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Record W4411685759 · doi:10.1093/sleep/zsaf168

Effect of chronic benzodiazepine and benzodiazepine receptor agonist use on sleep architecture and brain oscillations in older adults with chronic insomnia

2025· article· en· W4411685759 on OpenAlexaff
Loïc Barbaux, Aurore A. Perrault, Nathan Cross, Oren M. Weiner, Mehdi Essounni, Florence B. Pomares, Lukia Tarelli, Margaret M. McCarthy, Antonia Maltezos, Dylan Smith, Kirsten Gong, Jordan O’Byrne, Victoria Yue, Caroline Desrosiers, Doris Clerc, Francis Andriamampionona, David Lussier, Suzanne Gilbert, Cara Tannenbaum, Jean-Philippe Gouin, Thien Thanh Dang‐Vu

Bibliographic record

VenueSLEEP · 2025
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsMcGill University Health CentreStatistics CanadaUniversité de MontréalConcordia UniversityCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalInstitut Universitaire de Gériatrie de Montréal
Fundersnot available
KeywordsBenzodiazepineInsomniaPolysomnographyNon-rapid eye movement sleepSleep (system call)PsychologySlow-wave sleepAgonistElectroencephalographyAnesthesiaMedicineAudiologyNeuroscienceInternal medicinePsychiatryReceptor

Abstract

fetched live from OpenAlex

STUDY OBJECTIVES: Insomnia in older adults is associated with widespread benzodiazepine (BZD) and benzodiazepine receptor agonist (BZRA) use despite evidence that chronic use disrupts sleep regulation and cognition. Little is known about BZD/BZRA effects on Non-rapid eye movement (NREM) slow oscillations (SO), spindles and their coupling, which is crucial for memory in older adults. Our objective was to investigate the effects of chronic BZD/BZRA use on sleep macro-architecture, electroencephalogram (EEG) relative power, SO and spindle characteristics and coupling. METHODS: After habituation polysomnography, second-night data were analyzed from 101 participants (66.05 ± 5.84 years, range: 55-80 years, 73 per cent female) were categorized into three groups: good sleepers (GS, n = 28), individuals with insomnia (INS, n = 26) or individuals with insomnia who chronically use BZD/BZRA (MED, n = 47; diazepam equivalent: 6.1 ± 3.8 mg per use; >3 nights/week). We performed a comprehensive comparison of sleep architecture, EEG relative spectrum, and associated brain oscillatory activities, focusing on SO and spindles and their temporal coupling. RESULTS: MED showed disrupted sleep architecture with lower N3 and higher N1 duration and spectral activity and altered sleep-related brain oscillations synchrony, compared to INS and GS. An exploratory interaction model suggested that chronic use of higher doses (mg per use) correlated with more pronounced disruptions in sleep micro-architecture and EEG spectrum. CONCLUSIONS: Our results suggest that chronic BZD and BZRA use is associated with poorer sleep quality. Such alteration of sleep regulation-at the macro and micro-architectural levels-may contribute to the reported association between BZD/BZRA use and cognitive impairment in older adults. Statement of Significance Widespread use of sedative-hypnotics is driven by high insomnia rates among older adults. Chronic use can disrupt cognitive function; however, its impact on sleep regulation is not well understood. We assessed the effect of chronic benzodiazepine use in older adults using a between-group design involving good sleepers, drug-free individuals with insomnia disorder and individuals with insomnia disorder who chronically use sedative-hypnotics as a sleep aid. We performed a comprehensive comparison of sleep architecture, electroencephalogram relative spectrum, and associated NREM brain oscillations related to memory consolidation. We showed that chronic use of sedative-hypnotics is detrimental to sleep regulation-at the macro and micro-level-and this may contribute to the reported link between sedative-hypnotic use and cognitive impairment in older adults.

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 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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.776
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.265
Teacher spread0.257 · 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 teacher head, not a consensus.

Study designBench or experimental
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".

Quick stats

Citations14
Published2025
Admission routes1
Has abstractyes

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