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Record W2221282710 · doi:10.1017/cjn.2015.65

Health-related quality of life in children with Duchenne muscular dystrophy: a follow-up study

2015· article· en· W2221282710 on OpenAlexvenueno aff
Yi Wei, Kathy N. Speechley, C. Campbell

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2015
Typearticle
Languageen
FieldMedicine
TopicNeurogenetic and Muscular Disorders Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineQuality of life (healthcare)Duchenne muscular dystrophyClinical trialPhysical therapyPsychological interventionHealth related quality of lifePediatricsPopulationDiseasePsychiatryInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

Background: Improvement of health-related quality of life (HRQOL) is a major goal in chronic disease management and HRQOL has become an important outcome in clinical trials. Longitudinal data on HRQOL are needed to elucidate change over time and to assess effectiveness of interventions; such research is lacking in the paediatric Duchenne Muscular Dystrophy (DMD) population. Methods: We followed up participants from our initial HRQOL study in 2013 a year and a half later. Multidimensional generic and disease-specific measures from the Pediatric Quality of Life Inventory were used to assess HRQOL from child and parent perspectives. Mean changes in HRQOL were calculated. Results: Data collection is ongoing and currently, data from 16 families (out of the initial 98) are available. Preliminary results indicated that by both child and parent reports, there were declines in all domains of HRQOL except for social function, in which there was a slight improvement. Mean decline in HRQOL scores ranged from 1.6 to 8.6 for child reports; and 3.3 to 7.7 for parent reports. Conclusion: HRQOL of boys with DMD deteriorates over time. Our results may be helpful in interpreting patient reported outcomes in forthcoming clinical trials and determining minimally clinically important changes in this population.

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)0.009
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.150
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.005
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.071
GPT teacher head0.328
Teacher spread0.257 · 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 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

Citations2
Published2015
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences NeurologiquesSame topicNeurogenetic and Muscular Disorders ResearchFrench-language works237,207