An interactive voice response diary for patients with non‐dystrophic myotonia
Bibliographic record
Abstract
INTRODUCTION: Non-dystrophic myotonia (NDM) is caused by mutations in muscle chloride and sodium channels. Currently, there is no standardized instrument for documenting symptom frequency and severity in NDM. METHODS: Subjects used an automated, interactive, telephone-based voice response diary (IVR) to record frequency and severity of stiffness, weakness, pain, and tiredness once a week for 8 weeks, after their baseline visits. RESULTS: We describe the IVR and report data on 76 subjects for a total of 385 person-weeks. Overall there were 5.1 calls per subject. Forty-eight subjects called in 5 or more times, and 14 called in 8 times. Stiffness was both the most frequent and severe symptom. Warm-up and handgrip myotonia were associated with higher severity scores for stiffness. CONCLUSIONS: IVR is a convenient technology to allow patient reporting of repeated and real-time symptom frequency and severity, and it is presently being used in a trial of mexiletine in NDM.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".