The Effect of Mandibular Advancement Devices on Sympathetic Nerve Activity and Markers of Cardiovascular Health in Obstructive Sleep Apnea Patients: A Prospective Case Series Protocol
Bibliographic record
Abstract
Study Objectives:The effect of mandibular advancement devices (MADs) on sympathetic nerve activity (SNA) has not been measured directly through microneurography.Therefore, this protocol aims to determine whether MADs improve SNA, vascular health, blood pressure, and indirect markers of SNA (heart rate variability and concentrations of neurotransmitters in the blood) in adult study participants with OSA.Methods: Patients with a diagnosis of OSA will be referred by multiple dental practitioners in Edmonton, Alberta who are certified to provide MAD therapy.A sample size of 50 participants is planned, considering a 20% dropout rate.Participants will be examined at baseline and again after 3 and 6 months of efficacious MAD therapy.The following outcomes will be recorded at each time point: direct SNA via microneurography, heart rate, continuous blood pressure, flow-mediated dilation (a marker of vascular health), blood concentration of noradrenaline, apnea-hypopnea index (AHI) via a level 3 take-home sleep study, and MAD compliance via a scorecard for self-reported nighttime wear.Clinical Implications: Understanding how direct and indirect measures of SNA relate to OSA therapy may be valuable, as some participants and researchers consider microneurography an invasive and complex technique.Improved SNA and vascular health would further support MADs as an important alternative to no treatment.Finally, research examining the effect of various OSA therapies on the sympathetic influence of blood pressure and the heart is critical to understanding how changes in cardiac autonomic modulation may influence cardiovascular risk.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".