Novel breathing pattern analysis: Symmetric Projection Attractor Reconstruction improves identification of impending COPD re-exacerbations – a retrospective cohort analysis

Miquel Serna Pascual, Rebecca F. D'Cruz, Maria Volovaya, Caroline Jolley, Nicholas Hart, Gerrard Rafferty, Joerg Steier, Philip Aston, Manasi Nandi

Research output: Contribution to journalLetterpeer-review

1 Citation (Scopus)

Abstract

Acute exacerbations of COPD (AECOPD) are the second most common cause of emergency hospitalisation
worldwide, with one-quarter of patients readmitted within 30 days of discharge [1]. Each exacerbation
accelerates lung function decline [2] and is associated with a deterioration in health-related quality of life and
an increased risk of mortality in the post-discharge period [3]. Several pathophysiological changes including
decreased peak expiratory flow rate and increased dyspnoea often occur in the 3-5 days preceding an
exacerbation [4]. This time window presents an opportunity to identify AECOPD, initiate patient selfmanagement and clinical interventions aimed at mitigating hospitalisation. Sensitive and specific biomarkers of
physiological stress, which can be easily applied and interpreted in both community and clinical settings, would
facilitate earlier identification of AECOPD.
Increased respiratory rate (RR) is a well-validated biomarker of respiratory stress that is often incorporated into
patient monitoring systems, facilitating early identification of deterioration [5]. Respiratory
pressure/flow/plethysmography/thermistor waveforms are typically sampled as high-fidelity time-series data
(~100-1000 Hz) and RR measurement automated to circumvent common inconsistencies with manual breath
counting, using algorithms to detect waveform peaks [6]. However, such analysis disregards the intermediate
data points which contain information about changes in waveform morphology, quantification of which could
also help to identify physiological change. Symmetric Projection Attractor Reconstruction (SPAR) - a novel
analysis technique, overcomes this problem. SPAR replots every data point of any cyclic waveform, generating
a new visual representation (‘attractor’). Quantifiable attractor features can be extracted, providing new
diagnostic metrics pertaining to waveform morphology [7]. SPAR is resistant to baseline wander and has
previously been successfully applied to cardiovascular waveforms [8]–[10].
Original languageEnglish
Article number00164-2023
JournalERJ Open Research
Volume9
Issue number4
DOIs
Publication statusPublished - 1 Jul 2023

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