Patient-reported impact of myasthenia gravis in the real world: findings from a digital observational survey-based study (MyRealWorld MG)
Bibliographic record
Abstract
OBJECTIVES: This study aims to explore the impact of myasthenia gravis (MG) - in terms of treatments, side effects, comorbidities, psychological health and work or study- in the real world from a patient perspective. DESIGN AND PARTICIPANTS: This is a prospective, observational, digital, longitudinal study. Adults diagnosed with MG residing in the USA, Japan, Germany, the UK, Italy, Spain or Canada were eligible to participate in the study. There were no other exclusion criteria. Participants used a bespoke smartphone application to confirm eligibility, provide consent and enter data about their MG into a profile, a tracker to record MG-related events and a series of patient-reported outcome instruments. 1693 participants completed at least 1 survey and were included in this analysis. RESULTS: Results are presented as a percentage of respondents to each survey question. The study population was largely female (69% of 1586 respondents), with an average age of 49.9 years (SD 14.8). In the previous 12 months, 83.7% of 1412 respondents confirmed that they had received one or more routine treatments for MG, and 67.1% of 255 respondents confirmed that they had experienced a side effect in the previous month. Commonly experienced comorbidities reported by 966 respondents were thyroid problems, hypertension and anxiety, experienced by 37.5%, 31.4% and 28.0% of respondents, respectively.According to 889 respondents to the Hospital Anxiety and Depression Scale survey, 52.7% and 43.2% had a score indicative of at least mild anxiety and mild depression, respectively. Of 257 respondents, 33.0% reported experiencing a work or study impact in the past month. CONCLUSIONS: This analysis of baseline characteristics of the MyRealWorld MG study population indicates that, despite current treatments, patients experience notable burden. Further scheduled analyses will develop a longitudinal picture of MG burden. TRIAL REGISTRATION NUMBER: NCT04176211.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.006 |
| 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 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".