A Conceptual Framework for Evaluating Impairments in Myasthenia Gravis
Bibliographic record
Abstract
BACKGROUND: Myasthenia gravis is characterized by weakness and fatigability of different muscle groups, including ocular, bulbar and the limbs. Therefore, a measure of disease severity at the impairment level in myasthenia needs to reflect all the relevant impairments, as well as their variations with activity and fatigue. We conducted a qualitative study of patients with myasthenia, to explore their experiences and related impairments, aimed at developing a conceptual framework of disease severity at the impairment level in myasthenia gravis. METHODS: Twenty patients representing the spectrum of disease participated in semi-structured interviews. Interviews were recorded and the transcripts were analyzed by content analysis using an inductive approach with line-by-line open coding. Themes were generated from these codes. RESULTS: Two main themes were identified: the severity of the impairments and fatigability (i.e., triggering or worsening of an impairment with activity). The impairments were further classified within body regions (ocular, bulbar and axial/limbs). Fatigability was described as a phenomenon affecting the whole body but also affecting specific impairments, and was associated with fluctuation of the symptoms. Patients were concerned that clinical examination at a single point in time might not reflect their true clinical state due to fatigability and fluctuations in severity. CONCLUSIONS: This conceptual framework reflects the relevance of both severity and fatigability in understanding impairment-based disease severity in myasthenia. This framework could inform the development of impairment measures in myasthenia gravis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".