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Record W2623745768 · doi:10.1002/mus.25720

The utility of a single simple question in the evaluation of patients with myasthenia gravis

2017· article· en· W2623745768 on OpenAlexaff
Alon Abraham, Ari Breiner, Carolina Barnett, Hans Katzberg, Vera Bril

Bibliographic record

VenueMuscle & Nerve · 2017
Typearticle
Languageen
FieldMedicine
TopicMyasthenia Gravis and Thymoma
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMyasthenia gravisMedicineNeuromuscular diseaseWeaknessRetrospective cohort studyPhysical therapyQuality of life (healthcare)CohortMuscle weaknessDiseasePediatricsSurgeryInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Assessing myasthenia gravis (MG) can be challenging, and multiple scales are available to evaluate disease severity. We evaluated the utility of a single, simple question, as part of the MG evaluation: "What percentage of normal do you feel regarding your MG, 0%-100% normal?" METHODS: A retrospective chart review of patients attending the neuromuscular clinic from January 2014 to December 2015 was performed. Responses were correlated with symptoms and signs, the Quantitative Myasthenia Gravis Score (QMGS), the Myasthenia Gravis Impairment Index (MGII), and the 15-item Myasthenia Gravis Quality of Life scale (MG-QOL15). RESULTS: The total cohort included 169 patients. The percentage of normal correlated strongly with limb muscle weakness and MG scales, moderately with bulbar and respiratory symptoms, and weakly with ocular manifestations. DISCUSSION: The question, "What percentage of normal do you feel regarding your MG?" is feasible and valid, and can be incorporated easily into routine clinical evaluation. Muscle Nerve 57: 240-244, 2018.

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)0.002
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 score0.262
Threshold uncertainty score0.170

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.047
GPT teacher head0.318
Teacher spread0.271 · 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

Citations40
Published2017
Admission routes1
Has abstractyes

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