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Use of the Gross Motor Function Classification System in infants with cerebral palsy

2008· letter· en· W2128492232 on OpenAlexaboutno aff
Dinah Reddihough

Bibliographic record

VenueDevelopmental Medicine & Child Neurology · 2008
Typeletter
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsCerebral palsyGross Motor Function Classification SystemGross motor skillPsychologyMotor skillPsychological interventionService (business)Physical medicine and rehabilitationDevelopmental psychologyPhysical therapyMedicinePsychiatry

Abstract

fetched live from OpenAlex

See related article on page 46 ‘Will my child walk?’ is the first question that parents often ask following a diagnosis of cerebral palsy (CP).1 Information about the most likely motor outcome is crucial for families. The ability to predict prognosis is also vitally important for clinicians wishing to evaluate the results of interventions, and for service providers planning for future resource requirements at home, at school, and in the community. The Gross Motor Function Classification System (GMFCS) has been a remarkable development in our ability to communicate clearly with each other about individual children’s level of gross motor ability and has made a significant contribution to clinical practice and the research field. In 2004 it was noted that there were over 100 citations to this work and the number will have grown exponentially since that time. The McMaster group are to be congratulated on the wide universal acceptance of the classification; it is a tribute to the innovation of this research team and the development of the growth curves has enabled a greater understanding of how the gross motor abilities in each level change with age and how much independence in mobility children are likely to achieve. Substantial additional work has been undertaken demonstrating the stability of the GMFCS over time in children and the reliability of parent report. Attention is now being paid to the use of the GMFCS in adolescents and adults. The CanChild Centre for Childhood Disability Research has recently released the GMFCS: Expanded and Revised, that includes an age band of 12 to 18 years. The stability of the GMFCS in 103 adults assessed at mean ages of 12 years and 22 years has now been demonstrated.2 As the use of the GMFCS is expanded to adolescents and adults with CP, it is timely that the measure is considered in more detail for young children under the age of 2 years, as reported in this issue. Gorter et al. are to be commended in their efforts to assess the usefulness of the measure in very young children. At this early stage of life, interventions are more likely to have positive outcomes and it is at this age that parents have an urgent need to have their questions answered about prognosis. Gorter et al. found that the percentage of children whose GMFCS level changed one or more levels was 42% which was much higher than the 27% reported for all participants in the Ontario Motor Growth Study. The difficulty of classifying the gross motor function of children accurately between 1 and 2 years of age had been recognized by the developers of the GMFCS and therefore this outcome was not surprising. The assessment of young children provides many challenges and can vary considerably with time, given the rapid development that takes place at this age. However, Gorter et al.’s conclusion that levels can be combined to give some estimate of independent mobility with or without walking aids compared with requirement for a wheelchair, or, alternately, the ability to walk independently without walking aids compared with children who are likely to use walking aids or a wheelchair, does provide some guidelines for counselling families. However, more work needs to be done. The mean age at Time 1 in this study was 19.4 months and it would be a great advantage to have information about much younger children. It would also be useful to consider the type and topographical distribution of the motor disorder. A study from Sweden considered these additional parameters and importantly, included a group of 111 children under the age of 2 years although the precise age of these children was not stated.3 Furthering our understanding of early motor development will require additional studies to determine the reliability of the motor type classifications and to resolve the ongoing dilemma about the best terminology to describe topographical distribution. Gorter et al. describe a child who decreased two levels over time due to the onset of severe epilepsy. Frequently there are significant events that do have a profound effect on development. As the field moves forwards, it will be important to consider all the comorbidities and associated problems that may have an impact on outcome. The influence of the child’s social and emotional situation may not result in a change of GMFCS level but may have an impact on the quality of life of that child. These factors may make a substantial contribution to how the child and family adapts to the eventual motor outcome. There is an ever-increasing research agenda for the years ahead to ensure that we develop the knowledge to best assist children with CP and their families to optimize their motor development, their participation in society, and their quality of life.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.030
GPT teacher head0.225
Teacher spread0.195 · 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 designNot applicable
Domainnot available
GenreCommentary

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
Published2008
Admission routes1
Has abstractyes

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