Giant Somatosensory Evoked Potentials Coincident With Epileptiform Discharges in Acutely Comatose Patients
Bibliographic record
Abstract
BACKGROUND: The amplitude of the cortically generated somatosensory evoked potential (SSEP) is used to predict outcome in comatose patients. The relationship between epileptiform discharges and SSEP amplitude has not been elucidated in those patients. METHODS: Bilateral median nerve SSEP and electroencephalograph (EEG) studies were performed in a comatose patient (patient 1) 1 day after cardiac surgery and repeated 4 days later. He had tranexamic acid administered before and during surgery. Another comatose patient (patient 2) had the same studies performed 1 day after sustaining 10 minutes of pulseless electrical cardiac activity. RESULTS: Both comatose patients had epileptiform discharges (on EEG) that were coincident with giant cortically generated SSEPs. In patient 1, the EEG and SSEP studies repeated 5 days postoperatively showed no epileptiform discharges, and the cortically generated SSEP amplitude was decreased (normalized) compared with that obtained one day postoperatively. He emerged from coma and had a good recovery. Patient 2 died shortly after EEG and SSEP testing. CONCLUSIONS: Epileptiform discharges were associated with giant cortically generated median nerve SSEP amplitude (tranexamic acid was implicated in patient 1 and anoxic brain injury in patient 2). Accordingly, those who use the amplitude of cortically generated SSEPs for predicting outcome in comatose patients should consider the presence of epileptiform discharges (detected by EEG) as a potential confounding factor.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".