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Record W2606713290 · doi:10.1111/dmcn.3_12887

Effect of constraint‐induced movement therapy on activity and participation in children with hemiplegic cerebral palsy: a systematic review with meta‐analysis

2015· review· en· W2606713290 on OpenAlexaff
Michael J. Majsak, Jessica Mast, Linda Monterroso, Peter Altenburger, Roger Cardinal, Mindy Aisen, Cheryl L. Wolcott, Hermano Igo Krebs

Bibliographic record

VenueDevelopmental Medicine & Child Neurology · 2015
Typereview
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsHospital for Sick ChildrenSickKids FoundationHolland Bloorview Kids Rehabilitation HospitalUniversity of TorontoToronto Rehabilitation Institute
Fundersnot available
KeywordsConstraint-induced movement therapyCerebral palsyMeta-analysisPhysical medicine and rehabilitationConstraint (computer-aided design)MedicinePhysical therapyMovement (music)PsychologyUpper limbInternal medicine

Abstract

fetched live from OpenAlex

Results: Twenty-three children (51%) achieved clinically meaningful change on AMPS motor scale, 28 (60%) on AMPS process scale, 27 (53%) on COPM performance and satisfaction scales, 15 (29%) on the AHA and 18 (36%) on the TVPS-3.Lower baseline score was the single predictor of a best response on the AMPS motor scale (odds ratio (OR) = 0.04, p = 0.001) and AMPS process scale (OR = 0.003; p < 0.001).Higher FSIQ and lower baseline scores predicted best responders on the AHA (FSIQ OR = 1.07, p = 0.03; AHA baseline OR = 0.94, p = 0.03) and TVPS (FSIQ OR = 1.15, p = 0.003; TVPS baseline score OR = 0.92, p = 0.045).No significant predictors were identified on the COPM performance or satisfaction scales.Conclusions/Significance: Our findings suggest that a wide variety of children with UCP based on age, gender, laterality of injury and baseline hand function can achieve clinically meaningful improvements following a 20 week program of Mitii.Few characteristics predicted best responders across the included measures.Children with lower baseline scores may have had greater margin for improvement on measures.The nature of goals identified on the COPM may impact changes in score rather than clinical characteristics.

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)0.005
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0140.023
Bibliometrics0.0030.004
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.047
GPT teacher head0.339
Teacher spread0.292 · 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 designMeta-analysis
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

Citations1
Published2015
Admission routes1
Has abstractyes

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