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Record W4251890312 · doi:10.32920/ryerson.14646009

Comprehensive insomnia assessment following mild traumatic brain injury

2021· preprint· en· W4251890312 on OpenAlexaff
Dóra Zalai

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsToronto Metropolitan UniversitySystems, Applications & Products in Data Processing (Canada)
Fundersnot available
KeywordsInsomniaPrimary InsomniaMedicineObstructive sleep apneaTraumatic brain injurySleep disorderPsychiatryPsychologyInternal medicine

Abstract

fetched live from OpenAlex

Background and Rationale: Insomnia symptoms following mild traumatic brain injury (mTBI) predict poor TBI outcomes. Insomnia symptoms may be caused by sleep disorders that can be effectively treated, which in turn, may improve mTBI outcomes. Previous studies have focused on insomnia symptom assessment in mTBI or evaluated samples with all TBI severities. To effectively manage insomnia following mTBI, it is important to understand which sleep disorders contribute to insomnia symptoms in this clinical group. Furthermore, it is important to extend research on primary insomnia to determine which variables are related to the perception of poor sleep among individuals who report new onset/worsening insomnia symptoms following mTBI. Objectives: (1) determine the prevalence of sleep disorders that contribute to chronic insomnia symptoms in patients with mTBI and (2) determine which objectively measured electroencephalographic and subjective variables are associated with subjective wake time and the perception of poor sleep among patients with chronic insomnia symptoms following mTBI. Methods: Individuals with chronic insomnia symptoms following mTBI (N = 50; age 17-65; 64% females; 3 - 24 months post mTBI) participated in a multi-method sleep and circadian assessment. Sleep disorders were diagnosed according to ICSD-3 criteria. Results: Insomnia disorder was the most common diagnosis (62%), followed by obstructive sleep apnea (OSA) -44%; circadian rhythm sleep-wake disorders (CRSWD) - 26% and periodic limb movement disorder (PLMD) - 8%. The overestimation of wake time was similar to what has been described in primary insomnia. In contrast to the REM instability hypothesis of primary insomnia, REM sleep duration was not related to subjective wake time. Both low sleep quality and feeling unrested in the morning had the strongest relationship to subjective wake time. Feeling unrested was also associated with anxiety. Conclusions: OSA and CRSWD frequently occur among patients whose main presenting sleep symptom is chronic insomnia following a mTBI. Accordingly, objective sleep and circadian assessment should be part of chronic insomnia evaluation following a mTBI. The results imply that interventions reducing subjective wake time and anxiety could improve subjective sleep quality; however, these interventions should be mplemented in conjunction with the treatment for OSA, CRSWD and PLMD.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.087
GPT teacher head0.415
Teacher spread0.328 · 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
Published2021
Admission routes1
Has abstractyes

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