Unveiling the Impact of Respiratory Event-Related Hypoxia on Heart Sound Intensity During Sleep Using Novel Wearable Technology
Bibliographic record
Abstract
Muammar M Kabir,1,2,* Atousa Assadi,1– 3,* Shumit Saha,4 Bojan Gavrilovic,1 Kaiyin Zhu,1 Susanna Mak,5 Azadeh Yadollahi1,2 1KITE-Toronto Rehabilitation Institute, University Health Network, Toronto, ON, Canada; 2Institute for Biomedical Engineering, University of Toronto, Toronto, ON, Canada; 3Temerty Center for AI Research and Education in Medicine, University of Toronto, Toronto, ON, Canada; 4Department of Biomedical Data Science, School of Applied Computational Sciences (SACS), Meharry Medical College, Nashville, TN, USA; 5Department of Medicine, Division of Cardiology, University of Toronto, Toronto, ON, Canada*These authors contributed equally to this workCorrespondence: Azadeh Yadollahi, KITE-Toronto Rehabilitation Institute, University Health Network, Room 12-106, 550 University Ave., Toronto, ON, M5G 2A2, Canada, Tel +1 416 597 3422 x 7936, Fax +1 416 597 8959, Email azadeh.yadollahi@uhn.caPurpose: Cardiovascular disorders are the leading cause of mortality worldwide with obstructive sleep apnea (OSA) as the independent risk factor. Heart sounds are strong modalities to obtain clinically relevant information regarding the functioning of the heart valves and blood flow. The objective of this study was to use a small wearable device to record and investigate the changes in heart sounds during respiratory events (reduction and cessation of breathings) and their association with oxyhemoglobin desaturation (hypoxemia).Patients and Methods: Sleep assessment and tracheal respiratory and heart sounds were recorded simultaneously from 58 individuals who were suspected of having OSA. Sleep assessment was performed using in-laboratory polysomnography. Tracheal respiratory and heart sounds were recorded over the suprasternal notch using a small device with embedded microphone and accelerometer called the Patch. Heart sounds were extracted from bandpass filtered tracheal sounds using smoothed Hilbert envelope on decomposed signal. For each individual, data from 20 obstructive events during Non-Rapid Eye Movement stage-2 of sleep were randomly selected for analysis.Results: A significant increase in heart sounds’ intensities from before to after the termination of respiratory events was observed. Also, there was a significant positive correlation between the magnitude of hypoxemia and the increase in heart sounds’ intensities (r> 0.82, p< 0.001). In addition, the changes in heart sounds were significantly correlated with heart rate and blood pressure.Conclusion: Our results indicate that heart sound analysis can be used as an alternative modality for assessing the cardiovascular burden of sleep apnea, which may indicate the risk of cardiovascular disorders. Keywords: heart sounds, obstructive sleep apnea, sympathetic nervous activity, hypoxemia, blood pressure
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".