Identifying sleep apnea from self-reports

Abstract

An apnea score (AS) was developed as a potential screening tool for sleep apnea. This was based on self-report questionnaire responses of 76 sleep disorder center patients and 20 sleep survey volunteers. Twenty volunteers and 23 patients (group I) comprised the initial AS development group. Their questionnaire responses were compared to polysomnographic apnea indexes (AI) and apnea plus hypopnea indexes (AHI). Stepwise multivariate discriminant analysis was used to test whether or not selected group I questionnaire responses could be used to correctly classify respondents into apnea. (AI or AHI > 5) or nonapnea (AI, AHI ≤ 5) groups. Self-reports of 'stops breathing during sleep', 'loud snoring', and history of adenoidectomy best discriminated normal (AI ≤ 5) from apnea (AI > 5) cases. The AS derived from group I responses to these three variables was then computed for group II (n = 53). After examination of the AS results, the AS was modified to include just 'stop breathing' and 'loud snoring' and the AI criterion was raised to 10 per hour. This revised AS correctly identified 100% of the cases with moderate-severe sleep apnea (AI or AHI > 40) and 70-76% of all sleep apnea cases with AI or AHI > 5. Predictive accuracy was 88% for AI > 10. The two questions that comprise the AS should be incorporated into risk appraisal instruments or interviews to screen for sleep apnea.