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Inter‐relationships of functional status in cerebral palsy: analyzing gross motor function, manual ability, and communication function classification systems in children

2012· article· en· W2130865334 on OpenAlexaff
Mary Jo Cooley Hidecker, Nhan T. Ho, Nancy N. Dodge, Edward A. Hurvitz, Jaime Slaughter‐Acey, Marilyn Seif Workinger, Ray D. Kent, Peter Rosenbaum, Madeleine Lenski, Bridget M. Messaros, Suzette Báez Vanderbeek, Steven T. DeRoos, Nigel Paneth

Bibliographic record

VenueDevelopmental Medicine & Child Neurology · 2012
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsMcMaster University
FundersNational Institute of Neurological Disorders and StrokeNational Institutes of Health
KeywordsCerebral palsyGross Motor Function Classification SystemPhysical medicine and rehabilitationGross motor skillFunction (biology)Motor functionPsychologyAudiologyMedicineMotor skillNeuroscienceBiology

Abstract

fetched live from OpenAlex

AIM: To investigate the relationships among the Gross Motor Function Classification System (GMFCS), Manual Ability Classification System (MACS), and Communication Function Classification System (CFCS) in children with cerebral palsy (CP). METHOD: Using questionnaires describing each scale, mothers reported GMFCS, MACS, and CFCS levels in 222 children with CP aged from 2 to 17 years (94 females, 128 males; mean age 8 y, SD 4). Children were referred from pediatric developmental/behavioral, physiatry, and child neurology clinics, in the USA, for a case-control study of the etiology of CP. Pairwise relationships among the three systems were assessed using Spearman's correlation coefficients (r(s) ), stratifying by age and CP topographical classifications. RESULTS: Correlations among the three functional assessments were strong or moderate. GMFCS levels were highly correlated with MACS levels (r(s) = 0.69) and somewhat less so with CFCS levels (r(s) = 0.47). MACS and CFCS were also moderately correlated (r(s) = 0.54). However, many combinations of functionality were found. Of the 125 possible combinations of the three five-point systems, 62 were found in these data. INTERPRETATION: Use of all three classification systems provides a more comprehensive picture of the child's function in daily life than use of any one alone. This resulting functional profile can inform both clinical and research purposes.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.005
Threshold uncertainty score0.810

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.031
GPT teacher head0.263
Teacher spread0.232 · 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 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

Citations117
Published2012
Admission routes1
Has abstractyes

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