Abstract
ProposalThis paper investigates a novel screening tool for Obstructive Sleep Apnea Syndrome (OSAS), which aims at efficient population-wide monitoring. To this end, we introduce SASscore which provides better OSAS prediction specificity while maintaining a high sensitivity.MethodsWe process a cohort of 2595 patients from 4 sleep laboratories in Western Romania, by recording over 100 sleep, breathing, and anthropometric measurements per patient; using this data, we compare our SASscore with state of the art scores STOP-Bang and NoSAS through area under curve (AUC), sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV). We also evaluate the performance of SASscore by considering different Apnea–Hypopnea Index (AHI) diagnosis cut-off points and show that custom refinements are possible by changing the score’s threshold.ResultsSASscore takes decimal values within the interval (2, 7) and varies linearly with AHI; it is based on standardized measures for BMI, neck circumference, systolic blood pressure and Epworth score. By applying the STOP-Bang and NoSAS questionnaires, as well as the SASscore on the patient cohort, we respectively obtain the AUC values of 0.69 (95% CI 0.66-0.73, p < 0.001), 0.66 (95% CI 0.63-0.68, p < 0.001), and 0.73 (95% CI 0.71-0.75, p < 0.001), with sensitivities values of 0.968, 0.901, 0.829, and specificity values of 0.149, 0.294, 0.359, respectively. Additionally, we cross-validate our score with a second independent cohort of 231 patients confirming the high specificity and good sensitivity of our score. When raising SASscore’s diagnosis cut-off point from 3 to 3.7, both sensitivity and specificity become roughly 0.6.ConclusionsIn comparison with the existing scores, SASscore is a more appropriate screening tool for monitoring large populations, due to its improved specificity. Our score can be tailored to increase either sensitivity or specificity, while balancing the AUC value.
Highlights
Obstructive sleep apnea syndrome (OSAS) is a serious sleep respiratory disorder, which has a prevalence that is considered by many authors as epidemic [1,2,3,4,5,6]
SASscore takes decimal values within the interval (2, 7) and varies linearly with Apnea–Hypopnea Index (AHI); it is based on standardized measures for body mass index (BMI), neck circumference, systolic blood pressure and Epworth score
By applying the STOP-Bang and NoSAS questionnaires, as well as the SASscore on the patient cohort, we respectively obtain the area under curve (AUC) values of 0.69, 0.66, and 0.73, with sensitivities values of 0.968, 0.901, 0.829, and specificity values of 0.149, 0.294, 0.359, respectively
Summary
Obstructive sleep apnea syndrome (OSAS) is a serious sleep respiratory disorder, which has a prevalence that is considered by many authors as epidemic [1,2,3,4,5,6]. SDB increases the mortality rate [9], because it contributes to the development of cardiovascular diseases [10] such as hypertension [11], type 2 diabetes [12], cancer [13], and chronic kidney disease [14]. Because it is associated with many co-morbidities [15], SDB has several distinct clinical phenotypes. If not properly diagnosed and treated, SDB may increase morbidity and preoperative risks as well [16,17,18,19,20]
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