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Record W2937686950 · doi:10.3171/2019.1.spine181110

Investigating the utility of intraoperative neurophysiological monitoring for anterior cervical discectomy and fusion: analysis of over 140,000 cases from the National (Nationwide) Inpatient Sample data set

2019· article· en· W2937686950 on OpenAlex
Jetan H. Badhiwala, Farshad Nassiri, Christopher D. Witiw, Alireza Mansouri, Saleh A. Almenawer, Leodante da Costa, Michael G. Fehlings, Jefferson R. Wilson

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 · 2019
Typearticle
Languageen
FieldMedicine
TopicIntraoperative Neuromonitoring and Anesthetic Effects
Canadian institutionsMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsMedicineAnterior cervical discectomy and fusionPropensity score matchingLogistic regressionRetrospective cohort studyUnivariateIntraoperative neurophysiological monitoringSurgeryMultivariate analysisUnivariate analysisMultivariate statisticsInternal medicineCervical spine

Abstract

fetched live from OpenAlex

OBJECTIVE: Intraoperative neurophysiological monitoring (IONM) is a useful adjunct in spine surgery, with proven benefit in scoliosis-correction surgery. However, its utility for anterior cervical discectomy and fusion (ACDF) is unclear, as there are few head-to-head comparisons of ACDF outcomes with and without the use of IONM. The authors sought to evaluate the impact of IONM on the safety and cost of ACDF. METHODS: This was a retrospective analysis of data from the National (Nationwide) Inpatient Sample of the Healthcare Cost and Utilization Project from 2009 to 2013. Patients with a primary procedure code for ACDF were identified, and diagnosis codes were searched to identify cases with postoperative neurological complications. The authors performed univariate and multivariate logistic regression for postoperative neurological complications with use of IONM as the independent variable; additional covariates included age, sex, surgical indication, multilevel fusion, Charlson Comorbidity Index (CCI) score, and admission type. They also conducted propensity score matching in a 1:1 ratio (nearest neighbor) with the use of IONM as the treatment indicator and the aforementioned variables as covariates. In the propensity score-matched cohort, they compared neurological complications, length of stay (LOS), and hospital charges (in US dollars). RESULTS: A total of 141,007 ACDF operations were identified. IONM was used in 9540 cases (6.8%). No significant association was found between neurological complications and use of IONM on univariate analysis (OR 0.80, p = 0.39) or multivariate regression (OR 0.82, p = 0.45). By contrast, age ≥ 65 years, multilevel fusion, CCI score > 0, and a nonelective admission were associated with greater incidence of neurological complication. The propensity score-matched cohort consisted of 18,760 patients who underwent ACDF with (n = 9380) or without (n = 9380) IONM. Rates of neurological complication were comparable between IONM and non-IONM (0.17% vs 0.22%, p = 0.41) groups. IONM and non-IONM groups had a comparable proportion of patients with LOS ≥ 2 days (19% vs 18%, p = 0.15). The use of IONM was associated with an additional $6843 (p < 0.01) in hospital charges. CONCLUSIONS: The use of IONM was not associated with a reduced rate of neurological complications following ACDF. Limitations of the data source precluded a specific assessment of the effectiveness of IONM in preventing neurological complications in patients with more complex pathology (i.e., ossification of the posterior longitudinal ligament or cervical deformity).

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.241
Threshold uncertainty score0.424

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.084
GPT teacher head0.351
Teacher spread0.266 · 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