The utility of a single simple question in the evaluation of patients with myasthenia gravis
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".