Application of oxygen saturation variability analysis for the detection of exacerbation in individuals with COPD: A proof‐of‐concept study. Issue 23 (1st December 2021)

• Record Type: Journal Article
• Authors: Al Rajeh, Ahmed; Bhogal, Amar S.; Zhang, Yunkai; Costello, Joseph T.; Hurst, John R; Mani, Ali R.
• Is Part Of: Physiological reports. Volume 9:Issue 23(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12-01
• Subjects: entropy -- physiological measurement -- Pulse Oximetry -- respiratory -- SpO2; Physiology -- Periodicals; 571
• DOI: 10.14814/phy2.15132
• Languages: English
• ISSNs: 2051-817X

Abstract

Abstract: Background: Individuals with chronic obstructive pulmonary disease (COPD) commonly experience exacerbations, which may require hospital admission. Early detection of exacerbations, and therefore early treatment, could be crucial in preventing admission and improving outcomes. Our previous research has demonstrated that the pattern analysis of peripheral oxygen saturation (Sp O2 ) fluctuations provides novel insights into the engagement of the respiratory control system in response to physiological stress (hypoxia). Therefore, this pilot study tested the hypothesis that the pattern of Sp O2 variations in overnight recordings of individuals with COPD would distinguish between stable and exacerbation phases of the disease. Methods: Overnight pulse oximetry data from 11 individuals with COPD, who exhibited exacerbation after a period of stable disease, were examined. Stable phase recordings were conducted overnight and one night prior to exacerbation recordings were also analyzed. Pattern analysis of Sp O2 variations was carried examined using sample entropy (for assessment of irregularity), the multiscale entropy (complexity), and detrended fluctuation analysis (self‐similarity). Results: Sp O2 variations displayed a complex pattern in both stable and exacerbation phases of COPD. During an exacerbation, Sp O2 entropy increased ( p = 0.029) and long‐term fractal‐like exponent (α2) decreased ( p = 0.002) while the mean and standard deviation of Sp O2 time series remained unchanged. Through ROC analyses, Sp O2 entropy and α2 were both able to classify the COPD phases into either stable or exacerbation phase. With the best positive predictor value (PPV) for sample entropy (PPV = 70%) and a cut‐off value of 0.454. While the best negative predictor value (NPV) was α2 (NPV = 78%) with a cut‐off value of 1.00. Conclusion: Alterations in Sp O2 entropy and the fractal‐like exponent have the potential to detect exacerbations in COPD. Further research is warranted to examine if Sp O2 variability analysis could be used as a novel objective method of detecting exacerbations. Abstract : This report provides evidence that the pattern of peripheral oxygen saturation (Sp O2 ) fluctuations detects exacerbations in individuals with COPD. The entropy of Sp O2 signal increases a day prior to clinical diagnosis of exacerbation in COPD while mean and total variability of Sp O2 signals remain unchanged. This finding has potential for development of a non‐invasive method for early detection of exacerbations in COPD.