title: Pulse transit time in screening sleep disordered breathing in an elderly population: the PROOF-SYNAPSE study.
abstract: OBJECTIVE
  Pulse transit time (PPT) has been introduced as a useful screening tool to diagnose sleep disordered breathing (SDB). Since the prevalence of SDB increases with age, the question is whether PTT could be used to diagnose SDB in the elderly. We assess the effectiveness of PTT for SDB screening in a large healthy elderly population.
  
  
  METHODS
  Community-based sample in home and research clinical settings.
  
  
  METHODS
  N/A.
  
  
  METHODS
  Seven hundred eighty volunteers, free of cardiac and neurologic disease, aged 68.6 ± 1.0 years, underwent ambulatory polygraphy to measure the apnea-hypopnea index (AHI). The presence of SDB was defined as an AHI of 15 or greater. The PTT was continuously monitored during the nocturnal study, and the overall autonomic arousal index (AAI) was calculated.
  
  
  RESULTS
  SDB was diagnosed in 447 (57.3%) subjects. In these subjects, the Bland-Altman plot for AAI revealed an underestimation with a bias of -8.04 ± 16.55 events per hour (mean ± 95% confidence interval). Receiver operating characteristic curves constructed for an AHI of 15 or greater defined an area under the curve of 0.67 and a cutoff point to AAI 32.3 events per hour, giving a sensitivity of 70.5% and a specificity of 54.7%. For prediction of an AHI of at least 30, the area under the curve was equal to 0.74 for a cutoff point of 56.3 events per hour, giving a better specificity (94.7%) but a lower sensitivity (32.2%).
  
  
  CONCLUSIONS
  In a healthy older population, the AAI showed moderate sensitivity for predicting SDB. This data does not allow us to use PTT as a screening tool for the diagnosis of SDB in the elderly.
  
  
  BACKGROUND
  NCT 00759304 and NCT 00766584.
authors.affiliation: INSERM, U1028, CNRS, UMR5292, Centre de Recherche en Neurosciences de Lyon, Intégration centrale de la douleur chez l’Homme, Université Claude Bernard, Lyon, F-69000, France.
authors.forename: Florian
authors.initials: F
authors.lastname: Chouchou
authors.forename: Emilia
authors.initials: E
authors.lastname: Sforza
authors.forename: Sébastien
authors.initials: S
authors.lastname: Celle
authors.forename: Vincent
authors.initials: V
authors.lastname: Pichot
authors.forename: Delphine
authors.initials: D
authors.lastname: Maudoux
authors.forename: Arnauld
authors.initials: A
authors.lastname: Garcin
authors.forename: Jean Claude
authors.initials: JC
authors.lastname: Barthélémy
authors.forename: Frédéric
authors.initials: F
authors.lastname: Roche
mesh_terms: D000368:Aged; D004562:Electrocardiography / Q000379:methods* / Q000706:statistics & numerical data; D005260:Female; D015577:Geriatric Assessment / Q000379:methods / Q000706:statistics & numerical data; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D017286:Polysomnography / Q000379:methods / Q000706:statistics & numerical data; D011237:Predictive Value of Tests; D012372:ROC Curve; D012680:Sensitivity and Specificity; D012891:Sleep Apnea Syndromes / Q000175:diagnosis* / Q000503:physiopathology