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Record W2409277868 · doi:10.3233/jnd-150071

Health-Related Quality of Life in Children with Duchenne Muscular Dystrophy: A Review

2015· review· en· W2409277868 on OpenAlexafffund
Yi Wei, Kathy N. Speechley, Craig Campbell

Bibliographic record

VenueJournal of Neuromuscular Diseases · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsWestern University
FundersChildren's Health Research Institute
KeywordsMedicineQuality of life (healthcare)PsychosocialDuchenne muscular dystrophyPsycINFOMEDLINEConcordanceHealth related quality of lifePhysical therapyNeuromuscular diseaseDiseasePediatricsPopulationPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

In pediatric chronic illness, improving health-related quality of life (HRQOL) has become one of the most important goals of disease management. Duchenne muscular dystrophy (DMD) is a debilitating, progressive and chronic neuromuscular disorder affecting boys. The purpose of this review is to provide an overview of published research on HRQOL in the pediatric DMD population, describe the instruments used and summarize the study findings. The databases searched were Medline, Embase and PsycInfo. The literature search yielded 167 articles, of which 19 were included in this review. The studies were published between 2005 and 2013 across nine countries. Thirteen different generic and disease-specific measures were used, the most common being the Pediatric Quality of Life 4.0 Generic Core module.HRQOL in boys with DMD is worse than that of healthy peers and children with other chronic illnesses, especially in the physical domains. Boys who are at a more severe stage of the disease reported worse physical HRQOL but not necessarily psychosocial HRQOL than boys at a less severe stage. Traditional clinical outcome measures correlated well only with physical HRQOL. Parents' proxy-reports of their sons' HRQOL and the boys' self-reports had poor concordance. More research is needed to assess trends in HRQOL over time and to elucidate factors that affect HRQOL.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.784
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.035
GPT teacher head0.333
Teacher spread0.298 · 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.

Study designNot applicable
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

Citations27
Published2015
Admission routes2
Has abstractyes

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