clinical and neuroimaging characteristics and response to treatments. BACKGROUND: Acquired hepatocerebral degeneration is a chronic encephalopathy with predominant motor signs in the context of severe liver disease. Its clinical picture is not well defined, and its prevalence and risk factors are not well known. METHODS: Review of a database of 1000 patients with cirrhosis to identify cases of AHD. Clinical and neuroimaging data, follow-up and response to treatments, including liver transplantation, were recorded. RESULTS: Eight patients with AHD were identified. Its prevalence was 0.8% of patients with cirrhosis. The main risk factor for AHD was the presence of portosystemic shunts. Movement disorders, especially a combination of parkinsonism and cerebellar signs were observed in all patients. All AHD cases showed on MRI T1-weighted images hyperintensities in the globus pallidus, and 75% had extrapallidal involvement as well. Antiparkisonian drugs and treatments to prevent acute encephalopathies were ineffective. Three patients who underwent liver transplantation did not experience neurological improvement. Persistence of portosystemic shunts was demonstrated in two cases. CONCLUSIONS: Acquired hepatocerebral degeneration is a chronic encephalopathy which occurs in ∼1% of patients with liver cirrhosis and seems related to portosystemic shunts. Its is characterized by a combination of parkinsonism and cerebellar signs. MRI pallidal and extrapallidal lesions are seen in most patients, probably reflecting intracerebral deposits of manganese. Liver transplant did not improve the neurological signs in our patients, perhaps because of the persistence of portosystemic shunts.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".