Repeated L5 Nerve Root Compromise Detected with Motor Evoked Potentials (MEP), but Not Electromyography (EMG): A Case Report
Bibliographic record
Abstract
We report a case where neuromonitoring, using motor evoked potentials (MEP), detected an intraoperative L5 nerve root deficit during a lumbosacral decompression and instrumented fusion procedure. Critically, the MEP changes were not preceded nor accompanied by any significant spontaneous electromyography (sEMG) activity. Presumptive L5 innervated muscles, including tibialis anterior (TA), extensor hallucis longus (EHL) and gluteus maximus, were targets for nerve root surveillance using combined MEP and sEMG techniques. During a high-grade spondylolisthesis correction procedure, attempts to align a left-sided rod resulted in repeated loss and recovery cycles of MEP from the TA and EHL. No accompanying EMG alerts were associated with any of the MEP changes nor were MEP variations seen from muscles innervated above and below L5. After several attempts, the rod alignment was achieved, but significant MEP signal decrement (72% decrease) remained from the EHL. Postoperatively, the patient experienced significant foot drop on the left side that recovered over a period of 3 months. This case contributes to a growing body of evidence that exclusive reliance on sEMG for spinal nerve root scrutiny can be unreliable and MEP may provide more dependable data on nerve root patency.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.003 |
| 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".