Literature DB >> 10188136

Prediction of sleep-disordered breathing by unattended overnight oximetry.

L G Olson1, A Ambrogetti, S G Gyulay.   

Abstract

Between January 1994 and July 1997, 793 patients suspected of having sleep-disordered breathing had unattended overnight oximetry in their homes followed by laboratory polysomnography. From the oximetry data we extracted cumulative percentage time at SaO2 < 90% (CT90) and a saturation variability index (delta Index, the sum of the differences between successive readings divided by the number of readings - 1). CT90 was weakly correlated with polysomnographic apnea/hypopnea index (AHI). (Spearman rho = 0.36, P < 0.0001) and with delta Index (rho = 0.71, P < 0.0001). delta Index was more closely correlated with AHI (rho = 0.59, P < 0.0001). In a multivariate model, only delta Index was significantly related to AHI, the relationship being AHI = 18.8 delta Index + 7.7. The 95% CI for the coefficient were 16.2, 21.4, and for the constant were 5.8, 9.7. The sensitivity of a delta Index cut-off of 0.4 for the detection of AHI > or = 15 was 88%, for detection of AHI > or = 20 was 90% and for the detection of AHI > or = 25 was 91%. The specificity of delta Index > or = 0.4 for AHI > or = 15 was 40%. In 113 further patients, oximetry was performed simultaneously with laboratory polysomnography. Under these circumstances delta Index was more closely correlated with AHI (rho = 0.74, P < 0.0001), as was CT90 (rho = 0.58, P < 0.0001). Sensitivity of delta Index > or = 0.4 for detection of AHI > or = 15 was not improved at 88%, but specificity was better at 70%. We concluded that oximetry using a saturation variability index is sensitive but nonspecific for the detection of obstructive sleep apnea, and that few false negative but a significant proportion of false positive results arise from night-to-night variability.

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Year:  1999        PMID: 10188136     DOI: 10.1046/j.1365-2869.1999.00134.x

Source DB:  PubMed          Journal:  J Sleep Res        ISSN: 0962-1105            Impact factor:   3.981


  15 in total

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Journal:  Sleep       Date:  2015-08-01       Impact factor: 5.849

3.  Interrelationships between body mass, oxygen desaturation, and apnea-hypopnea indices in a sleep clinic population.

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Journal:  Sleep       Date:  2012-01-01       Impact factor: 5.849

4.  Comparison between a single-channel nasal airflow device and oximetry for the diagnosis of obstructive sleep apnea.

Authors:  Lydia Makarie Rofail; Keith K H Wong; Gunnar Unger; Guy B Marks; Ronald R Grunstein
Journal:  Sleep       Date:  2010-08       Impact factor: 5.849

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6.  [A population study of the efficacy of pulsioxymetry in diagnosing obstructive sleep apnoea syndrome].

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Review 8.  Computer-Assisted Diagnosis of the Sleep Apnea-Hypopnea Syndrome: A Review.

Authors:  Diego Alvarez-Estevez; Vicente Moret-Bonillo
Journal:  Sleep Disord       Date:  2015-07-21

9.  Cascading detection model for prediction of apnea-hypopnea events based on nasal flow and arterial blood oxygen saturation.

Authors:  Hui Yu; Chenyang Deng; Jinglai Sun; Yanjin Chen; Yuzhen Cao
Journal:  Sleep Breath       Date:  2019-07-05       Impact factor: 2.816

10.  Daytime polysomnography for early diagnosis and treatment of patients with suspected sleep-disordered breathing.

Authors:  Seiko Miyata; Akiko Noda; Seiichi Nakata; Hidehito Yagi; Eriko Yanagi; Kumiko Honda; Tatsuki Sugiura; Shigeru Nakai; Tsutomu Nakashima; Yasuo Koike
Journal:  Sleep Breath       Date:  2007-06       Impact factor: 2.655

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