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Record W3129370854 · doi:10.1097/brs.0000000000003971

Predictors of Superior Recovery Kinetics in Adult Cervical Deformity Correction

2021· article· en· W3129370854 on OpenAlexaff
Katherine E. Pierce, Peter G. Passias, Avery Brown, Cole Bortz, Haddy Alas, Renaud Lafage, Virginie Lafage, Christopher P. Ames, Douglas C. Burton, Robert A. Hart, Kojo Hamilton, Jeffrey L. Gum, Justin K. Scheer, Alan H. Daniels, Shay Bess, Alex Soroceanu, Eric O. Klineberg, Christopher I. Shaffrey, Breton Line, Frank Schwab, Justin S. Smith

Bibliographic record

VenueSpine · 2021
Typearticle
Languageen
FieldMedicine
TopicCervical and Thoracic Myelopathy
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineQuartileSurgeryCoronal planeSagittal planeDeformityInterquartile rangeRetrospective cohort studyInternal medicineConfidence intervalRadiology

Abstract

fetched live from OpenAlex

STUDY DESIGN: Retrospective review of a prospective database. OBJECTIVE: The aim of this study was to identify demographic, surgical, and radiographic factors that predict superior recovery kinetics following cervical deformity (CD) corrective surgery. SUMMARY OF BACKGROUND DATA: Analyses of CD corrective surgery use area under the curve (AUC) to assess health-related quality of life (HRQL) metrics throughout recovery. METHODS: Outcome measures were baseline (BL) to 1-year (1Y) health-related quality of life (HRQL) (Neck Disability Index [NDI]). CD criteria were C2-7 Cobb angle >10°, coronal Cobb angle >10°, C2-C7 sagittal vertical axis (cSVA) >4 cm, TS-CL >10°, or chin-brow vertical angle >25°. AUC normalization divided BL and postoperative outcomes by BL. Normalized scores (y axis) were plotted against follow-up (x axis). AUC was calculated and divided by cumulative follow-up length to determine overall, time-adjusted recovery (Integrated Health State [IHS]). IHS NDI was stratified by quartile, uppermost 25% being "Superior" Recovery Kinetics (SRK) versus "Normal" Recovery Kinetics (NRK). BL demographic, clinical, and surgical information predicted SRK using generalized linear modeling. RESULTS: Ninety-eight patients included (62 ± 10 years, 28 ± 6 kg/m2, 65% females, Charlson Comorbidity Index: 0.95), 6% smokers, 31% smoking history. Surgical approach was: combined (33%), posterior (49%), anterior (18%). Posterior levels fused: 8.7, anterior: 3.6, estimated blood loss: 915.9ccs, operative time: 495 minutes. Ames BL classification: cSVA (53.2% minor deformity, 46.8% moderate), TS-CL (9.8% minor, 4.3% moderate, 85.9% marked), horizontal gaze (27.4% minor, 46.6% moderate, 26% marked). Relative to BL NDI (Mean: 47), normalized NDI decreased at 3 months (0.9 ± 0.5, P = 0.260) and 1Y (0.78 ± 0.41, P < 0.001). NDI IHS correlated with age (P = 0.011), sex (P = 0.042), anterior approach (P = 0.042), posterior approach (P = 0.042). Greater BL pelvic tilt (PT) (SRK: 25.6°, NRK: 17°, P = 0.002), pelvic incidence-lumbar lordosis (PI-LL) (SRK: 8.4°, NRK: -2.8°, P = 0.009), and anterior approach (SRK: 34.8%, NRK: 13.3%; P = 0.020) correlated with SRK. 69.4% met MCID for NDI (<Δ-15) and 63.3% met substantial clinical benefit for NDI (<Δ-10); 100% of SRK met both MCID and substantial clinical benefit. The predictive model for SRK included (AUC = 88.1%): BL visual analog scale (VAS) EuroQol five-dimensional descriptive system (EQ5D) (odds rario [OR] 0.96, 95% confidence interval [CI]: 0.92-0.99), BL swallow sleep score (OR: 1.04, 95% CI: 1.01-1.06), BL PT (OR: 1.12, 95% CI: 1.03-1.22), BL modified Japanese Orthopedic Association scale (mJOA) (OR: 1.5, 95% CI: 1.07-2.16), BL T4-T12, BL T10-L2, BL T12-S1, and BL L1-S1. CONCLUSION: Superior recovery kinetics following CD surgery was predicted with high accuracy using BL patient-reported (VAS EQ5D, swallow sleep, mJOA) and radiographic factors (PT, TK, T10-L2, T12-S1, L1-S1). Awareness of these factors can improve decision-making and reduce postoperative neck disability.Level of Evidence: 3.

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)0.000
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 score0.417
Threshold uncertainty score0.867

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.009
GPT teacher head0.251
Teacher spread0.241 · 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".

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Citations7
Published2021
Admission routes1
Has abstractyes

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