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Record W2332714133 · doi:10.1097/cnd.0b013e31824619d5

The Quantitative Myasthenia Gravis Score

2012· article· en· W2332714133 on OpenAlexaff
Carolina Barnett, Hans Katzberg, Maryam Nabavi Nouri, Vera Bril

Bibliographic record

VenueJournal of Clinical Neuromuscular Disease · 2012
Typearticle
Languageen
FieldMedicine
TopicMyasthenia Gravis and Thymoma
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsMyasthenia gravisMedicineQuality of life (healthcare)Internal medicineCorrelationNursing

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine whether the quantitative myasthenia gravis score (QMGS) accurately represents disease severity in patients with myasthenia gravis (MG). METHODS: One hundred thirty-five patients with MG from 2 previous randomized studies were included. QMGS correlation with the Myasthenia Gravis Foundation of America (MGFA) score, quality of life scale, acetylcholine receptor antibodies (AChRAbs), and electrophysiological parameters was studied. RESULTS: The QMGS showed a good correlation with the MGFA scale (r² = 0.54, P < 0.0001), jitter (rs = 0.40, P < 0.0001), and 15-item quality of life scale (rs = 0.41, P = 0.007) and was less well correlated with the 60-item myasthenia gravis-specific quality of life survey and other electrophysiological markers. No correlation was demonstrated with AchRAb titers, but AchRAb-positive patients had higher QMGS (14.2 ± 4.5) than AchRAb-negative patients (12.0 ± 3.7, P = 0.008). CONCLUSIONS: These results demonstrate that the QMGS is a valid marker for disease severity as shown by the MGFA scale, quality of life scale, and jitter, supporting the use of the QMGS as a primary outcome measure in clinical trials of MG.

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)0.005
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 score0.089
Threshold uncertainty score0.562

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.109
GPT teacher head0.426
Teacher spread0.317 · 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

Citations65
Published2012
Admission routes1
Has abstractyes

Explore more

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