title: Screening of Patients with Snoring and Obstructive Sleep Apnoea using Heart Rate Variability Indices.
abstract: OBJECTIVE
  Snoring and obstructive sleep apnea (OSA) are common disorders. Snoring associated with excessive daytime sleepiness is the most prevalent symptoms of OSA. Heart rate variability (HRV) is altered in patients with OSA and the degree of alteration may be linked to the severity of OSA. Alterations in HRV in 24 hour tachograms have recently been used in screening OSA patients. Autonomic components causing HRV can be reliably studied using spectral analysis techniques involving fast Fourier transformation (FFT).
  
  
  METHODS
  Twenty-three subjects, 13 with severe OSA and 10 controls matched for age and body mass index, were selected from patients who had undergone polysomnography (PSG) for snoring at Sultan Qaboos University Hospital, Oman. A 24- hour electrocardiogram (ECG) Holter recording was done at home, starting at 10am. Spectral analysis of ECG from sleep Holter and PSG recordings was analysed using fast Fourier transformation (FFT).
  
  
  RESULTS
  The ECG RR intervals of snorers with OSA were significantly shorter than in snorers without OSA (p<0.01). The low frequency (LF) spectral densities of HRV from polysomnography and Holter were significantly higher in OSA patients than in snorers, (p< 0.0001). The power spectral density of the high frequency bands was similar in the two groups. The overnight ECG Holter accurately identified all 13 snorers with severe OSA.
  
  
  CONCLUSIONS
  The spectral power of the LF band obtained using FFT of sleep HRV from Holter tachograms may be a useful and cost effective test in identifying snorers with severe OSA.
authors.affiliation: Departments of Medicine.
authors.forename: Omar
authors.initials: O
authors.lastname: Al Rawas
authors.forename: Bazdawi
authors.initials: B
authors.lastname: Al-Riyami
authors.forename: Christopher
authors.initials: C
authors.lastname: Goddard
authors.forename: Mohammed O
authors.initials: MO
authors.lastname: Hassan