Malnutrition-related hyperammonemic encephalopathy presenting with burst suppression: a case report
Bibliographic record
Abstract
BACKGROUND: Hyperammonemia is a common cause of metabolic encephalopathy, mainly related to hepatic cirrhosis. Numerous nonhepatic etiologies exist but they are infrequent and not well known, thus, leading to misdiagnosis and inadequate care. Electroencephalography has a proven diagnostic and prognostic role in comatose patients. Burst suppression is a preterminal pattern found in deep coma states and is rarely associated with metabolic causes. CASE PRESENTATION: We report the case of an 81-year-old Caucasian man presenting with rapidly progressive somnolence and mutism. Soon after his arrival in our hospital, he developed profound coma. A comprehensive diagnostic workup was unremarkable except for admission electroencephalography showing diffuse slowing of cerebral activity with an intermittent pattern of burst suppression. He was admitted to our intensive care unit for supportive care where malnutrition-related hyperammonemia was diagnosed. His clinical course was spontaneously favorable and follow-up electroencephalography demonstrated normal cerebral activity. CONCLUSIONS: Nonhepatic hyperammonemia is a rare and potentially reversible cause of encephalopathy. Ammonia level measurement should be part of the diagnostic workup in patients with unexplained coma, particularly in the setting of nutritional deficiencies or nutritional supply. Detection of diffuse and nonspecific mild to moderate slowing of cerebral activity (theta-delta ranges) on electroencephalography is common. In contrast, to the best of our knowledge, burst suppression has never been described in association with hyperammonemia.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".