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Record W3155698117 · doi:10.3171/2020.10.peds20671

What happens to the unfused upper thoracic curve after posterior spinal fusion for adolescent idiopathic scoliosis?

2021· article· en· W3155698117 on OpenAlexaff
Maaz Iqbal, Amer F. Samdani, Joshua M. Pahys, Peter O. Newton, Suken A. Shah, Tracey P. Bastrom, Paul D. Sponseller, Firoz Miyanji, Steven W. Hwang

Bibliographic record

VenueJournal of Neurosurgery Pediatrics · 2021
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsBC Children's Hospital
Fundersnot available
KeywordsMedicineSpinal fusionIdiopathic scoliosisScoliosisRachisAnatomySurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: Spontaneous lumbar curve correction after selective thoracic fusion in surgery for adolescent idiopathic scoliosis (AIS) is well described. However, only a few articles have described the course of the uninstrumented upper thoracic (UT) curve after fusion, and the majority involve a hybrid construct. In this study, the authors sought to determine the outcomes and associated factors of uninstrumented UT curves in patients with AIS. METHODS: The authors retrospectively reviewed a prospectively collected multicenter AIS registry for all consecutive patients with Lenke type 1-4 curves with a 2-year minimum follow-up. UT curves were considered uninstrumented if the upper instrumented vertebra (UIV) did not extend above 1 level from the lower end vertebra of the UT curve. The authors defined progression as > 5°, and divided patients into two cohorts: those with improvement in the UT curve (IMP) and those without improvement in the UT curve (NO IMP). Radiographic, demographic, and Scoliosis Research Society (SRS)-22 survey outcome measures were compared using univariate analysis, and significant factors were compared using a multivariate regression model. RESULTS: The study included 450 patients (370 females and 80 males). The UT curve self-corrected in 86% of patients (n = 385), there was no change in 14% (n = 65), and no patients worsened. Preoperatively, patients were similar with respect to Lenke classification (p = 0.44), age (p = 0.31), sex (p = 0.85), and Risser score (p = 0.14). The UT curves in the IMP group self-corrected from 24.7° ± 6.5° to 12.6° ± 5.9°, whereas in the NO IMP group UT curves remained the same, from 20.3° ± 5.8° to 18.5° ± 5.7°. In a multivariate analysis, preoperative main thoracic (MT) curve size (p = 0.004) and MT curve correction (p = 0.001) remained significant predictors of UT curve improvement. Greater correction of the MT curve and larger initial MT curve size were associated with greater likelihood of UT curve improvement. CONCLUSIONS: Spontaneous UT curve correction occurred in the majority (86%) of unfused UT curves after MT curve correction in Lenke 1-4 curve types. The magnitude of preoperative MT curve size and postoperative MT curve correction were independent predictors of spontaneous UT curve correction.

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)0.009
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.040
GPT teacher head0.328
Teacher spread0.288 · 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
Published2021
Admission routes1
Has abstractyes

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