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Record W3127414105 · doi:10.3171/2020.8.spine191185

Surgical outcomes in rigid versus flexible cervical deformities

2021· article· en· W3127414105 on OpenAlexaff
Themistocles S. Protopsaltis, Nicholas Stekas, Justin S. Smith, Alexandra Sorocéanu, Renaud Lafage, Alan H. Daniels, Han Jo Kim, Peter G. Passias, Gregory M. Mundis, Eric O. Klineberg, D. Kojo Hamilton, Munish C. Gupta, Virginie Lafage, Robert A. Hart, Frank J. Schwab, Douglas C. Burton, Shay Bess, Christopher I. Shaffrey, Christopher P. Ames

Bibliographic record

VenueJournal of Neurosurgery Spine · 2021
Typearticle
Languageen
FieldMedicine
TopicCervical and Thoracic Myelopathy
Canadian institutionsUniversity of Calgary
FundersUniversity of California, San FranciscoAlloSourceNuVasiveStrykerPfizerScoliosis Research SocietyOrthopaedic Research and Education Foundation
KeywordsMedicineSagittal planeDeformitySurgeryRetrospective cohort studyRadiographyQuality of life (healthcare)Prospective cohort studyRadiology

Abstract

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OBJECTIVE: Cervical deformity (CD) patients have severe disability and poor health status. However, little is known about how patients with rigid CD compare with those with flexible CD. The main objectives of this study were to 1) assess whether patients with rigid CD have worse baseline alignment and therefore require more aggressive surgical corrections and 2) determine whether patients with rigid CD have similar postoperative outcomes as those with flexible CD. METHODS: This is a retrospective review of a prospective, multicenter CD database. Rigid CD was defined as cervical lordosis (CL) change < 10° between flexion and extension radiographs, and flexible CD was defined as a CL change ≥ 10°. Patients with rigid CD were compared with those with flexible CD in terms of cervical alignment and health-related quality of life (HRQOL) at baseline and at multiple postoperative time points. The patients were also compared in terms of surgical and intraoperative factors such as operative time, blood loss, and number of levels fused. RESULTS: A total of 127 patients met inclusion criteria (32 with rigid and 95 with flexible CD, 63.4% of whom were females; mean age 60.8 years; mean BMI 27.4); 47.2% of cases were revisions. Rigid CD was associated with worse preoperative alignment in terms of T1 slope minus CL, T1 slope, C2-7 sagittal vertical axis (cSVA), and C2 slope (C2S; all p < 0.05). Postoperatively, patients with rigid CD had an increased mean C2S (29.1° vs 22.2°) at 3 months and increased cSVA (47.1 mm vs 37.5 mm) at 1 year (p < 0.05) compared with those with flexible CD. Patients with rigid CD had more posterior levels fused (9.5 vs 6.3), fewer anterior levels fused (1 vs 2.0), greater blood loss (1036.7 mL vs 698.5 mL), more 3-column osteotomies (40.6% vs 12.6%), greater total osteotomy grade (6.5 vs 4.5), and mean osteotomy grade per level (3.3 vs 2.1) (p < 0.05 for all). There were no significant differences in baseline HRQOL scores, the rate of distal junctional kyphosis, or major/minor complications between patients with rigid and flexible CD. Both rigid and flexible CD patients reported significant improvements from baseline to 1 year according to the numeric rating scale for the neck (-2.4 and -2.7, respectively), Neck Disability Index (-8.4 and -13.3, respectively), modified Japanese Orthopaedic Association score (0.1 and 0.6), and EQ-5D (0.01 and 0.05) (p < 0.05). However, HRQOL changes from baseline to 1 year did not differ between rigid and flexible CD patients. CONCLUSIONS: Patients with rigid CD have worse baseline cervical malalignment compared with those with flexible CD but do not significantly differ in terms of baseline disability. Rigid CD was associated with more invasive surgery and more aggressive corrections, resulting in increased operative time and blood loss. Despite more extensive surgeries, rigid CD patients had equivalent improvements in HRQOL compared with flexible CD patients. This study quantifies the importance of analyzing flexion-extension images, creating a prognostic tool for surgeons planning CD correction, and counseling patients who are considering CD surgery.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.093
Threshold uncertainty score0.854

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.319
Teacher spread0.283 · 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

Citations9
Published2021
Admission routes1
Has abstractyes

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