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Record W4401597687 · doi:10.1097/brs.0000000000005119

Impact of Prior Cervical Fusion on Patients Undergoing Thoracolumbar Deformity Correction

2024· article· en· W4401597687 on OpenAlexaff
Manjot Singh, Mariah Balmaceno-Criss, Mohammad Daher, Renaud Lafage, Robert K. Eastlack, Munish C. Gupta, Gregory M. Mundis, Jeffrey L. Gum, Kojo Hamilton, Richard A. Hostin, Peter G. Passias, Themistocles S. Protopsaltis, Khaled M. Kebaish, Lawrence G. Lenke, Christopher P. Ames, Douglas C. Burton, Stephen M. Lewis, Eric O. Klineberg, Han Jo Kim, Frank J. Schwab, Christopher I. Shaffrey, Justin S. Smith, Breton Line, Shay Bess, Virginie Lafage, Bassel G. Diebo, Alan H. Daniels

Bibliographic record

VenueSpine · 2024
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineSurgeryKyphosisDeformityRetrospective cohort studySpinal fusionUnivariate analysisLumbosacral jointRadiographyLordosisLumbarMultivariate analysisInternal medicine

Abstract

fetched live from OpenAlex

STUDY DESIGN: Retrospective analysis of prospectively collected data. OBJECTIVE: Evaluate the impact of prior cervical constructs on upper instrumented vertebrae (UIV) selection and postoperative outcomes among patients undergoing thoracolumbar deformity correction. BACKGROUND: Surgical planning for adult spinal deformity (ASD) patients involves consideration of spinal alignment and existing fusion constructs. METHODS: ASD patients with (ANTERIOR or POSTERIOR) and without (NONE) prior cervical fusion who underwent thoracolumbar fusion were included. Demographics, radiographic alignment, patient-reported outcome measures (PROMs), and complications were compared. Univariate and multivariate analyses were performed on POSTERIOR patients to identify parameters predictive of UIV choice and to evaluate postoperative outcomes impacted by UIV selection. RESULTS: Among 542 patients, with 446 NONE, 72 ANTERIOR, and 24 POSTERIOR patients, mean age was 64.4 years and 432 (80%) were female. Cervical fusion patients had worse preoperative cervical and lumbosacral deformity, and PROMs ( P <0.05). In the POSTERIOR cohort, preoperative LIV was frequently below the cervicothoracic junction (54%) and uncommonly (13%) connected to the thoracolumbar UIV. Multivariate analyses revealed that higher preoperative cervical SVA (coeff=-0.22, 95% CI=-0.43 to -0.01, P =0.038) and C2SPi (coeff=-0.72, 95% CI=-1.36 to -0.07, P =0.031), and lower preoperative thoracic kyphosis (coeff=0.14, 95% CI=0.01-0.28, P =0.040) and thoracolumbar lordosis (coeff=0.22, 95% CI=0.10-0.33, P =0.001) were predictive of cranial UIV. Two-year postoperatively, cervical patients continued to have worse cervical deformity and PROMs ( P <0.05) but had comparable postoperative complications. Choice of thoracolumbar UIV below or above T6, as well as the number of unfused levels between constructs, did not affect patient outcomes. CONCLUSIONS: Among patients who underwent thoracolumbar deformity correction, prior cervical fusion was associated with more severe spinopelvic deformity and PROMs preoperatively. The choice of thoracolumbar UIV was strongly predicted by their baseline cervical and thoracolumbar alignment. Despite their poor preoperative condition, these patients still experienced significant improvements in their thoracolumbar alignment and PROMs after surgery, irrespective of UIV selection. LEVEL OF EVIDENCE: IV.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.332
Teacher spread0.315 · 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".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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