Psychostimulants for hypersomnia (excessive daytime sleepiness) in myotonic dystrophy
Bibliographic record
Abstract
BACKGROUND: Excessive daytime sleepiness is a common symptom of myotonic dystrophy. Psychostimulants are drugs that are increasingly used to treat hypersomnia in myotonic dystrophy. OBJECTIVES: To assess the effects of psychostimulants in myotonic dystrophy patients with hypersomnia. SEARCH METHODS: We searched the Cochrane Neuromuscular Specialised Register, CENTRAL, MEDLINE, Embase, ClinicalTrials.gov, and WHO ICTRP on 5 January 2023. We also checked the bibliographies of identified papers and made enquiries of the authors of the papers. SELECTION CRITERIA: We considered all randomised controlled trials that have evaluated any type of psychostimulant (versus a placebo or no treatment) in children or adults with myotonic dystrophy, confirmed by clinical and electromyographic diagnostic, or genetic testing, and hypersomnia. DATA COLLECTION AND ANALYSIS: Two review authors independently scrutinised potentially relevant papers for study inclusion, with any disagreements resolved by discussion. Two review authors independently performed data extraction. We obtained unpublished data from some study authors. We assessed the methodological quality of trials and applied GRADE to assess the certainty of evidence. Review authors did not contribute to eligibility or risk of bias assessment or data extraction of trials in which they had participated. When cross-over trials were included in the analysis, treatment effects were summarised as mean difference (MD) between treatment effects and standard error, and analysed by generic inverse variance. MAIN RESULTS: = 0%; low certainty evidence). No trial evaluated our primary or secondary outcomes in the long term. We were not able to perform planned subgroup analyses as none of the trials provided relevant data. AUTHORS' CONCLUSIONS: In myotonic dystrophy, the effects of psychostimulants on excessive daytime sleepiness as assessed by the Maintenance of Wakefulness Test or Multiple Sleep Latency Test and on quality of life are very uncertain. Psychostimulants may improve hypersomnia as self-evaluated by the Epworth Sleepiness Scale and may increase the risk of adverse events. More randomised trials are needed to evaluate the efficacy and safety of psychostimulants in both the short and long term.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".