Practical Recommendations for Hypnotic Switching in Insomnia Management: A Canadian Expert Clinical Framework
Bibliographic record
Abstract
Insomnia disorder is a complex condition in which patients experience difficulties with sleep initiation, sleep maintenance, or early morning awakening. Chronic insomnia is defined as dissatisfying sleep quality or quantity, occurring at least three times per week, that has persisted for at least three months. Insomnia is common, with a higher incidence in certain subpopulations, including older adults (≥65 years of age) and patients with psychiatric and physical comorbidities, such as depression, anxiety, dementia, restless leg syndrome, obstructive sleep apnea, chronic pain, and alcohol or substance use disorders. Individuals experiencing insomnia often have disrupted sleep architecture, with polysomnography showing reduced time spent in the rejuvenating slow wave and rapid eye movement (REM) sleep stages. As such, insomnia can seriously impair daytime functioning, cognition, and quality of life. Further, insomnia may result in a higher risk of various conditions, including cardiovascular disease, obesity, and diabetes, though the association between insomnia and these comorbidities is likely bi-directional. Unfortunately, for a variety of reasons, the diagnosis is often missed or trivialized in medical practice. Given the profound impact of chronic insomnia, a proactive diagnosis and successful treatment is essential. The primary non-pharmacologic treatment option available for insomnia is cognitive behavioural therapy for insomnia (CBT-I), which focuses on sleep hygiene techniques, sleep restriction, circadian rhythm therapy, and cognitive therapy. Although CBT-I is the first-line treatment for insomnia and should always be recommended, it may not always be available in a timely manner, it can be costly and not every patient can afford it, some patients choose to opt out, and may not be sufficient as a single therapy approach. Thus, in many cases, pharmacotherapy may be needed in addition to or instead of CBT-I to treat insomnia and improve daytime functioning and associated cardiovascular and metabolic risks. Of note, patients also often self-medicate with over-the-counter medications, including cannabis products. Currently, commonly prescribed medications for insomnia include benzodiazepine receptor agonists (BZDs; e.g., lorazepam, clonazepam) and Z-drugs (e.g., zolpidem, zopiclone, eszopiclone).10 In addition, despite their risks, antidepressants (e.g., trazodone, mirtazapine), and antipsychotics (e.g., quetiapine) have also been used to treat insomnia despite being off-label and promoting sleep indirectly.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.072 | 0.154 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.014 | 0.010 |
| Research integrity | 0.017 | 0.015 |
| Insufficient payload (model declined to judge) | 0.028 | 0.010 |
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".