Comparison of AutoSet (TM) and polysomnography for the detection of apnea-hypopnea events

• Autor(a) principal: Bagnato, Maurício da Cunha [UNIFESP]
• Data de Publicação: 2000
• Outros Autores: Nery, Luiz Eduardo [UNIFESP], Togeiro, Sonia Maria [UNIFESP], Bittencourt, Lia Rita Azeredo [UNIFESP], Tufik, Sergio [UNIFESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNIFESP
• Texto Completo: http://dx.doi.org/10.1590/S0100-879X2000000500005; http://repositorio.unifesp.br/handle/11600/961
• topic: obstructive sleep apnea; polysomnography; computerized diagnostic system

The use of the flow vs time relationship obtained with the nasal prongs of the AutoSetä (AS) system (diagnosis mode) has been proposed to detect apneas and hypopneas in patients with reasonable nasal patency. Our aim was to compare the accuracy of AS to that of a computerized polysomnographic (PSG) system. The study was conducted on 56 individuals (45 men) with clinical characteristics of obstructive sleep apnea (OSA). Their mean (± SD) age was 44.6 ± 12 years and their body mass index was 31.3 ± 7 kg/m2. Data were submitted to parametric analysis to determine the agreement between methods and the intraclass correlation coefficient was calculated. The Student t-test and Bland and Altman plots were also used. Twelve patients had an apnea-hypopnea index (AHI) <10 in bed and 20 had values >40. The mean (± SD) AHI PSG index of 37.6 (28.8) was significantly lower (P = 0.0003) than AHI AS (41.8 (25.3)), but there was a high intraclass correlation coefficient (0.93), with 0.016 variance. For a threshold of AHI of 20, AS showed 73.0% accuracy, 97% sensitivity and 60% specificity, with positive and negative predictive values of 78% and 93%, respectively. Sensitivity, specificity and negative predictive values increased in parallel to the increase in AHI threshold for detecting OSA. However, when the differences of AHI PSG-AS were plotted against their means, the limits of agreement between the methods (95% of the differences) were +13 and -22, showing the discrepancy between the AHI values obtained with PSG and AS. Finally, cubic regression analysis was used to better predict the result of AHI PSG as a function of the method proposed, i.e., AHI AS. We conclude that, despite these differences, AHI measured by AutoSetä can be useful for the assessment of patients with high pre-test clinical probability of OSA, for whom standard PSG is not possible as an initial step in diagnosis.