1244 Non-24-Hour Sleep-Wake Rhythm Disorder: a successful case of a 50 years-old blind woman
Bibliographic record
Abstract
Non-24-hour sleep-wake disorder (N24SWD) is characterised by insomnia and/or excessive daytime sleepiness due to misalignment between the 24-hour light-dark cycle and the endogenous circadian rhythm. Blind individuals are more susceptible to have nonentrained circadian rhythms due to the lack of photic input to the circadian pacemaker. A 50-years-old totally blind woman, married, mother of two children and retired for 14 years was referred to Université Laval Sleep Clinic. She has complained of excessive daytime sleepiness (Epworth=20/24) and great fatigue for eight years. She also reported disruption in her self-esteem and social/occupational functioning. She was diagnosed with sleep apnea in 2012 and with RLS/PLMS in 2015. These sleep disorders were addressed, respectively, with a CPAP machine and the intake of 300 mg of iron every night. The results of her MSLT demonstrated sleep latency within the normal. At the Sleep Clinic, the patient meet the criteria for N24SWD and agoraphobia. She has past medical history of depression with suicidal ideation. Citalopram and Bupropion had been addressed since 2009 in order to prevent recurrence of depression. Her treatment was based on CBT-I adapted for excessive daytime sleepiness and anxiety-depressive symptoms. Actigraphy and sleep diaries were used to monitor her sleep patterns, wakes times and the alignment of her sleep to external environment. Light therapy twice a day and structured social and physical activities were also employed. Her drugs doses were revised, since Citalopram is likely to increase sleepiness and RLS/PLMS symptoms. The patient totalised 23 sessions at the Sleep Clinic from March 2015 to March 2016. The synchronization between her circadian rhythm and the 24-hour light-dark cycle, as well as the use of light therapy and the reduction of Citalopram’s dose helped her to significantly decrease fatigue and daytime sleepiness levels (Epworth=7/24), stabilise her humor, and increase general daytime functioning.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| 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".