MétaCan
Menu
Back to cohort

Real-Time Continuous Intraoperative Electromyographic and Somatosensory Evoked Potential Recordings in Spinal Surgery: Correlation of Clinical and Electrophysiologic Findings in a Prospective, Consecutive Series of 213 Cases

2004· article· en· W2018367896 on OpenAlexaff
Þorsteinn Gunnarsson, Andrei V. Krassioukov, Roger Sarjeant, Michael G. Fehlings

Bibliographic record

VenueSpine · 2004
Typearticle
Languageen
FieldMedicine
TopicIntraoperative Neuromonitoring and Anesthetic Effects
Canadian institutionsUniversity of TorontoToronto Western Hospital
Fundersnot available
KeywordsSomatosensory evoked potentialMedicineElectromyographySomatosensory systemIntraoperative neurophysiological monitoringAnesthesiaEvoked potentialCentral nervous system diseaseProspective cohort studySurgeryPhysical medicine and rehabilitationAudiology

Abstract

fetched live from OpenAlex

In Brief Study Design. Retrospective analysis of a prospectively accrued series of 213 consecutive patients who underwent intraoperative neurophysiologic monitoring with electromyography and somatosensory-evoked potentials during thoracolumbar spine surgery. Objectives. To study the incidence of significant intraoperative electrophysiologic changes and new postoperative neurologic deficits. Summary of Background Data. Continuous intraoperative electromyography and somatosensory-evoked potentials are frequently used in spinal surgery to prevent neural injury. However, only limited data are available on the sensitivity, specificity, and predictive values of intraoperative electrophysiologic changes with regard to the occurrence of new postoperative neurologic deficits. Methods. We examined data on patients who underwent intraoperative monitoring with continuous lower limb electromyography and somatosensory-evoked potentials. The analysis focused on the correlation of intraoperative electrophysiologic changes with the development of new neurologic deficits. Results. A total of 213 patients underwent surgery on a total of 378 levels; 32.4% underwent an instrumented fusion. Significant electromyograph activation was observed in 77.5% of the patients and significant somatosensory-evoked potential changes in 6.6%. Fourteen patients (6.6%) had new postoperative neurologic symptoms. Of those, all had significant electromyograph activation, but only 4 had significant somatosensory-evoked potential changes. Intraoperative electromyograph activation had a sensitivity of 100% and a specificity of 23.7% for the detection of a new postoperative neurologic deficit. Somatosensory-evoked potentials had a sensitivity of 28.6% and specificity of 94.7%. Conclusions. Intraoperative electromyographic activation has a high sensitivity for the detection of a newpostoperative neurologic deficit but a low specificity. In contrast, somatosensory-evoked potentials have low sensitivity but high specificity. Combined intraoperative neurophysiologic monitoring with electromyography and somatosensory-evoked potentials is helpful for predicting and possibly preventing neurologic injury during thoracolumbar spine surgery. Spine 2004;29:677–684 We studied 213 patients undergoing thoracolumbar surgery and intraoperative neurophysiologic monitoring. Significant activation of electromyography occurred in 77.5%. Significant somatosensory-evoked potential changes occurred in 6.6% of the patients. The sensitivity of electromyography to detect new postoperative deficits was high, whereas specificity was low. Somatosensory-evoked potentials had low sensitivity but high specificity.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.012
GPT teacher head0.284
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations199
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueSpineSame topicIntraoperative Neuromonitoring and Anesthetic EffectsFrench-language works237,207