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Record W4394978981 · doi:10.1093/sleep/zsae067.0952

0952 Subjective Sleep Improvements Following Daily Theta-burst Stimulation for Treatment-resistant Depression

2024· article· en· W4394978981 on OpenAlexaffabout
Jennifer Cuda, David Smith, Arthur R. Chaves, Reggie Taylor, Jessica Drodge, Stacey Shim, Youssef Nasr, Karina Fonseca, Ram Brender, Ruxandra Antochi, Lisa McMurray, Rébecca Robillard, Sara Tremblay

Bibliographic record

VenueSLEEP · 2024
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsRoyal Ottawa Mental Health CentreUniversity of Ottawa
Fundersnot available
KeywordsDepression (economics)Sleep (system call)Treatment-resistant depressionStimulationWakefulnessPsychologyAudiologyInsomniaMedicinePsychiatryNeuroscienceAnesthesiaElectroencephalographyMoodMajor depressive disorder

Abstract

fetched live from OpenAlex

Abstract Introduction Sleep disturbances are commonly observed in individuals with depression, and are associated with severity of depression, treatment outcomes, and risk of relapse. Repetitive transcranial magnetic stimulation, including newer optimized theta-burst stimulation (TBS) protocols, is recognized as a safe and effective intervention for treatment-resistant depression (TRD). Presently, little is known about the impact of TBS treatments on sleep in individuals with depression. We examined changes in subjective sleep and depression in individuals with TRD receiving daily TBS treatments, and the relationship between changes in these symptom domains. Methods 50 participants (50% female, mean age 46.82 years) with TRD received four or six weeks of daily TBS treatments targeting the left or bilateral dorsolateral prefrontal cortex while participating in a randomized, double-blind clinical trial. Sleep disturbances and depression severity were measured at baseline, session 20 and session 30 using the Leeds Sleep Evaluation Questionnaire and 17-item Hamilton Rating Scale for Depression (HRSD-17), respectively. Linear mixed models examined whether scores changed significantly throughout treatment. Spearman’s correlations investigated whether changes in depression and sleep were associated. Results HRSD-17 scores improved significantly from baseline to weeks 4 and 6 (p< 0.001). We also observed significant improvements in quality of sleep (QOS), ease of awakening from sleep (AFS), and behaviour following wakefulness (BFW) after 4 and 6 weeks of TBS (p< 0.001). After 4 weeks of TBS, improvements in HRSD-17 significantly correlated with BFW scores (p= 0.008). After 6 weeks of TBS, improvements in HRSD-17 scores significantly correlated with improvements in both AFS and BFW scores (p< 0.005). Conclusion Participants reported improvements in depression, sleep quality, ease of waking, and daytime alertness following TBS. Furthermore, improvements in several aspects of sleep and depression were correlated. These findings suggest that TBS may be an effective intervention for individuals experiencing comorbid depression and sleep disturbances. This also strengthens the view that sleep enhancement may contribute to better mental health outcomes. Support (if any) Support was provided by the Royal’s Institute of Mental Health Research’s Emerging Research Innovators in Mental Health award, the Fonds de Recherche en Santé – Québec Research Scholar Junior 1 grant (grant number 297133), and an anonymous donation.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.045
GPT teacher head0.338
Teacher spread0.293 · 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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