Development of Predictive Model for Detection of Sleep Apnea in Underrepresented Minorities

Purpose: Obstructive Sleep Apnea (OSA) is a sleep disorder that is caused by recurrent upper airway closure and is highly associated with hypertension. OSA is also known to be underdiagnosed in the general population. Previous studies have shown that individuals with OSA experience hypoxia which leads to elevated sympathetic nerve activity (SNA) and arterial pressure (AP). The elevated SNA has been shown to directly correlate to an increased pressor response through voluntary apneas. This pressor response is exaggerated in OSA despite the degree of hypoxia that subjects are exposed to prior to the apnea. The current standard for the diagnosis of OSA is through polysomnography (PSG) which relies on a sleep laboratory and can be inaccessible to some patients. In order to minimize or reduce underdiagnoses, the elevated systolic AP observed in OSA patients during voluntary apneas could serve as alternative or adjunctive measure with PSG along with other predictors such as the Epworth Sleepiness Scale (ESS). Methods: A combination of anthropometric data, STOPBANG, ESS and AP responses to voluntary apnea data were used to assess the predictive power for OSA in all populations. In order to achieve this, multiple regression analyses and estimations of specificity and sensitivity were determined from cohorts of patient data from sleep and of a previously collected data set. This data set includes participants with diagnosed OSA, Normotensive participants who do not have OSA, and undiagnosed participants. Results and Conclusions: The preliminary findings from this pilot study suggest that 1) addition of the pressor response to apnea enhances predictive power for OSA and 2) the predictive power is equally strong in underrepresented minority and Caucasian populations.