Somatosensory Evoked Potential Monitoring During Carotid Endarterectomy in Patients with a Stroke
Bibliographic record
Abstract
UNLABELLED: The aim of our study was to assess the characteristics and feasibility of somatosensory evoked potential (SSEP) monitoring in patients who have had a stroke undergoing carotid endarterectomy. We retrospectively reviewed the medical and SSEP records of 204 patients. The patients were divided into two groups: Stroke (n = 65) and No-Stroke (n = 139). The amplitude and latency of the N20-P25 cortical complex on the ipsilateral side (surgical) were compared with the contralateral side in each group and between groups. Stroke patients showed asymmetry of their cortical waveforms; the ipsilateral N20-P25 baseline amplitude was 1.5 +/- 1.0 microv versus 1.9 +/- 1.2 microv for the contralateral (P = 0.001), for No-Stroke patients 2.0 +/- 1.1 microv versus 2.1 +/- 1.1 microv (P = 0.2). Forty-eight percent of Stroke patients had a ratio (ipsilateral/contralateral amplitude) of <1.0 +/- 0.2 compared with 26% for No-Stroke patients (P = 0.01). There were no differences in latency measurements, in the incidences of significant SSEP changes (four Stroke, six No-Stroke) and immediate postoperative neurological deficits (two Stroke, six No-Stroke) between the two groups. Nine patients (three Stroke, six No-Stroke) had a decrease in ipsilateral N20-P25 amplitude >50% after cross-clamping, and had a shunt inserted. In conclusion, patients with a history of a stroke before surgery had a decrease in the amplitude of the ipsilateral cortical peak. There were no differences in the incidences of SSEP changes or neurological deficits. IMPLICATIONS: Patients who have had a preoperative stroke may show asymmetry of their cortical baseline somatosensory evoked potential waveforms; however, this does not interfere with the ability to use somatosensory evoked potential as a monitor during surgery.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".