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Record W1965133455 · doi:10.3171/spi/2008/8/3/215

Predictive value of intraoperative neurophysiological monitoring during cervical spine surgery: a prospective analysis of 1055 consecutive patients

2008· article· en· W1965133455 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Neurosurgery Spine · 2008
Typearticle
Languageen
FieldMedicine
TopicIntraoperative Neuromonitoring and Anesthetic Effects
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsMedicineIntraoperative neurophysiological monitoringSomatosensory evoked potentialProspective cohort studyElectromyographySurgeryPredictive value of testsAnesthesiaPhysical medicine and rehabilitationInternal medicine

Abstract

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OBJECT: Despite the growing use of multimodal intraoperative monitoring (IOM) in cervical spinal surgery, limited data exist regarding the sensitivity, specificity, and predictive values of such a technique in detecting new neurological deficits in this setting. The authors sought to define the incidence of significant intraoperative electrophysiological changes and new postoperative neurological deficits in a cohort of patients undergoing cervical surgery. METHODS: The authors conducted a prospective analysis of a consecutive series of patients who had undergone cervical surgery during a 5-year period at a university-based neurosurgical unit, in which multimodal IOM was recorded. Sensitivity, specificity, positive predictive values (PPVs), and negative predictive values (NPVs) were determined using standard Bayesian techniques. The study population included 1055 patients (614 male and 441 female) with a mean age of 55 years. RESULTS: The IOM modalities performed included somatosensory evoked potential (SSEP) recording in 1055 patients, motor evoked potential (MEP) recording in 26, and electromyography (EMG) in 427. Twenty-six patients (2.5%) had significant SSEP changes. Electromyographic activity was transient in 212 patients (49.6%), and 115 patients (26.9%) had sustained burst or train activity. New postoperative neurological deficits occurred in 34 patients (3.2%): 6 had combined sensory and motor deficits, 7 had new sensory deficits, 9 had increased motor weakness, and 12 had new root deficits. Of these 34 patients, 12 had spinal tumors, of which 7 were intramedullary. Overall, of the 34 new postoperative deficits, 21 completely resolved, 9 partially resolved, and 4 had no improvement. The deficits that completely resolved did so on average 3.3 months after surgery. Patients with deficits that did not fully resolve (partial or no improvement) were followed up for an average of 1.8 years after surgery. Somatosensory evoked potentials had a sensitivity of 52%, a specificity of 100%, a PPV of 100%, and an NPV of 97%. Motor evoked potential sensitivity was 100%, specificity 96%, PPV 96%, and NPV 100%. Electromyography had a sensitivity of 46%, specificity of 73%, PPV of 3%, and an NPV of 97%. CONCLUSIONS: Combined neurophysiological IOM with EMG and SSEP recording and the selective use of MEPs is helpful for predicting and possibly preventing neurological injury during cervical spine surgery.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.263
Teacher spread0.245 · 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