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Record W2256595858 · doi:10.1177/0883073815627879

Factors Associated With Health-Related Quality of Life in Children With Duchenne Muscular Dystrophy

2016· article· en· W2256595858 on OpenAlexaffabout
Yi Wei, Kathy N. Speechley, Guangyong Zou, Craig Campbell

Bibliographic record

VenueJournal of Child Neurology · 2016
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsChildren’s Health Research InstituteLawson Health Research InstituteWestern University
Fundersnot available
KeywordsDuchenne muscular dystrophyQuality of life (healthcare)MedicineMuscular dystrophyProxy (statistics)Health related quality of lifePopulationDiseaseGerontologyFamily incomeNeuromuscular diseasePhysical therapyPsychologyEnvironmental healthInternal medicineNursing

Abstract

fetched live from OpenAlex

This study investigated clinical and family characteristics associated with health-related quality of life in children with Duchenne muscular dystrophy. Families of 176 boys with Duchenne muscular dystrophy were identified and mailed questionnaires via the Canadian Neuromuscular Disease Registry. Multiple linear regressions analyses were used to examine the relationship between clinical and family characteristics and child-self and parent-proxy reported health-related quality of life. Greater fatigue and use of wheelchairs were consistently associated with worse health-related quality of life independent of other factors. Higher household income and parent having a postsecondary degree were associated with better health-related quality of life in some of the measures. A greater clinical focus on and efforts to reduce fatigue could lead to improvement of health-related quality of life in the Duchenne muscular dystrophy population. This study also sets the ground for longitudinal studies where changes in health-related quality of life can be monitored over time.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.029
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.259
Teacher spread0.235 · 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 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

Citations38
Published2016
Admission routes2
Has abstractyes

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Same venueJournal of Child NeurologySame topicCerebral Palsy and Movement DisordersFrench-language works237,207