Patient-acceptable symptom states in myasthenia gravis
Bibliographic record
Abstract
<h3>Objectives</h3> To estimate patient-acceptable symptom state (PASS) cut points for myasthenia gravis (MG) health scales. <h3>Methods</h3> We conducted an electronic survey that included the Myasthenia Gravis Impairment Index (MGII), EuroQol 5-Dimension (EQ5D), and a simple PASS question. PASS-anchored thresholds were estimated for the MGII questionnaire through receiver operating characteristic curves. We used the MGII PASS cut point in a validation cohort of 257 patients to estimate PASS thresholds for other clinically relevant health scales such as the Quantitative Myasthenia Gravis Scale (QMGS), Myasthenia Gravis Activities of Daily Living (MG-ADL), Myasthenia Gravis Composite (MGC), and Myasthenia Quality of Life (MG-QoL15). <h3>Results</h3> One hundred twenty-four of ≈250 invited patients answered the electronic survey (49% response rate), and 80 considered their current symptom state acceptable (PASS-positive). They had lower MGII scores than PASS-negative patients (7.76 ± 9.37 vs 25.0 ± 13.7, <i>p</i> < 0.0001) and better EQ5D scores (0.86 ± 0.17 vs 0.69 ± 0.18, <i>p</i> < 0.0001). The MGII questionnaire threshold for PASS was ≤10 points. With the use of this threshold in an independent dataset of 257 patients, all patients in remission or minimal manifestation status were PASS-positive. In addition, some patients in Classes I, II, and IIIA also achieved PASS status. PASS thresholds for the QMGS, MG-ADL, MGC, and MG-QoL15 were ≤7, 2, 3, and 8 points, respectively. <h3>Conclusions</h3> We have estimated thresholds for commonly used myasthenia health scales reflecting patient-acceptable states in patients with MG. These thresholds indicate a global state of well being, rather than a change in scores, or being better. Therefore, PASS thresholds can be used as secondary endpoints for myasthenia research.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".