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. 2023 Jan 30;13(3):507.
doi: 10.3390/diagnostics13030507.

Can Respiration Complexity Help the Diagnosis of Disorders of Consciousness in Rehabilitation?

Piergiuseppe Liuzzi  1   2 , Antonello Grippo  1 , Francesca Draghi  1 , Bahia Hakiki  1 , Claudio Macchi  1   3 , Francesca Cecchi  1   2   1   3 , Andrea Mannini  1
Affiliations

Can Respiration Complexity Help the Diagnosis of Disorders of Consciousness in Rehabilitation?

Piergiuseppe Liuzzi et al. Diagnostics (Basel). .

Abstract

Background: Autonomic Nervous System (ANS) activity, as cardiac, respiratory and electrodermal activity, has been shown to provide specific information on different consciousness states. Respiration rates (RRs) are considered indicators of ANS activity and breathing patterns are currently already included in the evaluation of patients in critical care.

Objective: The aim of this work was to derive a proxy of autonomic functions via the RR variability and compare its diagnostic capability with known neurophysiological biomarkers of consciousness.

Methods: In a cohort of sub-acute patients with brain injury during post-acute rehabilitation, polygraphy (ECG, EEG) recordings were collected. The EEG was labeled via descriptors based on American Clinical Neurophysiology Society terminology and the respiration variability was extracted by computing the Approximate Entropy (ApEN) of the ECG-derived respiration signal. Competing logistic regressions were applied to evaluate the improvement in model performances introduced by the RR ApEN.

Results: Higher RR complexity was significantly associated with higher consciousness levels and improved diagnostic models' performances in contrast to the ones built with only electroencephalographic descriptors.

Conclusions: Adding a quantitative, instrumentally based complexity measure of RR variability to multimodal consciousness assessment protocols may improve diagnostic accuracy based only on electroencephalographic descriptors. Overall, this study promotes the integration of biomarkers derived from the central and the autonomous nervous system for the most comprehensive diagnosis of consciousness in a rehabilitation setting.

Keywords: ECG-derived respiration; approximate entropy; autonomic nervous system; disorders of consciousness; instrumental assessment of consciousness; respiration rate complexity.

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Conflict of interest statement

There are no conflict of interest to declare.

Figures

Figure 1
Figure 1
Approximate Entropy (ApEN) of respiration rate (RR) intervals across consciousness states. Legend. ApEN: Approximate Entropy; UWS: Unresponsive Wakefulness Syndrome; MCS: Minimally Consciousness State; EMCS: Emergence from MCS.
See this image and copyright information in PMC

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