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Record W1964566526 · doi:10.1002/mus.21493

Muscle strength and fatigue in patients with generalized myasthenia gravis

2009· article· en· W1964566526 on OpenAlexaff
Caitlin Symonette, Bradley V. Watson, Wilma J. Koopman, Michael Nicolle, Timothy J. Doherty

Bibliographic record

VenueMuscle & Nerve · 2009
Typearticle
Languageen
FieldMedicine
TopicMyasthenia Gravis and Thymoma
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsIsometric exerciseMyasthenia gravisMedicineMuscle fatigueNeuromuscular transmissionWeaknessMuscle weaknessElectromyographyNeuromuscular diseaseMuscle strengthPopulationMuscle contractionPhysical therapyInternal medicinePhysical medicine and rehabilitationSurgeryDisease

Abstract

fetched live from OpenAlex

Myasthenia gravis (MG) is characterized by fatigue and fluctuating muscle weakness resulting from impaired neuromuscular transmission (NMT). The objective of this study was to quantify, by direct measurement of muscle force, the strength and fatigue of patients with MG. A maximal voluntary isometric contraction protocol of shoulder abductors was used in conjunction with conventional fatigue and disease-severity instruments. Results from patients with (D-MG) and without (ND-MG) decrement on repetitive nerve stimulation (RNS) of the spinal accessory and axillary nerves were compared with healthy controls. Patients with MG reported greater fatigue than controls. Muscle strength was lowest in the D-MG group, followed by the ND-MG group and controls. Normalized shoulder abduction fatigue and recovery values did not differ between the D-MG and ND-MG groups or controls. The RNS decrement appears to relate best to disease severity and muscle weakness but not to objective measures of fatigue 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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.414
Threshold uncertainty score0.704

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 head0.012
GPT teacher head0.237
Teacher spread0.225 · 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 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

Citations38
Published2009
Admission routes1
Has abstractyes

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