Correlation Between Oxygen Saturation and Pulse Tracing Patterns on Overnight Oximetry With Normal Desaturation Index Is an Independent Predictor of Obstructive Sleep Apnea

An Obstructive Sleep Apnea - A Novel Public Health Threat

In patients with obstructive sleep apnea (OSA) during obstructive events, episodes of hypoxia and hypercapnia may modulate the autonomic nervous system (ANS) by increasing sympathetic tone and irritability, which contributes to sympathovagal imbalance and ultimately dysautonomia. Because OSA can alter ANS function through biochemical changes, we can assume that heart rate variability (HRV) will be altered in patients with OSA. Most studies show that in both the time and frequency domains, patients with OSA have higher sympathetic components and lower parasympathetic dominance than healthy controls. These results confirm autonomic dysfunction in these patients, but also provide new therapeutic directions. Respiratory methods that modulate ANS, e.g., cardiorespiratory biofeedback, could be beneficial for these patients. Heart rate variability assessment can be used as a tool to evaluate the effectiveness of OSA treatment due to its association with autonomic impairment.

Portable evaluation of obstructive sleep apnea in adults: A systematic review

Obstructive sleep apnea (OSA) is a significant healthcare burden affecting approximately one billion people worldwide. The prevalence of OSA is rising with the ongoing obesity epidemic, a key risk factor for its development. While in-laboratory polysomnography (PSG) is the gold standard for diagnosing OSA, it has significant drawbacks that prevent widespread use. Portable devices with different levels of monitoring are available to allow remote assessment for OSA. To better inform clinical practice and research, this comprehensive systematic review evaluated diagnostic performances, study cost and patients' experience of different levels of portable sleep studies (type 2, 3, and 4), as well as wearable devices and non-contact systems, in adults. Despite varying study designs and devices used, portable diagnostic tests are found to be sufficient for initial screening of patients at risk of OSA. Future studies are needed to evaluate cost effectiveness with the incorporation of portable diagnostic tests into the diagnostic pathway for OSA, as well as their application in patients with chronic respiratory diseases and other comorbidities that may affect test performance.

A model for obstructive sleep apnea detection using a multi-layer feed-forward neural network based on electrocardiogram, pulse oxygen saturation, and body mass index

PURPOSE

To develop and evaluate a model for obstructive sleep apnea (OSA) detection using an artificial neural network (ANN) based on the combined features of body mass index (BMI), electrocardiogram (ECG), and pulse oxygen saturation (SpO2).

METHODS

Polysomnography (PSG) data for 148 patients with OSA and 33 unaffected individuals were included. A multi-layer feed-forward neural network (FNN) was used based on the features obtained from ECG, SpO2, and BMI. The receiver operating characteristic (ROC) curve and the metrics of accuracy, sensitivity, and specificity were used to evaluate the performance of the overall classification. Some other machine learning methods including linear discriminant, linear Support Vector Machine (SVM), Complex Tree, RUSBoosted Trees, and Logistic Regression were also used to compare their performance with the FNN.

RESULTS

The accuracy, sensitivity, and specificity of the proposed multi-layer FNN were 97.8%, 98.6%, and 93.9%, respectively, and the area under the ROC curve was 97.0%. Compared with the other machine learning methods mentioned above, the FNN achieved the highest performance.

CONCLUSIONS

The satisfactory performance of the proposed FNN model for OSA detection indicated that it is reliable to screen potential patients with OSA using the combined channels of ECG and SpO2 and also taking into account BMI. This strategy might be a viable alternative method for OSA diagnosis.

High-Resolution Pulse Oximetry and Titration of a Mandibular Advancement Device for Obstructive Sleep Apnea

Background: To determine whether utilizing high-resolution pulse oximetry is a viable method for evaluating the successful titration of oral appliances for the treatment of obstructive sleep apnea (OSA) patients.

Methods: Of 136 consecutive potentially eligible OSA patients, 133 were fitted with mandibular advancement devices (MADs), and 101 completed all phases of treatment. The vertical and horizontal dimensions of the appliances were adjusted based on three-nights with a high-resolution pulse oximeter during sleep and associated software after each adjustment.

Results: Significant improvements in OSA severity were apparent in patients at all disease severity levels. High-resolution pulse oximetry provided reliable guidance in the titration process of mandibular advancement therapy. In 67 subjects (66.3%), a respiratory event index of <5 events/hour was achieved.

Conclusions: OSA can be effectively treated with a MAD at any severity level, and high-resolution pulse oximetry provides critical information to guide oral appliance titration.