ArticleDiagnostics (Basel, Switzerland)2023
Can Respiration Complexity Help the Diagnosis of Disorders of Consciousness in Rehabilitation?
Article in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Respiratory Variability in Disorders of Consciousness: Relationship and Clinical Applications.CNS neuroscience & therapeutics · 2026Article
- From zero to lab: Guidelines and practical implementation for building a multimodal experimental psychology and cognitive neuroscience laboratory.Behavior research methods · 2026Article
- Do individuals with disorders of consciousness dream and mind wander? Implications for improving diagnosis and understanding patient wellbeing.Neuroscience of consciousness · 2025Article
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7 authors.
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Abstract
backgroundAutonomic 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.
objectiveThe 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.
methodsIn 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.
resultsHigher RR complexity was significantly associated with higher consciousness levels and improved diagnostic models' performances in contrast to the ones built with only electroencephalographic descriptors.
conclusionsAdding 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.
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