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Record W2167743109 · doi:10.3138/physio.62.2.141

Muscle Length and Joint Range of Motion in Children with Cystic Fibrosis Compared to Children Developing Typically

2010· article· en· W2167743109 on OpenAlexvenueno aff
Allison Mandrusiak, Donnae Giraud, J. Macdonald, Corey Wilson, Pauline Watter

Bibliographic record

VenuePhysiotherapy Canada · 2010
Typearticle
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsnot available
Fundersnot available
KeywordsRange of motionMedicinePhysical medicine and rehabilitationPhysical therapyInternal rotationTypically developing

Abstract

fetched live from OpenAlex

PURPOSE: To explore range of motion in children with cystic fibrosis (CF) compared to children developing typically. With the increasing longevity of people with CF, musculoskeletal concerns are becoming more prevalent and should be identified and considered in management plans. Reduced range of motion (ROM) in older people with CF has been demonstrated, and the age at which these changes begin to occur must be explored. METHODS: Participants were 38 children with CF (aged 7-14 years) and 38 children developing typically, matched for age and gender. Muscle length and joint ROM measurements were compared, using analysis of variance, in the thoracolumbar region (extension, flexion, lateral flexion), upper limb (pectoralis minor, pectoralis major, shoulder horizontal abduction), and lower limb (hip internal and external rotation, hamstrings, gastrocnemius-soleus). RESULTS: Children with CF had significantly shorter pectoralis minor, pectoralis major, and gastrocnemius-soleus muscles and significantly greater range of shoulder horizontal abduction than matched controls. CONCLUSION: Altered ROM was identified in children with CF, strengthening the rationale to support proactive physiotherapy management of the musculoskeletal system, aiming to optimize function across the increasing lifespan. Evaluation and management of ROM and its impact on activity and participation are important areas for future research and clinical practice.

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)0.000
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 score0.399
Threshold uncertainty score0.729

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.008
GPT teacher head0.259
Teacher spread0.251 · 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

Citations13
Published2010
Admission routes1
Has abstractyes

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