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Record W2761497911 · doi:10.1093/pch/pxx086.068

FACTORS ASSOCIATED WITH HEALTH-RELATED QUALITY OF LIFE IN CHILDREN WITH CONGENITAL MYOTONIC DYSTROPHY

2017· article· en· W2761497911 on OpenAlexaff
Selwyn O. Rogers, Richard E. Hicks, Kevin Bax, Delia Ceballos‐Sáenz, B El-Aloul, Deanna DiBella, Evan M Pucillo, Nicholas E. Johnson, C Campbell, Eugenio Zapata‐Aldana

Bibliographic record

VenuePaediatrics & Child Health · 2017
Typearticle
Languageen
FieldMedicine
TopicSpaceflight effects on biology
Canadian institutionsWestern University
Fundersnot available
KeywordsMyotonic dystrophyQuality of life (healthcare)MedicineWechsler Adult Intelligence ScalePhysical therapyEpworth Sleepiness ScaleExcessive daytime sleepinessPediatricsPhysical medicine and rehabilitationCognitionPsychiatrySleep disorderInternal medicinePolysomnography

Abstract

fetched live from OpenAlex

BACKGROUND: Myotonic dystrophy type 1 (DM1) is an autosomal dominant disorder that results from a CTG trinucleotide repeat in the DMPK gene. Congenital myotonic dystrophy (CDM) is the most severe form of DM1, and patients with CDM are reported to have reduced health-related quality of life (HRQoL). However, the relationship between disease manifestations in CDM and HRQoL has not been well-characterized. Most studies assessing HRQoL have focused on adult-onset DM1, showing that excessive daytime sleepiness, fatigue, cognitive deficits, and muscle weakness negatively impact HRQoL. OBJECTIVES: The objective of this study was to evaluate the relationship between HRQoL and neuropsychological function, physical capacity, comorbidities, and disease severity in children with CDM. DESIGN/METHODS: Children with CDM aged 0-13 years were enrolled at two sites. PedsQL Generic Core Scales and Neuromuscular Module Parent Proxy-Reports were used to measure HRQoL. Neuropsychological function was assessed using Pediatric Daytime Sleepiness Scale, Social Communication Questionnaire, Vineland Adaptive Functioning Scale, and Wechsler Intelligence Scale for Children or Wechsler Preschool and Primary Scale of Intelligence. The Six-Minute Walk Test (6MWT) Z-score was used as a measure of physical capacity. CTG repeats, a measure of disease severity, and comorbidities were retrieved from patient histories. Correlations between patient characteristics and HRQoL were computed with the Spearman correlation coefficient in Stata 13.0. RESULTS: Forty-eight participants with CDM were enrolled: 24 females and 24 males with an average age of 6.5 years (SD 3.4). Greater daytime sleepiness was significantly associated with poor overall HRQoL determined by generic (=-0.41, P=0.007) and neuromuscular (=-0.40, P=0.01) measures, as well as psychosocial HRQoL (=-0.46, P=0.002). Higher adaptive functioning (Vineland subscales) was significantly associated with better HRQoL determined by the neuromuscular module: communication (=0.39, P=0.03), daily living skills (=0.54, P=0.002), and socialization (=0.52, P=0.005). Higher physical capacity, determined by 6MWT Z-score, was associated with better physical (=0.37, P=0.04) but not overall HRQoL. An increased number of comorbidities was associated with poor overall HRQoL determined by generic (=-0.40, P=0.009) and neuromuscular (=-0.32, P=0.05) measures. CTG repeats did not correlate with HRQoL. CONCLUSION: This study has identified several factors that are associated with HRQoL in children with CDM. Daytime sleepiness, adaptive functioning, and higher comorbidities had the most pronounced effect on HRQoL. These may be promising factors to target in treatment plans.

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)0.003
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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.034
GPT teacher head0.310
Teacher spread0.276 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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