Surrogate therapeutic outcome measures in patients with myasthenia gravis
Bibliographic record
Abstract
Treatment of acquired myasthenia gravis (MG) with immunotherapies successfully relieves symptoms and improves strength as documented by the Quantitative Myasthenia Gravis Score for disease severity (QMGS). Neuromuscular function, as demonstrated by the surrogate measures of repetitive nerve stimulation (RNS) and single-fiber electromyography (SFEMG), is sensitive for diagnosis and staging disease severity. This study of 51 patients treated with immunomodulation confirmed that RNS and SFEMG are useful to stage disease severity, but found that clinical measures such as the QMGS are more sensitive to change than electrophysiological parameters. The presence of blocking on SFEMG did predict responsiveness to intravenous immunoglobulin (IVIG) treatment, providing clinicians with an objective, reliable, quantitative measure to help determine which patients will benefit from this costly treatment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".