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Record W2923326347 · doi:10.2106/jbjs.17.00621

Assessing the Risk-Benefit Ratio of Scoliosis Surgery in Cerebral Palsy: Surgery Is Worth It

2018· article· en· W2923326347 on OpenAlexaff
Firoz Miyanji, Luigi Aurelio Nasto, Paul D. Sponseller, Suken A. Shah, Amer F. Samdani, Baron S. Lonner, Burt Yaszay, David H. Clements, Unni Narayanan, Peter O. Newton

Bibliographic record

VenueJournal of Bone and Joint Surgery · 2018
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsBC Children's Hospital
Fundersnot available
KeywordsCerebral palsyMedicineScoliosisQuality of life (healthcare)Physical therapyCobb angleGross Motor Function Classification SystemProspective cohort studyOswestry Disability IndexSurgeryLow back pain

Abstract

fetched live from OpenAlex

BACKGROUND: The true benefits of scoliosis surgery in cerebral palsy (CP) remain uncertain. Our aims were to determine the benefits of spinal fusion according to health-related quality of life (HRQoL) improvement at long-term follow-up and to explore the effect of surgery-related complications on clinical outcomes. METHODS: The cases of consecutive patients who had Gross Motor Function Classification System (GMFCS) level-IV or V cerebral palsy with 5-year follow-up from a prospective, longitudinal, multicenter database were analyzed. Caregivers completed the Caregiver Priorities and Child Health Index of Life with Disabilities (CPCHILD) questionnaire and 4 Likert-type anchor questions preoperatively and at 1, 2, and 5 years of follow-up. Data on complications were collected prospectively. Preoperative CPCHILD scores were compared with postoperative scores at the 1, 2, and 5-year follow-up evaluations. Preoperative CPCHILD scores were compared with postoperative scores at the 1, 2, and 5-year follow-up evaluations using repeated-measures analysis of variance (ANOVA). Spearman correlation coefficient was used to explore the association between changes in the CPCHILD at 1, 2, and 5-year follow-up and the reported complications within the follow-up period. Similarly, a comparative analysis between the percentage distribution of the answers to the 4 anchor questions and the reported complications was also performed. RESULTS: Sixty-nine patients with a mean age (and standard deviation) of 13.4 ± 2.6 years at enrollment were analyzed. The major Cobb angle was a mean of 81.9° ± 26.7° preoperatively and improved to a mean of 28.7° ± 14.4° at 2 years and 30.7° ± 15.3° at 5 years postoperatively. Significant improvements in CPCHILD personal care, positioning, and comfort domains were noted at all time points. The mean increase in the total score was 7.19 (p < 0.001) at 1 year, and the score gain was maintained at 2 and 5 years postoperatively. The overall complication rate was 46.4% at 1 year, 1.4% between 1 and 2 years, and 4.3% at 2 to 5 years postoperatively, with surgical intervention required in 6 patients within 1 year and in 2 additional patients within 5 years following scoliosis surgery. There was no correlation between complications and CPCHILD scores postoperatively at all time points, with the only exception of a weak correlation (ρ = -0.450, p = 0.002) with CPCHILD comfort score at 1 year after surgery. CONCLUSIONS: Scoliosis surgery in patients with CP leads to a significant improvement in HRQoL, which is maintained 5 years following surgery. The substantial complication rate does not correlate with HRQoL changes postoperatively, suggesting that the benefits of surgery outweigh the risks in this fragile population. LEVEL OF EVIDENCE: Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence.

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)0.007
metaresearch head score (Gemma)0.026
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 score0.007
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
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 head0.070
GPT teacher head0.313
Teacher spread0.243 · 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".

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Citations89
Published2018
Admission routes1
Has abstractyes

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