Comparison of the single simple question and the patient acceptable symptom state in myasthenia gravis
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The single simple question (SSQ) is a simple and validated question asking what percentage of normal a patient feels with respect to their myasthenia gravis (MG), with 100% being normal. Patient acceptable symptom states (PASS) are based on a dichotomous 'Yes' or 'No' response, asking whether a patient is satisfied overall with their current status and thus measures holistic satisfaction with their MG state. Both are patient-reported self-assessments but assess different dimensions of MG. The objective was to determine thresholds for the SSQ when patients with MG achieve an acceptable PASS status. METHODS: A retrospective chart review was performed of consecutive MG patients attending a neuromuscular clinic, and SSQ and PASS responses, demographic, clinical and serological characteristics and disease severity by the MG impairment index were extracted. RESULTS: One hundred and fifty-seven consecutive patients were identified: 43 (27.4%) patients responded 'No' to the PASS question. Between the PASS 'Yes'/'No' groups, only SSQ (87.5 ± 13.4 vs. 52.3 ± 23.3; P < 0.001) and MG impairment index scores (9.2 ± 10.3 vs. 29.6 ± 16; P < 0.001) were significantly different. The receiver operating characteristic curve for PASS and SSQ had an area under the curve of 0.92 ± 0.024 (confidence interval 0.872-0.965, P < 0.001). An SSQ score ≥72.5% had 84.2% sensitivity and 86% specificity to classify patients as PASS positive. CONCLUSION: The PASS and SSQ patient-reported outcomes are closely associated and a SSQ threshold ≥72.5% predicts an acceptable MG state. Other demographic and disease-related factors did not influence the PASS response in this study.
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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 | 0.000 |
| 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) | 0.000 | 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".