Hemorragic presentation of Listeria Monocytogenes rhombencephalic abscess
Bibliographic record
Abstract
Listeria monocytogenes (LM) bacterium is a cause of central nervous system (CNS) infection and the most common cause of rhombencephalitis in immunocompetent elderly. A prompt identification of this condition should be always desirable, since its clinical manifestations are often unspecific with prodromal symptoms leading to high rates of morbidity and mortality if underestimated. CNS listeriosis magnetic resonance imaging (MRI) findings are generally not specific. However, in the appropriate clinical setting, focal brainstem hyperintensity on T2-weighted pulse sequences associated with ring-enhancement pattern after i.v. contrast media injection should be suspicious of LM abscess. The diagnosis cannot exempt from anamnestic-clinical investigation data correlation to exclude mimicking. We report the case of a 72-year-old man with fever, headache, vomiting, and persistent hiccups with an increasing walking difficulty. A progressive worsening of the state of consciousness led him to a stupor state. Brain MRI examination detected multiple rhombencephalic abscesses. Among these, one was with atypical hemorrhagic presentation. The presence of hemorrhage, uncommon for listeria abscesses, may further complicate their detection, with consequent delayed treatment. The diagnostic hypothesis was confirmed by cerebrospinal fluid examination, which was confident with LM infection. Clinical and neuroradiological state improved after antibiotic therapy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".