EAMI: A qualitative quantification of periodic breathing based on amplitude of oscillations

• Main Authors: Tellez, Helio Fernandez, Pattyn, Nathalie, Mairesse, Olivier, Dolenc-Groselj, Leja, Eiken, Ola, Mekjavic, Igor I.B., Migeotte, Pierre-François, Macdonald-Nethercott, Eoin, Meeusen, Romain, Neyt, Xavier
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2015
• Subjects: Physiologie générale; Neurologie; Cheyne-Stokes respiration; Loop gain; Modulating index; Periodic breathing; Quantification; Antarctic; Antarc*; Antarctica
• Online Access: http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/198520; https://dipot.ulb.ac.be/dspace/bitstream/2013/198520/3/doi_182147.pdf

Study Objectives: Periodic breathing is sleep disordered breathing characterized by instability in the respiratory pattern that exhibits an oscillatory behavior. Periodic breathing is associated with increased mortality, and it is observed in a variety of situations, such as acute hypoxia, chronic heart failure, and damage to respiratory centers. The standard quantification for the diagnosis of sleep related breathing disorders is the apnea-hypopnea index (AHI), which measures the proportion of apneic/hypopneic events during polysomnography. Determining the AHI is labor-intensive and requires the simultaneous recording of airflow and oxygen saturation. In this paper, we propose an automated, simple, and novel methodology for the detection and qualification of periodic breathing: the estimated amplitude modulation index (eAMI). Patients or Participants: Antarctic cohort (3,800 meters): 13 normal individuals. Clinical cohort: 39 different patients suffering from diverse sleep-related pathologies. Measurements and Results: When tested in a population with high levels of periodic breathing (Antarctic cohort), eAMI was closely correlated with AHI (r = 0.95, P < 0.001). When tested in the clinical setting, the proposed method was able to detect portions of the signal in which subclinical periodic breathing was validated by an expert (n = 93; accuracy = 0.85). Average eAMI was also correlated with the loop gain for the combined clinical and Antarctica cohorts (r = 0.58, P < 0.001). Conclusions: In terms of quantification and temporal resolution, the eAMI is able to estimate the strength of periodic breathing and the underlying loop gain at any given time within a record. The impaired prognosis associated with periodic breathing makes its automated detection and early diagnosis of clinical relevance. SCOPUS: ar.j info:eu-repo/semantics/published