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Record W2959234984 · doi:10.1097/bpo.0000000000001424

Improving Health-related Quality of Life for Patients With Nonambulatory Cerebral Palsy: Who Stands to Gain From Scoliosis Surgery?

2019· article· en· W2959234984 on OpenAlexaff
Daniel J. Miller, John M. Flynn, Saba Pasha, Burt Yaszay, Stefan Parent, Jahangir Asghar, Mark F. Abel, Joshua M. Pahys, Amer F. Samdani, Steven W. Hwang, Unni Narayanan, Paul D. Sponseller, Patrick J. Cahill

Bibliographic record

VenueJournal of Pediatric Orthopaedics · 2019
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsHospital for Sick ChildrenUniversité de Montréal
Fundersnot available
KeywordsMedicineCerebral palsyScoliosisGross Motor Function Classification SystemQuality of life (healthcare)PerioperativeLogistic regressionRadiographyPhysical therapySurgeryCobb angleInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: It is unclear what factors influence health-related quality of life (HRQOL) in neuromuscular scoliosis. The aim of this study was to evaluate which factors are associated with an improvement in an HRQOL after spinal fusion surgery for nonambulatory patients with cerebral palsy (CP). METHODS: A total of 157 patients with nonambulatory CP (Gross Motor Function Classification System IV and V) with a minimum of 2-year follow-up after PSF were identified from a prospective multicenter registry. Radiographs and quality of life were evaluated preoperatively and 2 years postoperatively. Quality of life was evaluated using the validated Caregiver Priorities and Child Health Index of Life with Disabilities (CPCHILD) questionnaire. Patients who had an increase of 10 points or greater from baseline CPCHILD scores were considered to have meaningful improvement at 2 years postoperatively. 10 points was chosen as a threshold for meaningful improvement based on differences between Gross Motor Function Classification System IV and V patients reported during the development of the CPCHILD. Perioperative demographic, clinical, and radiographic variables were analyzed to determine predicators for meaningful improvement by univariate and multivariate regression analysis. RESULTS: A total of 36.3% (57/157) of the patients reported meaningful improvement in CPCHILD scores at 2 years postoperatively. Preoperative radiographic parameters, postoperative radiographic parameters, and deformity correction did not differ significantly between groups. Patients who experienced meaningful improvement from surgery had significantly lower preoperative total CHPILD scores (43.8 vs. 55.2, P<0.001). On backwards conditional binary logistic regression, only the preoperative comfort, emotions, and behavior domain of the CPCHILD was predictive of meaningful improvement after surgery (P≤0.001). CONCLUSION: Analysis of 157 CP patients revealed a meaningful improvement in an HRQOL in 36.3% of the patients. These patients tended to have lower preoperative HRQOL, suggesting more "room for improvement" from surgery. A lower score within the comfort, emotions, and behavior domain of the CPCHILD was predictive of meaningful improvement after surgery. Radiographic parameters of deformity or curve correction were not associated with meaningful improvement after surgery. LEVEL OF EVIDENCE: Level II-retrospective review of prospectively collected data.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.281
Teacher spread0.256 · 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

Citations41
Published2019
Admission routes1
Has abstractyes

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