Pembrolizumab-Induced Meningoencephalitis: A Brain Autopsy Case
Bibliographic record
Abstract
Encephalitis is very rare, but often fatal immune-related adverse event (irAE) of immune checkpoint inhibitors (ICIs). A 65-year-old Japanese woman was admitted to our hospital because of general fatigue, chillness and high-grade fever for 4 days, 8 months after the initiation of the first-line pembrolizumab monotherapy for metastatic pulmonary adenocarcinoma. On the hospital day 3, she suddenly presented delirium and uncontrollable impaired consciousness. Although the magnetic resonance imaging (MRI) did not suggest a diagnosis of encephalitis and meningitis, the spinal fluid showed abnormally elevated levels of protein (317.6 mg/L) and cell count (197 cells/µL) with increased mononuclear cells (93%). An empirical and intravenous administration of acyclovir in doses of 10 mg/kg body weight every 8 h and steroid pulse therapy in dose of 1 g/body/day from the hospital day 5 until her death failed to improve her conditions. She died on the hospital day 8. The postmortem autopsy showed viable cancer cells in the metastatic tumor in the left occipital lobe and in the spinal fluids. However, many inflammatory cells infiltration in the meninges and perivascular cuffing were prominent especially in the brain stem and medial part of the temporal lobe. Infiltrating lymphocytes in the meninges and parenchyma of the brain stem were mainly composed of cluster of differentiation (CD)8-positive lymphocytes. For irAE encephalitis, early recognition of early signs and symptoms and subsequent early therapeutic intervention are necessary. It is important for oncologists to keep in mind of the possible adverse effects of immunotherapies on the nervous system.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".