Abstract 10389: Cost-Effective Screening for Obstructive Sleep Apnea by Automated ECG Detection of Cyclic Variation of Heart Rate
Background: Obstructive sleep apnea (OSA) is an increased risk for cardiovascular morbidity and mortality. To explore a cost-effective screening method for OSA, we examined the relationship between the severity of OSA and the cyclic variation of heart rate (CVHR), a potential ECG marker of OSA, in a large-scale controlled clinical setting.
Methods: We developed an automated algorithm of autocorrelated wave detection with adaptive threshold (ACAT) for detecting the CVHR. The algorithm was optimized with a training database of 63 sleep studies and the performance was tested with 70 studies in the Physionet Apnea-ECG database. Then, we applied the algorithm to the ECG extracted from all-night polysomnographic recordings in consecutive 887 subjects referred for diagnostic polysomnography.
Results: The number of CVHR per hour (CVHR index) closely correlated (r = 0.82) with the apnea-hypopnea index (AHI) and showed a good performance in identifying the patients with an AHI≥15/h (the AUC of receiver-operating curve 0.913; the sensitivity 83% and specificity 88% with a predetermined cutoff threshold of CVHR index≥15 /h). The classification performance was unaffected by older age (≥65 yr) or cardiac autonomic dysfunction (SDNN<65 ms; the AUC, 0.915 and 0.913, respectively). Although the absolute agreement between the AHI and the CVHR index were modest (the upper and lower limits of agreement, 21 and −19 /h), with periodic leg movement (PLM) being the major cause of the disagreement (P <0.001).
Conclusions: The automated detection of CVHR by the ACAT algorithm provides a powerful marker of moderate-to-severe OSA even in older subjects and in those with cardiac autonomic dysfunction. Although leaving the challenge of the handling of PLM, our observations suggest that the routine ambulatory ECG monitoring may be used as a cost-effective screening method for OSA by incorporating the automated CVHR detection algorithm into Holter scanners.
- Sleep apnea
- Heart rate/Heart rate variability
- Monitoring, physiologic
- Autonomic nervous system
- © 2010 by American Heart Association, Inc.