Simulation of Brain Death from Fulminant De-efferentation
Bibliographic record
Abstract
BACKGROUND: Guillain-Barré syndrome (GBS) classically presents with a subacutely evolving areflexic paralysis, with typical laboratory findings of elevated cerebrospinal fluid protein and abnormal nerve conduction studies. There is now an increasing recognition of GBS variants that differ in clinical presentation, prognosis, electrophysiology and presumed pathogenesis. Fulminant cases of GBS have been reported in which a rapid deterioration evolves to a clinical state resembling "brain death". METHODS: A retrospective analysis of two such cases of fulminant neuropathy are described, that includes the clinical course, electrophysiology and neuropathology where available. RESULTS: We describe two patients that presented with a rapid course of neurological deterioration, lapsing into what resembled a "clinically brain-dead" state that was subsequently ascribed to a fulminant polyneuropathy. Investigations (electrophysiological, pathological) and the clinical course suggested an axonal neuropathy. CONCLUSIONS: A fulminant neuropathy can result in a clinical state resembling "brain death" through diffuse de-efferentation. Although generally attributed to aggressive demyelination with secondary axonal degeneration, a primary axonopathy can also lead to a similar clinical presentation.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".