4.6 Article

Effects of CPAP therapy withdrawal on exhaled breath pattern in obstructive sleep apnoea

期刊

THORAX
卷 71, 期 2, 页码 110-117

出版社

BMJ PUBLISHING GROUP
DOI: 10.1136/thoraxjnl-2015-207597

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资金

  1. Swiss National Science Foundation [CR23I2_149617, 32003B_143365/1]
  2. University of Zurich Clinical Research Priority Program Sleep and Health
  3. Marie Curie European Reintegration Grant within the 7th European Community Framework Programme [276860]
  4. Swiss National Science Foundation (SNF) [32003B_143365, CR23I2_149617] Funding Source: Swiss National Science Foundation (SNF)

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Background Obstructive sleep apnoea (OSA) is highly prevalent and associated with cardiovascular and metabolic changes. OSA is usually diagnosed by polysomnography which is time-consuming and provides little information on the patient's phenotype thus limiting a personalised treatment approach. Exhaled breath contains information on metabolism which can be analysed by mass spectrometry within minutes. The objective of this study was to identify a breath profile in OSA recurrence by use of secondary-electrospray-ionization-mass spectrometry (SESI-MS). Methods Patients with OSA effectively treated with CPAP were randomised to either withdraw treatment (subtherapeutic CPAP) or continue therapeutic CPAP for 2 weeks. Exhaled breath analysis by untargeted SESI-MS was performed at baseline and 2 weeks after randomisation. The primary outcome was the change in exhaled molecular breath pattern. Results 30 patients with OSA were randomised and 26 completed the trial according to the protocol. CPAP withdrawal led to a recurrence of OSA (mean difference in change of oxygen desaturation index between groups +30.3/h; 95% CI 19.8/h, 40.7/h, p<0.001) which was accompanied by a significant change in 62 exhaled features (16 metabolites identified). The panel of discriminating mass-spectral features allowed differentiation between treated and untreated OSA with a sensitivity of 92.9% and a specificity of 84.6%. Conclusion Exhaled breath analysis by SESI-MS allows rapid and accurate detection of OSA recurrence. The technique has the potential to characterise an individual's metabolic response to OSA and thus makes a comprehensible phenotyping of OSA possible.

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