Assessing cardiovascular comorbidities in sleep apnea patients using SpO2

摘要

Several studies have demonstrated the relationship between Obstructive Sleep Apnea Syndrome (OSAS) and cardiovascular comorbidities. It is even suggested that timely OSAS treatment can prevent the development of such comorbidities. Hence, it is important to identify the patients with a high risk for cardiovascular comorbidities and prioritize their treatment. This study investigates if the blood oxygen saturation (SpO₂) signal could be used to assess the cardiovascular status of the patient. This on its turn can improve the phenotyping of OSAS patients. SpO₂ signals from 100 OSAS patients, of which half have a known cardiovascular comorbidity, are investigated. The individual oxygen desaturations are extracted and these desaturations are classified as caused by a respiratory event or not. This classification is then used to compute patient averaged features of apneic and non-apneic desaturations. The most discriminative features to differentiate between patients with and without cardiac comorbidity are selected. Using these, a Least-squares Support Vector Machine (LS-SVM) classifier reached an accuracy of 76.7 % on separating test set patients according to their cardiac comorbidity status. These results suggest that the analysis of the SpO2 signal has an added value in the assessment of the cardiovascular risk of OSAS patients.