MétaCan
Menu
Back to cohort

The first meta‐analysis of randomized controlled surgical trials in cerebral palsy (2002)

2008· letter· en· W2049699360 on OpenAlexaff
Robert W. Armstrong

Bibliographic record

VenueDevelopmental Medicine & Child Neurology · 2008
Typeletter
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSpasticitySpastic diplegiaCerebral palsyRhizotomyRandomized controlled trialSpasticGross Motor Function Classification SystemDiplegiaMeta-analysisMedicineModified Ashworth scalePhysical medicine and rehabilitationSpastic quadriplegiaPhysical therapyDorsumSurgeryInternal medicineAnatomy

Abstract

fetched live from OpenAlex

This study is a comparative analysis and meta-analysis of three randomized clinical trials. Children with spastic diplegia received either 'selective' dorsal rhizotomy (SDR) plus physiotherapy (SDR+PT) or PT without SDR (PT-only). Common outcome measures were used for spasticity (Ashworth scale) and function (Gross Motor Function Measure [GMFM]). Baseline and 9- to 12-month outcome data were pooled (n=90). At baseline, 82 children were under 8 years old and 65 had Gross Motor Function Classification System level II or III disability. Pooled Ashworth data analysis confirmed a reduction of spasticity with SDR+PT (mean change score difference -1.2; Wilcoxon p<0.001). Pooled GMFM data revealed greater functional improvement with SDR+PT (difference in change score +4.0, p=0.008). Multivariate analysis in the SDR+PT group revealed a direct relationship between percentage of dorsal root tissue transected and functional improvement. SDR+PT is efficacious in reducing spasticity in children with spastic diplegia and has a small positive effect on gross motor function.

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)0.026
metaresearch head score (Gemma)0.108
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.990
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.108
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0100.016
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.039
GPT teacher head0.287
Teacher spread0.248 · 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.

Study designMeta-analysis
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

Citations3
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueDevelopmental Medicine & Child NeurologySame topicCerebral Palsy and Movement DisordersFrench-language works237,207