Fatigue and daytime sleepiness rating scales in myotonic dystrophy: a study of reliability
Bibliographic record
Abstract
OBJECTIVES: To assess the reliability of the Epworth Sleepiness Scale (ESS), Daytime Sleepiness Scale (DSS), Chalder Fatigue Scale (CFS), and Krupp's Fatigue Severity Scale (KFSS) in patients with myotonic dystrophy type 1 (DM1). METHODS: In total, 27 patients with DM1 were administered the questionnaires on two occasions, with a 2 week interval. Internal consistency and test retest reliability were measured using intraclass correlation coefficients (ICCs), and Cronbach's alpha, Cohen's kappa, and Goodman-Kruskal's gamma coefficients. RESULTS: Internal consistency of the CFS and KFSS were adequate (alpha > 0.70) but that of the ESS was weak (alpha = 0.24). Both daytime sleepiness and fatigue rating scales showed significant test retest reliability. Test retest reliability for individual items revealed inconsistencies for some ESS and CFS items. CONCLUSIONS: Reliability of the CFS, DSS, and KFSS was high, allowing their use for individual patients with DM1, but that of the ESS was lower, rendering its current usage in DM1 questionable. Fatigue rating scales such as the KFSS, which are based on the behavioural consequences of fatigue, may constitute a more accurate and comprehensive measure of fatigue severity in the DM1 population.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".