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Record W2561219451

THE EFFECT OF DISC DEGENERATION ON ANTERIOR SHEAR FLEXIBILITY IN THE LUMBAR SPINE

2018· article· en· W2561219451 on OpenAlexaff
Angela D. Melnyk, Wen Tong, Jason D. Chak, Adrienne Kelly, Peter A. Cripton, Charles G. Fisher, Marcel F. Dvorak, Thomas R. Oxland

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicHermeneutics and Narrative Identity
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCadaveric spasmLumbarSpondylolisthesisMedicineLow back painAnatomyBiomechanicsFlexibility (engineering)OrthodonticsMathematicsPathology
DOInot available

Abstract

fetched live from OpenAlex

Summary Statement Spinal flexibility in bending and axial torque has been shown to exhibit very modest changes with advancing disc degeneration. This study is the first to address the possible relationship in pure anterior shear and no clear relationship was observed. Introduction Disc degeneration (DD) is a risk factor for low back pain. Stable or unstable spine segments may be treated with an isolated decompression or instrumented stabilization, respectively. The effect of DD on spinal flexibility has been addressed by several groups in bending but not in shear; a highly relevant load direction in the lumbar spine is anterior shear. The objective of our study was to determine the effect of DD on anterior translation and specimen stiffness under shear loading in an in vitro model of degenerative spondylolisthesis. Methods Magnetic resonance images were obtained for human cadaveric lumbar FSUs (N=30). Disc degeneration was assessed with the Pfirrmann five-point grading scale. Three surgeons independently graded the discs and the grade common to at least two of the surgeons was assigned to that specimen. Each specimen was then tested in three sequential states: intact, facet destabilization, and disc destabilization, with the latter two states representing the clinical scenario of degenerative lumbar spondylolisthesis. The specimens were loaded with a constant 300 N axial compressive force, representing body weight, combined with a cyclic anterior shear force (5–250 N). Vertebral translation was tracked with an optoelectronic motion capture system. Kruskal-Wallis ANOVA and multiple comparison Dunn9s tests were performed to determine the effect of DD on anterior translation and specimen stiffness. Results There was only one specimen with disc grade V, and it was grouped with specimens with disc grade IV for the statistical analyses. DD had no effect on anterior translation or specimen stiffness for the intact and disc destabilization conditions. In the facet destabilization condition, specimens with disc grade II translated more than those with disc grades IV and V (p=0.03). Stiffness increased with DD in the facet destabilization condition (ANOVA p=0.04; Dunn9s test was not significant). However, we re-analyzed the data with each surgeon9s disc grades and found no significant differences in any of the specimen conditions for all three surgeons. Discussion In the original data analysis, the translation results showed a trend to reduced anterior translation in shear with advancing degeneration only in the facet destabilization condition. These results suggest that shear stiffness of an intact specimen is not affected by overall degeneration, except in the case where the facets are not competent to resist load. In the subsequent data analyses, no significant effects were found. These findings indicate the sensitivity of the analyses to the assignment of disc grade. There are numerous disc grading scales reported in the literature and it is not clear which scale best defines disc degeneration. We are continuing to assess our methods to determine the most appropriate method of defining disc degeneration by disc grade.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.281
Teacher spread0.257 · 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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