Myasthenia Gravis Impairment Index
Bibliographic record
Abstract
OBJECTIVE: To study responsiveness and meaningful change of the Myasthenia Gravis Impairment Index (MGII) and its relative efficiency compared to other measures. METHODS: We enrolled 95 patients receiving prednisone, IV immunoglobulin (IVIg), or plasma exchange (PLEX) and 54 controls. Patients were assessed with the MGII and other measures-including the Quantitative Myasthenia Gravis Score, Myasthenia Gravis Composite, and Myasthenia Gravis Activities of Daily Living-at baseline and 3-4 weeks after treatment. Statistical markers of responsiveness included between-groups and within-group differences, and we estimated the relative efficiency of the MGII compared to other measures. Patient-meaningful change was assessed with an anchor-based method, using the patient's impression of change. We determined the minimal detectable change (MDC) and the minimal important difference (MID) at the group and individual level. RESULTS: = 0.07). For the total MGII score, the individual MDC95 was 9.1 and the MID was 5.5 for individuals and 8.1 for groups. Relative efficiency ratios were >1 favoring the MGII. CONCLUSIONS: The MGII demonstrated responsiveness to prednisone, IVIg, and PLEX in patients with myasthenia. There is a differential response in ocular and generalized symptoms to type of therapy. The MGII has higher relative efficiency than comparison measures and is viable for use in clinical trials.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".