Myasthenia gravis - a retrospective analysis of e-mail inquiries made to a patient organisation and specialized center to uncover unmet needs from patients and caregivers
Bibliographic record
Abstract
Abstract Background and aims Myasthenia Gravis requires expert treatment from specialized neurologists. In Germany, this treatment is mainly provided by 18 Integrated Myasthenia Centers (iMZ) accredited by the German Myasthenia Gravis Association (DMG). The DMG is a large and well-organized patient organisation that is regarded as a trusted source for disease-specific information. The aim of this study was to analyse the type of requests that each of these institutions receives in order to identify any potential unmet needs regarding the availability of advice for patients and caregivers. This data can then be used in further research to tailor modern digital communication tools to the specific needs of MG patients. Methods Counselling requests sent via e-mail to both institutions were extracted for defined examination periods and divided into a period ‘before COVID-19 pandemic’ (01.07.2019–31.12.2019) and ‘during COVID-19 pandemic’ (01.07.2020–31.12.2020). Requests were then analysed using four main categories: medical requests, organisational issues, COVID-19 and social legislation inquiries. Results One thousand seven hundred eleven requests for advice were addressed to DMG and iMZ Charité. Most inquiries directed to the DMG (47%; n = 750) were related to medical issues, most frequently to side effects of medications (n = 325; 20%) and questions about treatment (n = 263; 16%), followed by inquiries regarding organisational issues (26%; n = 412). About half of the inquiries (n = 69; 58%) to the iMZ Charité were related to medical issues and almost one in three inquiries concerned organisational issues (n = 37; 30%). About one in ten inquiries concerned socio-legal matters (iMZ: n = 7; 6% and DMG: n = 177; 11%). During the pandemic, COVID-19 related issues accounted for 8% (n = 6) of inquiries at iMZ, and 16% (n = 253) at DMG. Conclusions MG sufferers have a high demand for timely advice. In the current setting, they address their requests to both iMZs and the DMG via e-mail. Our findings confirm that the DMG is highly trusted by patients and caregivers and is used to obtain second opinions. A relevant proportion of requests to the iMZ could be answered more effectively through standardized responses or improved process management. The implementation of modern digital solutions, including telemedicine, for communication between patient and specialist should be evaluated in further research.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".