Understanding the Brain-Heart Connection Through a Case of Angry Glioma Syndrome
Bibliographic record
Abstract
We discuss a patient with a tumor on the anterior corpus callosum who underwent open biopsy eventually succumbing to cerebrogenic fatal arrhythmia following wounded glioma syndrome. A healthy 37-year-old female patient was admitted to our department due to a history of headache for 13 months. MRI revealed a suspicious glioma infiltrating the anterior corpus callosum. Neurologic examination only showed low cognitive assessment score (Montreal Cognitive Assessment score 20/30). ECG was normal sinus rhythm. Steroids and levetiracetam were administered prior to operation. Patient underwent right frontal craniotomy and biopsy of tumor with unremarkable events. During the first hospital day, patient had episodes of bradycardia followed by decrease in sensorium. Brain CT scan showed progression of edema without hemorrhage within the tumor bed. This was followed minutes later by two episodes of generalized tonic-clonic seizures and pulseless ventricular tachycardia. Cardiac resuscitation was done for 24 minutes but patient eventually expired. Location of the lesion and the epileptogenicity of the peritumoral cortex greatly contributed to the patient's demise. Involvement of the fronto-mesial structures, particularly the insula and the cingulate cortex, and their connection to the central autonomic network, increased susceptibility to arrhythmias. Decreased seizure threshold worsened post-operative edema, further aggravating the dysregulation of the brain-heart-connection.
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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) | 0.000 | 0.000 |
| 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) | 0.001 | 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".