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Record W2548735672 · doi:10.1002/mus.25451

Lower limb muscle strength impairment in late‐onset and adult myotonic dystrophy type 1 phenotypes

2016· article· en· W2548735672 on OpenAlexafffund
Émilie Petitclerc, Luc J. Hébert, Jean Mathieu, Johanne Desrosiers, Cynthia Gagnon

Bibliographic record

VenueMuscle & Nerve · 2016
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsUniversité LavalUniversité de Sherbrooke
FundersUniversité de Sherbrooke
KeywordsMyotonic dystrophyWastingMuscle weaknessWeaknessMedicinePhenotypeMyotoniaMuscle strengthMuscular dystrophyClinical phenotypeAge of onsetInternal medicinePhysical medicine and rehabilitationDiseaseBiologyAnatomyGeneticsGene

Abstract

fetched live from OpenAlex

INTRODUCTION: Lower limb strength has never been characterized separately for late-onset and adult myotonic dystrophy type 1 (DM1) phenotypes. METHODS: The purpose of this study was to: (1) describe and compare lower limb strength between the 2 DM1 phenotypes; and (2) compare the impairment profiles obtained from 2 assessment methods [manual (MMT) and quantitative (QMT) muscle testing] among 107 patients. RESULTS: Both MMT and QMT showed more pronounced weakness in the adult phenotype. In the late-onset phenotype, although MMT showed normal strength, QMT revealed a loss of 11.7%-20.4%. Participants with grade 1 or 2 on the Muscle Impairment Rating Scale had weakness detected using QMT, which suggests earlier muscle impairment than MMT alone would suggest. CONCLUSIONS: To avoid muscle wasting, physical activity recommendations should be made for the late-onset phenotype and in the early stages of the disease for the adult phenotype. MMT is not recommended for use in clinical trials. Muscle Nerve 56: 57-63, 2017.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.530
Threshold uncertainty score0.748

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 head0.015
GPT teacher head0.238
Teacher spread0.223 · 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

Citations28
Published2016
Admission routes2
Has abstractyes

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