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Record W4405820562 · doi:10.1016/j.bpsgos.2024.100445

Pathophysiological Models of Hypersomnolence Associated With Depression

2024· review· en· W4405820562 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBiological Psychiatry Global Open Science · 2024
Typereview
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsMcGill UniversityDouglas Mental Health University Institute
Fundersnot available
KeywordsDepression (economics)PsychologyPathophysiologyNeuroscienceMedicinePsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Up to 25% of patients with depression experience hypersomnolence (e.g., excessive daytime sleepiness, hypersomnia, and/or sleep inertia), which is associated with treatment resistance, overall poorer outcomes, and safety concerns while driving. Hypersomnolence can result from various sleep/neurological disorders or side effects from medication but is often medically unexplained in depression. In this review, we aimed to summarize the different pathophysiological models of hypersomnolence in depression to discuss their impact on nosology and to foster the development of better tailored diagnostics and treatments. We identified several potential mechanisms underlying hypersomnolence including a daytime hypoactivity of dopaminergic and noradrenergic systems, nighttime GABA (gamma-aminobutyric acid) hypoactivation, hypoperfusion, and hypoconnectivity in the medial prefrontal cortex, as well as a longer circadian period and light hyposensitivity. In some patients with depression, nighttime hyperarousal can fragment sleep and result in a complaint of excessive daytime sleepiness, thus mimicking hypersomnolence. Others might adopt maladaptive behaviors such as spending excessive time in bed, a term coined clinophilia. Objective markers of hypersomnolence, such as ambulatory ad libitum polysomnography may facilitate distinguishing between conditions that mimic hypersomnolence. Our review identified several clinical targets for hypersomnolence in depression. Low-sodium oxybate, which is approved for idiopathic hypersomnia, needs additional study in patients with depression. Neuromodulation that targets prefrontal cortex anomalies should be systematically explored, while tailored light therapy protocols may mitigate light hyposensitivity. Additionally, cognitive behavioral therapy for hypersomnolence is being developed as a nonpharmacological adjunct to these treatments. Many people with depression experience hypersomnolence, which encompasses excessive daytime sleepiness and prolonged sleep duration. Hypersomnolence is associated with safety issues, such as driving concerns, and makes depression more difficult to treat. The causes of hypersomnolence in depression are unknown. In this review of the literature, we synthesize potential causes, including reduced daytime activity in brain systems that regulate alertness, nighttime sleep disruptions, altered circadian rhythms, and behaviors like spending extended time in bed. Understanding these mechanisms may support the development of targeted treatments, such as medications, specific light therapy protocols, and customized cognitive behavioral approaches, to better manage hypersomnolence in depression.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.911
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.003
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0050.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.098
GPT teacher head0.405
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it