Observation-based nocturnal sleep inventory: screening tool for sleep apnea in elderly people.
OBJECTIVE
To measure the ability of the Observation-based Nocturnal Sleep Inventory (ONSI) to detect the presence or absence of sleep apnea syndrome (SAS) in older adults.


METHODS
Cross-sectional blinded study.


METHODS
University hospital-based geriatric sleep center.


METHODS
All participants aged 70 and older were referred by physicians for suspicion of SAS.


METHODS
ONSI performed by nurses; overnight polysomnography. SAS was defined as an apnea-hypopnea index of 15 events or more per hour of sleep.


RESULTS
A total of 121 consecutive patients were evaluated for study participation. Six were excluded because of technical difficulties with polysomnography or too-frequent awakenings related to medical conditions. One hundred eleven patients completed the validation process. Polysomnography identified 68 patients as having SAS and 43 patients as not having SAS. The nurse-administered ONSI demonstrated good levels of sensitivity (90%), specificity (81%), positive predictive value (88%), and negative predictive value (83%) in screening older adults for SAS.


CONCLUSIONS
The ONSI is the first valid SAS screening tool proposed for older persons in hospitals and nursing homes. This study demonstrates that the ONSI provides accurate information; is a simple, easy-to-use bed-side tool; and is highly sensitive and specific in screening SAS when compared with overnight polysomnography results.
Onen
S-Hakki
SH
Hospices Civils de Lyon, Pôle Gériatrie, Hôpital Gériatrique Antoine Charial, Francheville, France. hakki.onen@chu-lyon.fr
Dubray
Claude
C
Decullier
Evelyne
E
Moreau
Thierry
T
Chapuis
François
F
Onen
Fannie
F
D000368:Aged; D003951:Diagnostic Errors; D005260:Female; D006801:Humans; D008297:Male; D009733:Nursing Diagnosis; D017286:Polysomnography / Q000451:nursing*; D011237:Predictive Value of Tests; D012372:ROC Curve; D012680:Sensitivity and Specificity; D012891:Sleep Apnea Syndromes / Q000175:diagnosis* / Q000451:nursing