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Medline ® Abstract for Reference 86

of 'Evaluation of suspected obstructive sleep apnea in children'

Respiratory monitoring by means of an unattended device in children with suspected uncomplicated obstructive sleep apnea: a validation study.
Zucconi M, Calori G, Castronovo V, Ferini-Strambi L
Chest. 2003 Aug;124(2):602-7.
STUDY OBJECTIVE: To compare an unattended device for cardiorespiratory monitoring (POLY-MESAM; MAP; Martinsried, Germany) [P-M]with classic nocturnal polysomnography (PSG) for diagnosis of obstructive sleep apnea (OSA) in children.
DESIGN: Clinical setting.
PATIENTS: Twelve children (age range, 3 to 6 years) with highly suspected uncomplicated OSA who underwent PSG and P-M on 2 consecutive laboratory nights in a balanced manner.
MEASUREMENTS: Respiratory indexes were compared for P-M (automated analysis), hand-scored revised P-M (P-Mrev), and PSG. Analysis of contingency for cutoff levels of respiratory disturbance index (RDI) of 5 and 10 and level of agreement between P-M, P-Mrev, and PSG by the concordance method were evaluated.
RESULTS: Nine of twelve children (75%) had a PSGRDI>5, while 41.7% had an RDI>10, indicating moderate-to-severe OSA. P-M sensitivity (78%) increased with the increase of the RDI cutoff, and P-Mrev sensitivity reached 100% at the cutoff of 10. The specificity was low for RDI>5 and increased only modestly at RDI>10 (P-Mrev, 57%). Seven of 12 children (increasing to 9 children with P-Mrev) and 9 of 12 children (increasing to 11 children with P-Mrev) were correctly classified by the P-M unit when cutoffs of 5 and 10 were considered, respectively. As far as the agreement level is concerned, P-M underestimated the incidence of obstructive hypopnea and overestimated the number of central apnea cases. P-Mrev improved the latter measure.
CONCLUSION: Based on these data, the P-M device cannot be advocated for common use in a clinical setting, but it may have a role in urgent screening for highly suspected moderate-to-severe OSA.
Sleep Disorders Center, Department of Neurology, and Statistic Unit, IRCCS H San Raffaele, Milan, Italy. zucconi.marco@hsr.it