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Record W4394979487 · doi:10.1093/sleep/zsae067.0965

0965 Investigating Cardiac Autonomic Activity During Sleep in Individuals with Major Depression and Bipolar Disorder

2024· article· en· W4394979487 on OpenAlexaffabout
Chloe Leveille, Mysa Saad, Daniel BRABANT, David H. Birnie, Elliott Kyung Lee, Alan B. Douglass, Georg Northoff, Katerina Nikolitch, Julie Carrier, Stuart Fogel, Caitlin Higginson, Tetyana Kendzerska, Rébecca Robillard

Bibliographic record

VenueSLEEP · 2024
Typearticle
Languageen
FieldMedicine
TopicHeart Rate Variability and Autonomic Control
Canadian institutionsCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalRoyal Ottawa Mental Health CentreCanadian Sleep & Circadian NetworkUniversity of Ottawa
FundersResearch Grants Council, University Grants Committee
KeywordsBipolar disorderDepression (economics)Sleep (system call)PsychologyMedicinePsychiatryMajor depressive disorderAutonomic nervous systemCardiologyClinical psychologyInternal medicineMoodHeart rateBlood pressure

Abstract

fetched live from OpenAlex

Abstract Introduction Autonomic nervous system dysfunction and reduced heart rate variability (HRV) have been reported in individuals with mood disorders, a phenomenon likely to be influenced by sleep disturbances. Several studies have previously assessed HRV in individuals with major depression or bipolar disorder across the entire sleep period. This study investigated whether distinct heart rate (HR) and HRV profiles across wake, rapid eye movement (REM) sleep, and non-REM (NREM) sleep are linked to unipolar versus bipolar mood disorders in individuals with sleep complaints. Methods Polysomnographic data was retrospectively collated for 120 adult patients with sleep complaints and depressive symptoms referred to a specialized sleep clinic for sleep assessment [60 diagnosed with bipolar disorder (70% female, mean age= 43.4±11.6 years) and 60 age-matched cases diagnosed with a unipolar depressive disorder (68.3% female, mean age= 43.2±11.6 years)], and 60 age-matched healthy controls (68.3% female, mean age= 43.4±12.6 years). HR and time-based HRV parameters were computed on 30-second segments and averaged across the night for wake and sleep stages. Results Significant group by sleep stage interactions showed that the unipolar and bipolar groups had lower standard deviation of normal-to-normal intervals (SDNN) and vagal tone root mean square of successive R-R interval differences (RMSSD) compared to controls during NREM sleep ( p≤.001) and REM sleep (p≤.003), but not during wake (p>.050). The unipolar group had significantly higher heart rate than controls regardless of sleep stages (all, p≤ .042), while the bipolar group had higher heart rate than controls only during NREM 2 (p=.012) and NREM 3 (p=.009) sleep. These interactions persisted after excluding individuals taking antipsychotic, lithium, anticonvulsant, and cardiovascular medications. Conclusion While additional research is required to account for manic and euthymic states, as well as the impact of psychotropic and cardiac medications, and potential confounders like variations in body mass index, the present findings suggest that the sleep-based autonomic signature of depressive states differs across different types of mood disorders and could potentially inform the development of biomarkers and therapeutic targets. Support (if any) This project was supported by the Ottawa Region for Advanced Cardiovascular Research Excellence (ORACLE) funding program.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.239
Teacher spread0.231 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2024
Admission routes2
Has abstractyes

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