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Record W2159133573 · doi:10.3171/2015.2.spine14414

Impact of dynamic alignment, motion, and center of rotation on myelopathy grade and regional disability in cervical spondylotic myelopathy

2015· article· en· W2159133573 on OpenAlexaff
Shian Liu, Renaud Lafage, Justin S. Smith, Themistocles S. Protopsaltis, Vincent Challier, Christopher I. Shaffrey, Kris E. Radcliff, Paul M. Arnold, Jens R. Chapman, Frank Schwab, Eric M. Massicotte, S. Tim Yoon, Michael G. Fehlings, Christopher P. Ames

Bibliographic record

VenueJournal of Neurosurgery Spine · 2015
Typearticle
Languageen
FieldMedicine
TopicCervical and Thoracic Myelopathy
Canadian institutionsToronto Western Hospital
FundersUniversity of California, San FranciscoStrykerAOSpineNuVasiveU.S. Department of Defense
KeywordsMedicineMyelopathyRange of motionSagittal planeLordosisRadiographyOrthodonticsCervical vertebraeQuality of life (healthcare)Physical therapySurgerySpinal cordRadiology

Abstract

fetched live from OpenAlex

OBJECT: Cervical stenosis is a defining feature of cervical spondylotic myelopathy (CSM). Matsunaga et al. proposed that elements of stenosis are both static and dynamic, where the dynamic elements magnify the canal deformation of the static state. For the current study, the authors hypothesized that dynamic changes may be associated with myelopathy severity and neck disability. This goal of this study was to present novel methods of dynamic motion analysis in CSM. METHODS: A post hoc analysis was performed of a prospective, multicenter database of patients with CSM from the AOSpine North American study. One hundred ten patients (34%) met inclusion criteria, which were symptomatic CSM, age over 18 years, baseline flexion/extension radiographs, and health-related quality of life (HRQOL) questionnaires (modified Japanese Orthopaedic Association [mJOA] score, Neck Disability Index [NDI], the 36-Item Short Form Health Survey Physical Component Score [SF-36 PCS], and Nurick grade). The mean age was 56.9 ± 12 years, and 42% of patients were women (n = 46). Correlations with HRQOL measures were analyzed for regional (cervical lordosis and cervical sagittal vertical axis) and focal parameters (kyphosis and spondylolisthesis between adjacent vertebrae) in flexion and extension. Baseline dynamic parameters (flexion/extension cone relative to a fixed C-7, center of rotation [COR], and range of motion arc relative to the COR) were also analyzed for correlations with HRQOL measures. RESULTS: At baseline, the mean HRQOL measures demonstrated disability and the mean radiographic parameters demonstrated sagittal malalignment. Among regional parameters, there was a significant correlation between decreased neck flexion (increased C2-7 angle in flexion) and worse Nurick grade (R = 0.189, p = 0.048), with no significant correlations in extension. Focal parameters, including increased C-7 sagittal translation overT-1 (slip), were significantly correlated with greater myelopathy severity (mJOA score, Flexion R = -0.377, p = 0.003; mJOA score, Extension R = -0.261, p = 0.027). Sagittal slip at C-2 and C-4 also correlated with worse HRQOL measures. Reduced flexion/extension motion cones, a more posterior COR, and smaller range of motion correlated with worse general health SF-36 PCS and Nurick grade. CONCLUSIONS: Dynamic motion analysis may play an important role in understanding CSM. Focal parameters demonstrated a significant correlation with worse HRQOL measures, especially increased C-7 sagittal slip in flexion and extension. Novel methods of motion analysis demonstrating reduced motion cones correlated with worse myelopathy grades. More posterior COR and smaller range of motion were both correlated with worse general health scores (SF-36 PCS and Nurick grade). To our knowledge, this is the first study to demonstrate correlation of dynamic motion and listhesis with disability and myelopathy in CSM.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.031
Threshold uncertainty score0.532

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.035
GPT teacher head0.319
Teacher spread0.284 · 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.

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".

Quick stats

Citations50
Published2015
Admission routes1
Has abstractyes

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