Validation of the Italian version of the Myasthenia Gravis Impairment Index (MGII)
Bibliographic record
Abstract
OBJECTIVE: To validate the Italian version of the Myasthenia Gravis Impairment Index (MGII). INTRODUCTION: MGII is a recent promising measure developed for MG patient evaluation. It includes a clinical severity evaluation and a patient-reported questionnaire. It has been developed in English and has demonstrated feasibility, reliability, and construct validity. Recently, its Dutch translation has been validated. METHODS: MGII was translated to Italian with a multi-step forward process. We assessed correlations with the following scores: Istituto Nazionale Carlo Besta score for Myasthenia Gravis (INCB-MG), the MG Activities of Daily Living (MG-ADL), the Myasthenia Gravis Composite (MGC), the Quality of Life 15 for Myasthenia Gravis (QOL15-MG), and the Myasthenia Gravis Disability (MGDIS). We also assessed differences in MGII scores by disease severity with the ANOVA Kruskal-Wallis test. RESULTS: One hundred forty-one patients were enrolled. The mean MGII total score was 13.3 ± 11.9 (range 0-49), with a mean ocular subscore of 3.7 ± 4.7 and a mean MGII generalized subscore of 9.6 ± 9.0. As expected, the MGII had a good correlation with the other severity scores. The MGII had a lower floor effect (3.5%) than the other measures. Twenty-five patients were assessed in follow-up; as expected, the MGII change scores had moderate correlations with change in other MG severity measures and lower correlations with quality of life measures. CONCLUSIONS: The MGII score was cross-culturally validated in an Italian cohort of MG patients. We confirmed its lower floor effect and the correlations with other MG measures including INCB-MG that was not evaluated in previous studies.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".