A polysomnographic study of daytime sleepiness in myotonic dystrophy type 1
Bibliographic record
Abstract
OBJECTIVES: To assess contributors to excessive daytime sleepiness (EDS) in myotonic dystrophy type 1 (DM1), to characterise subjects with sleep-onset REM periods (SOREMPs), and to verify whether self-reported instruments and respiratory function tests can predict multiple sleep latency test (MSLT) and sleep-disordered breathing. METHODS: A sample of 43 DM1 patients without selection bias underwent polysomnography (PSG) for two consecutive nights and MSLT, completed a sleep diary and Epworth Sleepiness Scale (ESS), and were assessed for respiratory function and narcolepsy symptoms. RESULTS: ESS scores (ES) > or =11 and MSLT mean sleep latency (MSL) < or =8 min were found in 21 (50.0%) and 19 (44.2%) subjects, and either in 30 (69.8%) subjects. ES did not relate to MSL. Subjects with subjective sleepiness (ES> or =11) reported more cataplexy-like and sleep paralysis symptoms, longer habitual sleep times, and higher sleep efficiency and REM sleep per cent than those without. Subjects with objective sleepiness (MSL< or =8 min) had a higher stage 4 sleep per cent. Subjects with > or =2 SOREMPs (25.6%) showed higher muscular impairment, lower MSL, higher ES, and more cataplexy-like symptoms than those with < or =1 SOREMP. Apnoea-hypopnoea index (AHI) > or =5, predominantly obstructive, was found in 37 (86.0%) subjects, and AHI >30 in 12 (27.9%). Neither subjective nor objective sleepiness could be explained by AHI, nor satisfactorily predicted by daytime respiratory abnormalities. CONCLUSIONS: DM1 entails frequent EDS but with different phenotypes and distinct mechanisms involved. The high prevalence of daytime sleepiness and severe sleep apnoeas found in this study supports the routine use of clinical sleep interviews, PSG and MSLT in DM1, and emphasises the need for more randomised trials of psychostimulants.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".