Patient-reported burden of myasthenia gravis: baseline results of the international prospective, observational, longitudinal real-world digital study MyRealWorld-MG
Bibliographic record
Abstract
OBJECTIVES: Myasthenia gravis (MG) is a rare, chronic, autoimmune neuromuscular disease which can affect functional and mental aspects of health and health-related quality of life (HRQoL). This study aims to obtain detailed knowledge of the impact of MG on HRQoL in a broad population from the perspective of the patient. DESIGN: Prospective, observational, digital, longitudinal real-world study. SETTING: Adult patients with MG from seven countries (USA, Japan, Germany, UK, Italy, Spain and Canada) downloaded a mobile application onto their phones and entered data about themselves and their MG. OUTCOME MEASURES: Data was collected using the following general and disease-specific patient-reported outcome measurements: EuroQol 5 Domains Health-Related Quality of Life Questionnaire (EQ-5D-5L), Myasthenia Gravis Activities of Daily Living (MG-ADL), Myasthenia Gravis Quality of Life 15-item revised scale (MG-QoL-15r), Hospital Anxiety and Depression Scale (HADS) and Health Utilities Index III (HUI3). Patients were categorised by their self-assessed Myasthenia Gravis Foundation of America (MGFA) class (I-V). RESULTS: Baseline results of 841 participants (mean age 47 years, 70% women) are reported . The distribution across the MGFA classes was: 13.9%, 31.0%, 38.1%, 15.5% and 1.6% for classes I-V. The MGFA class was a strong predictor of all aspects of HRQoL, measured with disease-specific and with generic instruments. The domains in which patients with MG most frequently mentioned problems were usual activities, anxiety and depression, tiredness, breathing and vision. The mean total MG-ADL Score was positively associated with increasing MGFA classes: 2.7, 4.4, 6.3 and 8.4 for MGFA classes I-IV. Mean baseline EQ-5D-5L utility was also associated with MGFA classes and was 0.817, 0.766, 0.648 and 0.530 for MGFA class I-IV. CONCLUSIONS: MG has a large impact on key aspects of health and HRQoL. The impact of this disease increases substantially with increasing disease severity.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".