title: Differentiating obstructive from central and complex sleep apnea using an automated electrocardiogram-based method.
abstract: OBJECTIVE
  Complex sleep apnea is defined as sleep disordered breathing secondary to simultaneous upper airway obstruction and respiratory control dysfunction. The objective of this study was to assess the utility of an electrocardiogram (ECG)-based cardiopulmonary coupling technique to distinguish obstructive from central or complex sleep apnea.
  
  
  METHODS
  Analysis of archived polysomnographic datasets.
  
  
  METHODS
  A laboratory for computational signal analysis.
  
  
  METHODS
  None.
  
  
  RESULTS
  The PhysioNet Sleep Apnea Database, consisting of 70 polysomnograms including single-lead ECG signals of approximately 8 hours duration, was used to train an ECG-based measure of autonomic and respiratory interactions (cardiopulmonary coupling) to detect periods of apnea and hypopnea, based on the presence of elevated low-frequency coupling (e-LFC). In the PhysioNet BIDMC Congestive Heart Failure Database (ECGs of 15 subjects), a pattern of "narrow spectral band" e-LFC was especially common. The algorithm was then applied to the Sleep Heart Health Study-I dataset, to select the 15 records with the highest amounts of broad and narrow spectral band e-LFC. The latter spectral characteristic seemed to detect not only periods of central apnea, but also obstructive hypopneas with a periodic breathing pattern. Applying the algorithm to 77 sleep laboratory split-night studies showed that the presence of narrow band e-LFC predicted an increased sensitivity to induction of central apneas by positive airway pressure.
  
  
  CONCLUSIONS
  ECG-based spectral analysis allows automated, operator-independent characterization of probable interactions between respiratory dyscontrol and upper airway anatomical obstruction. The clinical utility of spectrographic phenotyping, especially in predicting failure of positive airway pressure therapy, remains to be more thoroughly tested.
authors.affiliation: Division of Pulmonary, Critical Care and Sleep Medicine, Beth Israel Deaconess Medical Center Boston, MA 02215, USA. rthomas1@bidmc.harvard.edu
authors.forename: Robert Joseph
authors.initials: RJ
authors.lastname: Thomas
authors.forename: Joseph E
authors.initials: JE
authors.lastname: Mietus
authors.forename: Chung-Kang
authors.initials: CK
authors.lastname: Peng
authors.forename: Geoffrey
authors.initials: G
authors.lastname: Gilmartin
authors.forename: Robert W
authors.initials: RW
authors.lastname: Daly
authors.forename: Ary L
authors.initials: AL
authors.lastname: Goldberger
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Gottlieb
mesh_terms: D000328:Adult; D000465:Algorithms; D003196:Computer Graphics; D045422:Continuous Positive Airway Pressure; D003626:Data Display; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation*; D004562:Electrocardiography / Q000295:instrumentation*; D005103:Expert Systems; D005260:Female; D005583:Fourier Analysis; D006801:Humans; D008297:Male; D008875:Middle Aged; D017286:Polysomnography / Q000295:instrumentation*; D012016:Reference Values; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D012891:Sleep Apnea Syndromes / Q000175:diagnosis* / Q000628:therapy; D020182:Sleep Apnea, Central / Q000175:diagnosis* / Q000628:therapy; D020181:Sleep Apnea, Obstructive / Q000175:diagnosis* / Q000628:therapy