title: Accuracy of residual apnea-hypopnea index obtained using the continuous positive airway pressure device: application of new version 2.0 scoring rules for respiratory events during sleep.
abstract: OBJECTIVE
  Continuous positive airway pressure (CPAP) devices can estimate apnea-hypopnea index (AHI) using respiratory event detection algorithms. In 2012, rules for manually scoring respiratory events during sleep were updated to version 2.0. The purpose of the present study was to compare residual AHI determined using the Sleepstyle HC608 CPAP device (HC) with those determined by the new manual scoring (NM) rules during CPAP titration in patients with obstructive sleep apnea (OSA).
  
  
  METHODS
  Fifty-seven patients underwent CPAP titration with HC. Correlations were assessed between AHI determined by NM and HC. The AHI, the apnea index (AI), and the hypopnea index (HI) were evaluated separately.
  
  
  RESULTS
  The mean AHI as assessed using diagnostic polysomnography (PSG) was 53.9 ± 22.4. During CPAP titration, respiratory events were effectively suppressed (HC-AHI, 4.2 ± 6.0; NM-AHI, 6.0 ± 5.8). Lower HI and AHI were obtained using HC compared to NM (HC-HI, 2.9 ± 3.6 and NM-HI, 5.2 ± 4.2, p < 0.001; HC-AHI, 4.2 ± 6.0 and NM-AHI, 6.0 ± 5.8, p < 0.001). Additionally, HC reported higher AI compared to NM (HC-AI, 1.3 ± 2.8; NM-AI, 0.9 ± 2.2, p = 0.002). NM-AI (ß = 1.017, p < 0.001), NM-HI (ß = -0.599, p < 0.001), and NM-arousal index (ß = -0.058, p = 0.042) were associated with greater differences between HC-AHI and NM-AHI in multivariate regression analysis.
  
  
  CONCLUSIONS
  Our findings indicate differences in scoring respiratory events between our CPAP device and new version 2.0 manual scoring and suggest that residual AHI values should be carefully interpreted.
authors.affiliation: Sleep Disorders Center, Department of Neurology, Cheonan Hospital, Soonchunhyang University College of Medicine, Soonchunhyang 6 gil 31, Dongnam-gu, Cheonan, Chungnam, 330-721, South Korea.
authors.forename: Doh-Eui
authors.initials: DE
authors.lastname: Kim
authors.affiliation: Department of Preventive Medicine, Cheonan Hospital, Soonchunhyang University College of Medicine, Cheonan, South Korea.
authors.forename: Young
authors.initials: Y
authors.lastname: Hwangbo
authors.affiliation: Sleep Disorders Center, Department of Neurology, Cheonan Hospital, Soonchunhyang University College of Medicine, Soonchunhyang 6 gil 31, Dongnam-gu, Cheonan, Chungnam, 330-721, South Korea.
authors.forename: Ji Hyun
authors.initials: JH
authors.lastname: Bae
authors.affiliation: Sleep Disorders Center, Department of Neurology, Cheonan Hospital, Soonchunhyang University College of Medicine, Soonchunhyang 6 gil 31, Dongnam-gu, Cheonan, Chungnam, 330-721, South Korea. neurofan@schmc.ac.kr.
authors.forename: Kwang Ik
authors.initials: KI
authors.lastname: Yang
mesh_terms: D000328:Adult; D000465:Algorithms; D001143:Arousal; D045422:Continuous Positive Airway Pressure / Q000295:instrumentation*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D017286:Polysomnography / Q000145:classification* / Q000295:instrumentation*; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D020181:Sleep Apnea, Obstructive / Q000145:classification / Q000175:diagnosis* / Q000628:therapy*; D012894:Sleep Stages; D013223:Statistics as Topic
keywords: Continuous positive airway pressure; Obstructive sleep apnea; Residual apnea-hypopnea index; Smart card