OBJECTIVE: Studies have shown an increased cardiovascular risk in obstructive sleep apnea (OSA) patients. In order to prioritize treatment of high risk patients, there is a need for improved cardiovascular OSA phenotyping. This study investigates the use of oxygen saturation ( SpO2) parameters for cardiovascular risk assessment of OSA patients. To this end, a novel multilevel interval coded scoring (mICS) algorithm is proposed.
METHODS: The study includes SpO2 recordings from 1987 overnight polysomnographies, of which 974 are from patients suspected to have OSA, 931 from the general population based Sleep Heart Health Study and 83 from healthy controls. The minimal SpO2 value, SpO2 upslope and amplitude ratio of desaturation over resaturation are extracted for all oxygen desaturations and averaged per patient. These three SpO2 parameters are used together with patient demographics to develop a mICS model to predict the probability that a patient had a cardiovascular comorbidity, or had already experienced a cardiovascular event, at the time of the polysomnography.
RESULTS: Including the SpO2 parameters in the mICS together with age and BMI improves the model's performance by 2.7% and leads to a test area under the curve (AUC) of 69.5% for the detection of any cardiovascular comorbidity. Moreover, an increase in AUC of 5% was obtained for the detection of cardiovascular events, resulting in an AUC of 93.5%.
CONCLUSIONS: This study shows that parameters based on SpO2 and the mICS model are useful to predict the cardiovascular comorbidity status of OSA patients.
SIGNIFICANCE: The proposed model could be used to assist in prioritizing OSA patients for treatment.