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Record W4415962671 · doi:10.1227/neu.0000000000003838

Use of an Expert Panel for Symptomatic Patients With Grade I Degenerative Lumbar Spondylolisthesis: A Randomized Clinical Trial

2025· article· en· W4415962671 on OpenAlexaff
Zoher Ghogawala, Tasneem Zaihra Rizvi, Zhibang Lin, Adam S. Kanter, Praveen V. Mummaneni, Erica F. Bisson, Todd J. Albert, Daniel K. Resnick, Michael Y. Wang, Steven D. Glassman, David W. Polly, Mohamad Bydon, Subu N. Magge, Luis M. Tumialán, Michael G. Fehlings, Michael P. Steinmetz, Robert G. Whitmore, Vedantam Rajshekhar, James S. Harrop, Roger Härtl, El-Nasri Ahmed, Dom Coric, Paul C. McCormick, Richard Assaker, Abdul Karim Msaddi, Langston T. Holly, Yoshiharu Kawaguchi, Asdrúbal Falavigna, Fred G. Barker, Edward C. Benzel

Bibliographic record

VenueNeurosurgery · 2025
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersStuart Foundation
KeywordsRandomized controlled trialLumbarQuality of life (healthcare)Degenerative diseaseClinical trialMEDLINELumbar spine

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: The appropriate utilization of lumbar fusion when performing laminectomy for lumbar spondylolisthesis is uncertain. The objective was to determine whether the use of a surgical expert review panel recommending fusion might improve patient selection, possibly reducing surgical failures. METHODS: Randomized clinical trial of patients with symptomatic degenerative lumbar stenosis with spondylolisthesis enrolled from 14 North American hospitals was conducted with patients randomized to receive an expert panel review of their case or not. Spinal expert review consisted of 10 to 15 surgeons' review of patient images and clinical data with voting on the appropriateness of fusion. Primary outcome was the percentage of patients who failed to improve their 1-year EuroQol-5 Dimension (EQ-5D) score. Secondary analysis focused on whether a supermajority (>80% consensus) of spinal experts recommending fusion might reduce operative failures. The trial (SLIP II) was registered at ClinicalTrials.gov (NCT03570801). RESULTS: Between November 1, 2017, and June 30, 2022, 663 patients were randomized (mean age 65.6 years; [59.6%] female) and 523 of 574 patients (91%; who had surgery) were included in the 1-year analysis. Final follow-up was on March 5, 2024. Among the 523 patients, 270 underwent review and 253 had no review. The overall surgical failure rate (using EQ-5D) did not differ between the review groups, 16.7% vs 17.4% (no review: difference 0.7%; 95% CI, -8% to 6%; P = .92). However, with supermajority recommending fusion, the proportion of patients who failed to improve EQ-5D score after surgery was 8.4% (review group) vs 18.4% (nonreview group: difference 10%; 95% CI, 2%-18%; P = .03). Supermajority recommendation for fusion was associated with 0.296 vs 0.240 EQ-5D change in the nonreview group (difference 0.056, 95% CI, 0.002-0.108; P = .04). CONCLUSION: Among patients with grade I degenerative lumbar spondylolisthesis, an expert panel review with a supermajority favoring fusion was associated with a greater improvement in health-related quality of life and fewer surgical failures.

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)0.007
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.128
GPT teacher head0.373
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

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 designRandomized trial
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

Citations0
Published2025
Admission routes1
Has abstractyes

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