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Record W2047088157 · doi:10.1196/annals.1405.038

<i>IVIG Treatment for Myasthenia Gravis</i>

2008· article· en· W2047088157 on OpenAlexaff
Lorne Zinman, Vera Bril

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2008
Typearticle
Languageen
FieldMedicine
TopicMyasthenia Gravis and Thymoma
Canadian institutionsUniversity Health NetworkHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineMyasthenia gravisExacerbationPlaceboRandomized controlled trialWeaknessClinical trialNeuromuscular diseaseInternal medicineAnesthesiaDiseaseSurgery

Abstract

fetched live from OpenAlex

Acquired myasthenia gravis (MG) is an autoimmune disorder treated with cholinesterase inhibitors and a number of immunotherapies. Intravenous immunoglobulin (IVIG) is an expensive and commonly used immunotherapy for patients with an exacerbation of MG, but its effectiveness has only recently been demonstrated in a randomized clinical trial. This paper describes the study design, results, and limitations of a double-blind, randomized, placebo-controlled trial designed to definitively determine if IVIG benefits patients with MG who present with worsening weakness. Fifty-one patients with worsening weakness due to MG were randomized to receive either 2 g/kg of IVIG over 2 days or an equivalent volume of placebo (5% dextrose in water). The Quantitative MG Score (QMG Score) for Disease Severity, a validated clinical composite scale and the primary outcome measure in the study, was calculated by a masked observer 14 and 28 days after treatment. Patients treated with IVIG demonstrated a significant improvement in QMG Score for Disease Severity at day 14 and the response persisted at day 28. The largest clinical improvement occurred in patients with more severe disease. IVIG was well tolerated with no significant side effects observed. Given the observed efficacy and safety of IVIG demonstrated in this trial, future studies are necessary to determine if there is a role for interval IVIG treatments in chronic 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)0.000
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 score0.553
Threshold uncertainty score0.311

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 studies0.0000.001
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 head0.171
GPT teacher head0.368
Teacher spread0.197 · 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

Citations26
Published2008
Admission routes1
Has abstractyes

Explore more

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