False-Negative Transcranial Motor-Evoked Potentials During Scoliosis Surgery Causing Paralysis
Bibliographic record
Abstract
In Brief Study Design. Case report. Objective. To report a case of false-negative intraoperative motor-evoked potentials (MEP) that developed paraplegia after surgery. Summary of Background Data. Although several false-negative results have been reported with somatosensory-evoked potentials, there is no report noted with MEP. Therefore, several authors have preferred using MEPs as a gold standard in neuromonitoring. Methods. We report a case of false-negative MEP during the scoliosis surgery which is the first report showing false-negative MEPs during operation. Results. A 15-year-old girl with severe kyphoscoliosis (Cobb angle, 140°) in neurofibromatosis was operated for correction and posterior spinal fusion surgery, using pedicle screw instrumentation. Intraoperative neuromonitoring did not show any change in MEPs throughout the procedure, however, she woke-up with paraplegia. Immediate implant release could not recover her neurology functionally at last follow-up. Positive event during the operation was massive blood loss which could not show drop in MEPs as an ischemic cord injury (probable cause). Postoperative CT scan in both patients did not show any injury with pedicle screw as implants were well placed within the pedicles. Reviewing the literature, we could not find out any prospective study in animals identifying false-negative results with MEPs. Conclusion. From our experience of false-negative MEPs, we conclude that unwanted events with use of MEP in scoliosis or other spinal surgeries. We propose further prospective research on animals to solve this issue. We report a case of false-negative motor-evoked potentials (MEP) during the scoliosis surgery. A 15-year old girl with severe kyphoscoliosis was operated for correction with transcranial-MEP monitoring. Transcranial-MEP were maintained throughout surgery, however, she woke-up with paraplegia. Immediate release of construct could not recover neurology at final follow-up.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".