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Record W2793544342 · doi:10.1016/j.spinee.2018.02.001

Incidence and risk factors of postoperative neurologic decline after complex adult spinal deformity surgery: results of the Scoli-RISK-1 study

2018· article· en· W2793544342 on OpenAlexaff
Michael G. Fehlings, So Kato, Lawrence G. Lenke, Hiroaki Nakashima, Narihito Nagoshi, Christopher I. Shaffrey, Kmc Cheung, Leah Y. Carreon, Mark B. Dekutoski, Frank Schwab, Oheneba Boachie–Adjei, Khaled M. Kebaish, Christopher P. Ames, Yong Qiu, Yukihiro Matsuyama, Benny Dahl, Hossein Mehdian, Ferrán Pellisé, Stephen J. Lewis, Sigurd Berven

Bibliographic record

VenueThe Spine Journal · 2018
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsToronto Western HospitalUniversity of Toronto
FundersAOSpineNuVasiveStrykerScoliosis Research Society
KeywordsMedicineSpinal deformityIncidence (geometry)Spinal surgerySurgeryDeformityAnesthesia

Abstract

fetched live from OpenAlex

BACKGROUND CONTEXT: Significant variability in neurologic outcomes after surgical correction for adult spinal deformity (ASD) has been reported. Risk factors for decline in neurologic motor outcomes are poorly understood. PURPOSE: The objective of the present investigation was to identify the risk factors for postoperative neurologic motor decline in patients undergoing complex ASD surgery. STUDY DESIGN/SETTING: This is a prospective international multicenter cohort study. PATIENT SAMPLE: From September 2011 to October 2012, 272 patients undergoing complex ASD surgery were prospectively enrolled in a multicenter, international cohort study in 15 sites. OUTCOME MEASURES: Neurologic decline was defined as any postoperative deterioration in American Spinal Injury Association lower extremity motor score (LEMS) compared with preoperative status. METHODS: To identify risk factors, 10 candidate variables were selected for univariable analysis from the dataset based on clinical relevance, and a multivariable logistic regression analysis was used with backward stepwise selection. RESULTS: Complete datasets on 265 patients were available for analysis and 61 (23%) patients showed a decline in LEMS at discharge. Univariable analysis showed that the key factors associated with postoperative neurologic deterioration included older age, lumbar-level osteotomy, three-column osteotomy, and larger blood loss. Multivariable analysis revealed that older age (odds ratio [OR]=1.5 per 10 years, 95% confidence interval [CI] 1.1-2.1, p=.005), larger coronal deformity angular ratio [DAR] (OR=1.1 per 1 unit, 95% CI 1.0-1.2, p=.037), and lumbar osteotomy (OR=3.3, 95% CI 1.2-9.2, p=.022) were the three major predictors of neurologic decline. CONCLUSIONS: Twenty-three percent of patients undergoing complex ASD surgery experienced a postoperative neurologic decline. Age, coronal DAR, and lumbar osteotomy were identified as the key contributing factors.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.005
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.039
GPT teacher head0.319
Teacher spread0.280 · 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

Citations57
Published2018
Admission routes1
Has abstractyes

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