TY - GEN
T1 - A retrospective study on obstructive sleep apnea
AU - São João, Ricardo
AU - Cardoso, Andreia
AU - Domingues, Tiago Dias
AU - Fradinho, Marta
AU - Silva, Vânia
AU - Feliciano, Amélia
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - Obstructive sleep apnea (OSA) is a sleep-related breathing disorder with worldwide increasing prevalence. Polysomnography is the traditional gold standard for the diagnosis of OSA, but the fact that it is a complex, time-consuming, and expensive test contributes to the underdiagnosis of this pathology. For this reason, one usually opts for the simpler, less labor-intensive, and cheaper cardiorespiratory sleep test for the diagnosis of this syndrome. The manual analysis of these tests, which usually involves two or more qualified observers, is one of the aspects that most contributes to the amount of time spent in the analysis and, consequently, to diagnostic delay. Automatic analysis emerges as a faster alternative to the manual analysis. Based on a sample of 2559 patients monitored by the Pulmonology Department—Sleep Unit of the Hospital da Luz Setúbal during the period 2011–2019, this research concludes that there is no agreement between the manual and automatic readings of two popular OSA classification indexes.
AB - Obstructive sleep apnea (OSA) is a sleep-related breathing disorder with worldwide increasing prevalence. Polysomnography is the traditional gold standard for the diagnosis of OSA, but the fact that it is a complex, time-consuming, and expensive test contributes to the underdiagnosis of this pathology. For this reason, one usually opts for the simpler, less labor-intensive, and cheaper cardiorespiratory sleep test for the diagnosis of this syndrome. The manual analysis of these tests, which usually involves two or more qualified observers, is one of the aspects that most contributes to the amount of time spent in the analysis and, consequently, to diagnostic delay. Automatic analysis emerges as a faster alternative to the manual analysis. Based on a sample of 2559 patients monitored by the Pulmonology Department—Sleep Unit of the Hospital da Luz Setúbal during the period 2011–2019, this research concludes that there is no agreement between the manual and automatic readings of two popular OSA classification indexes.
KW - Association measures
KW - Automatic reading
KW - Concordance measures
KW - Manual reading
KW - OSA
UR - https://www.scopus.com/pages/publications/85144360173
U2 - 10.1007/978-3-031-12766-3_19
DO - 10.1007/978-3-031-12766-3_19
M3 - Conference contribution
AN - SCOPUS:85144360173
SN - 9783031127656
T3 - Springer Proceedings in Mathematics and Statistics
SP - 281
EP - 292
BT - Recent Developments in Statistics and Data Science - SPE2021
A2 - Bispo, Regina
A2 - Henriques-Rodrigues, Lígia
A2 - Alpizar-Jara, Russell
A2 - de Carvalho, Miguel
PB - Springer
T2 - 25th Congress of the Portuguese Statistical Society, SPE 2021
Y2 - 13 October 2021 through 16 October 2021
ER -