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Record W2113105798 · doi:10.2522/ptj.20140234

Longitudinal Evaluation of Muscle Composition Using Magnetic Resonance in 4 Boys With Duchenne Muscular Dystrophy: Case Series

2015· article· en· W2113105798 on OpenAlexaff
Claudia Senesac, Donovan J. Lott, Sean C. Forbes, Sunita Mathur, Ishu Arpan, Emily S. Senesac, Glenn A. Walter, Krista Vandenborne

Bibliographic record

VenuePhysical Therapy · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsUniversity of Toronto
FundersNational Center for Advancing Translational SciencesNational Institute of Arthritis and Musculoskeletal and Skin Diseases
KeywordsDuchenne muscular dystrophyMuscular dystrophyMagnetic resonance imagingSeries (stratigraphy)MedicineComposition (language)Physical medicine and rehabilitationInternal medicineBiologyRadiology

Abstract

fetched live from OpenAlex

BACKGROUND: Duchenne muscular dystrophy (DMD), an inherited recessive X chromosome-linked disease, is the most severe childhood form of muscular dystrophy. Boys with DMD experience muscle loss, with infiltration of intramuscular fat into muscles. OBJECTIVES: This case series describes the progression of DMD in boys using magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS). Magnetic resonance results are then compared with an established functional timed test. METHODS: Four boys with DMD and 4 healthy age-matched controls were chosen from a larger cohort. Boys with DMD were assessed at 4 time points over 2 years, with controls assessed at baseline only. Progression of the disease was documented by assessing the plantar flexors using MRI and MRS techniques and by assessing ambulation using the 30-Foot Fast Walk Test. RESULTS: Transverse relaxation time (T2) values were elevated in all boys with DMD at baseline. The lipid ratio increased rapidly as the disease progressed in 2 boys. Discrete changes in T2 in the other 2 boys with DMD indicated a slower disease progression. Magnetic resonance imaging and MRS allowed monitoring of the disease over all time periods regardless of ambulation status. LIMITATIONS: The magnetic resonance data were collected with 2 different magnets at 2 different field strengths (1.5 and 3.0 T). Although we corrected for this difference, care must be taken in interpreting data when different image collection systems are used. This was a case series of 4 boys with DMD taken from a larger cohort study. CONCLUSIONS: Magnetic resonance imaging and MRS are objective, noninvasive techniques for measuring muscle pathology and can be used to detect discrete changes in both people who are ambulatory and those who are nonambulatory. These techniques should be considered when monitoring DMD progression and assessing efficacy of therapeutic interventions.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.387
Threshold uncertainty score0.380

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 head0.046
GPT teacher head0.307
Teacher spread0.262 · 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 designBench or experimental
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

Citations8
Published2015
Admission routes1
Has abstractyes

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