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Record W4328097159 · doi:10.1016/j.wnsx.2023.100185

Is anterior cervical plating necessary for cage constructs in anterior cervical discectomy and fusion surgery for cervical degenerative disorders? Evidence-based on the systematic overview of meta-analyses

2023· review· en· W4328097159 on OpenAlexaff
Vibhu Krishnan Viswanathan, Sathish Muthu

Bibliographic record

VenueWorld Neurosurgery X · 2023
Typereview
Languageen
FieldMedicine
TopicCervical and Thoracic Myelopathy
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAnterior cervical discectomy and fusionMedicineMeta-analysisSurgeryCageSystematic reviewCervical spineMEDLINEInternal medicine

Abstract

fetched live from OpenAlex

Systematic review of meta-analyses. To perform a systematic review of meta-analyses to compare the clinical and radiological outcomes following anterior cervical discectomy and fusion with stand-alone cage (SAC) and anterior cervical cage-plate constructs (ACCPC). The systematic overview was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and reported as per Cochrane Handbook for Systematic Reviews of Interventions following the methodology described in reporting Overview of reviews. Based on the available level-1 evidence, SAC offers significantly better benefits over ACCPC, in terms of shorter operative time (p < 0.00001; I2 = 0%), lower blood loss (p = 0.01; I2 = 0%), lesser rates of post-operative dysphagia (p = 0.02; I2 = 0%), reduced overall expenditure (p = 0.001) and long-term adjacent segment degeneration (ASD)/anterior longitudinal ligament ossification (ALO; p = 0.0003; I2 = 0%). There is no significant difference between the two constructs with regard to fusion rates, functional outcome scores, follow-up radiological sagittal alignment parameters or cage subsidence. Based on the available evidence, SAC constructs in ACDF reduce blood loss, decreases operative time, mitigates post-operative dysphagia, lessens hospital-related expenditure and minimises long-term ASD rates.

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 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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.067
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0100.004
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 head0.422
GPT teacher head0.441
Teacher spread0.018 · 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 teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

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

Citations5
Published2023
Admission routes1
Has abstractyes

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