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Record W1994679611 · doi:10.1097/brs.0b013e318134eabe

Does Spinal Fusion Influence Quality of Life in Neuromuscular Scoliosis?

2007· review· en· W1994679611 on OpenAlexaff
Eyal Mercado, Benjamin A. Alman, James G. Wright

Bibliographic record

VenueSpine · 2007
Typereview
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineScoliosisSpinal fusionQuality of life (healthcare)Spina bifidaNeuromuscular diseasePhysical therapyPhysical medicine and rehabilitationSpinal muscular atrophySurgeryDiseaseInternal medicine

Abstract

fetched live from OpenAlex

In Brief Study Design. Systematic literature review of articles pertaining to quality of life (QOL) in neuromuscular scoliosis patients that underwent spinal fusion. Objective. To determine if QOL is improved by scoliosis surgery in neuromuscular patients. Summary of Background Data. The primary focus of most prior studies on neuromuscular scoliosis has been on the technical correction of spinal deformities, and not the child’s postoperative performance and function in activities of daily living. Methods. Computer-based English literature search of Google and PubMed databases. Results. A total of 198 publications in the English literature between 1980 and 2006 were identified from a PubMed and Google Scholar search of QOL in neuromuscular scoliosis patients that underwent spinal fusion. Conclusion. Spinal fusion improves QOL in CP (Grade C recommendation). Spinal fusion improves QOL in muscular dystrophy (Grade C recommendation). Spinal fusion does not improve QOL in spina bifida (Grade C recommendation). In order to determine if QOL is improved by spinal fusion in neuromuscular patients, a systematic literature review was performed. A total of 198 publications in the English literature between 1980 and 2006 were identified regarding QOL in neuromuscular scoliosis patients that underwent spinal fusion. The conclusion of this literature review is that spinal fusion improves QOL in CP and muscular dystrophy but not in spina bifida.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.865
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.115
GPT teacher head0.442
Teacher spread0.328 · 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 designOther design
Domainnot available
GenreReview

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

Citations78
Published2007
Admission routes1
Has abstractyes

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