Application of oxygen saturation variability analysis for the detection of exacerbation in individuals with COPD: A proof-of-concept study

Ahmed Al Rajeh; Amar S Bhogal; Yunkai Zhang; Joseph T Costello; John R Hurst; Ali R Mani

doi:10.14814/phy2.15132

Application of oxygen saturation variability analysis for the detection of exacerbation in individuals with COPD: A proof-of-concept study

Physiol Rep. 2021 Dec;9(23):e15132. doi: 10.14814/phy2.15132.

Authors

Ahmed Al Rajeh^{1

2}, Amar S Bhogal^{3

4}, Yunkai Zhang³, Joseph T Costello⁵, John R Hurst¹, Ali R Mani³

Affiliations

¹ UCL Respiratory, Royal Free Campus, Division of Medicine, University College London, London, UK.
² Department of Respiratory Care, King Faisal University, Al-Ahsa, Saudi Arabia.
³ Network Physiology Laboratory, Division of Medicine, UCL, London, UK.
⁴ Medical School, University of Birmingham, Birmingham, UK.
⁵ Extreme Environment Laboratory, School of Sport, Health and Exercise Science, University of Portsmouth, Portsmouth, UK.

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 (S_p 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 S_p 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 S_p O₂ variations was carried examined using sample entropy (for assessment of irregularity), the multiscale entropy (complexity), and detrended fluctuation analysis (self-similarity).

Results: S_p O₂ variations displayed a complex pattern in both stable and exacerbation phases of COPD. During an exacerbation, S_p O₂ entropy increased (p = 0.029) and long-term fractal-like exponent (α2) decreased (p = 0.002) while the mean and standard deviation of S_p O₂ time series remained unchanged. Through ROC analyses, S_p 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 S_p O₂ entropy and the fractal-like exponent have the potential to detect exacerbations in COPD. Further research is warranted to examine if S_p O₂ variability analysis could be used as a novel objective method of detecting exacerbations.

Keywords: Pulse Oximetry; SpO2; entropy; physiological measurement; respiratory.

MeSH terms

Aged
Aged, 80 and over
Disease Progression
Female
Humans
Hypoxia / physiopathology*
Male
Middle Aged
Oximetry
Oxygen Saturation / physiology*
Pilot Projects
Pulmonary Disease, Chronic Obstructive / physiopathology*