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Acute upper airway muscle and inspiratory flow responses to transcranial magnetic stimulation during sleep in apnoeic patients

2012· article· en· W1595887498 on OpenAlexafffund
César Augusto Melo‐Silva, Jean‐Christian Borel, Simon Gakwaya, Frédéric Sériès

Bibliographic record

VenueExperimental Physiology · 2012
Typearticle
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
FundersCanadian Institutes of Health Research
KeywordsTranscranial magnetic stimulationMedicineAnesthesiaAirwayNon-rapid eye movement sleepSleep (system call)StimulationNeurostimulationElectroencephalographyInternal medicine

Abstract

fetched live from OpenAlex

New Findings What is the central question of this study? Peripheral hypoglossal nerve stimulation is a novel therapeutic approach aimed at recruiting lingual muscles electrically and thus relieving pharyngeal airflow obstruction during sleep but the effects of corticomotor stimulation of upper airway muscles during sleep are unknown. What is the main finding and its importance? Using transcranial magnetic stimulation, we show that corticobulbar excitability of the submental muscles is decreased during sleep in apnoeic patients. Furthermore, we demonstrate that transcranial magnetic stimulation briefly recruits submental muscles and increases maximal inspiratory flow as well as the inspiratory volume of flow‐limited respiratory cycles without arousing patients from sleep. We suggest that this central neurostimulation approach is capable of improving upper airway mechanics in sleep apnoea patients. Transcranial magnetic stimulation (TMS) can activate the corticobulbar system and briefly recruit upper airway dilator muscles, improving the inspiratory airflow dynamics of flow‐limited respiratory cycles during sleep. The purpose of this investigation was to quantify the effects of TMS‐induced twitches applied during sleep on flow‐limited respiratory cycles in 14 obstructive sleep apnoea patients. Submental muscle motor threshold (SUB MT ) and motor‐evoked potential (SUB MEP ) were examined during wakefulness and sleep. The TMS‐induced twitches were applied during stable non‐rapid eye movement (NREM) sleep, during non‐consecutive flow‐limited respiratory cycles at the beginning of inspiration, with intensities varying from sleep SUB MT up to maximal stimulation without arousal. Maximal inspiratory flow, inspiratory volume, shifts of electroencephalogram frequency and pulse rate variability were assessed. Cortical and/or autonomic arousal after TMS was observed in only 13.8% of all twitches applied. The SUB MT increased during NREM sleep (wakefulness, 24.8 ± 9.3%; and NREM sleep, 28.3 ± 9.5%; P = 0.003). Augmenting stimulator output from SUB MT to maximal stimulation before arousal enhanced SUB MEP peak‐to‐peak amplitude (from 0.09 ± 0.05 to 0.4 ± 0.3 mV; P = 0.005) with a concomitant rise in maximal inspiratory flow (from 376.2 ± 107.9 to 411.9 ± 109.3 ml s −1 ; P = 0.008) and inspiratory volume (from 594.8 ± 189.2 to 663.7 ± 203.1 ml; P = 0.001) in all but one patient. Corticobulbar excitability of submental muscles decreases during NREM sleep. Brief recruitment of submental muscles with TMS during sleep improves upper airway mechanics without arousing patients from sleep.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.800
Threshold uncertainty score0.656

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.012
GPT teacher head0.296
Teacher spread0.284 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations21
Published2012
Admission routes2
Has abstractyes

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