Identifying sleep apnea from self-reports

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 qu...

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Bibliographic Details
Published in:Sleep (New York, N.Y.) N.Y.), 1988-10, Vol.11 (5), p.430-436
Main Authors: KAPUNIAI, L. E, ANDREW, D. J, CROWELL, D. H, PEARCE, J. W
Format: Article
Language:English
Subjects:
Adenoidectomy
Adolescent
Adult
Aged
Biological and medical sciences
Female
Fundamental and applied biological sciences. Psychology
Humans
Male
Middle Aged
Monitoring, Physiologic
Postoperative Complications - diagnosis
Sleep Apnea Syndromes - diagnosis
Sleep Apnea Syndromes - physiopathology
Sleep Stages - physiology
Sleep. Vigilance
Vertebrates: nervous system and sense organs
Citations: Items that cite this one
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Summary: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 greater than 5) or nonapnea (AI, AHI less than or equal to 5) groups. Self-reports of "stops breathing during sleep," "loud snoring," and history of adenoidectomy best discriminated normal (AI less than or equal to 5) from apnea (AI greater than 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 "stops 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 greater than 40) and 70-76% of all sleep apnea cases with AI or AHI greater than 5. Predictive accuracy was 88% for AI greater than 10. The two questions that comprise the AS should be incorporated into risk appraisal instruments or interviews to screen for sleep apnea.
ISSN:0161-8105
1550-9109
DOI:10.1093/sleep/11.5.430