O040 Assessment of Heart Rate Variability During Respiratory Events and Arousals Using Symbolic Dynamics

Abstract

Abstract Introduction Beat-to-beat heart rate dynamics vary during obstructive respiratory events and in both respiratory and spontaneous arousals. However, conventional quantifications of heart rate variability (HRV) require segments of data substantially longer than the typical respiratory event or arousal. Subsequently, previous studies investigating dynamics in these significantly shorter segments have utilised simple quantifications such as peak heart rate. This study aimed to more-richly characterise HRV during obstructive respiratory events and arousals using symbolic dynamics. Methods One hundred individuals with suspected obstructive sleep apnoea (55 male, 57.1±12.9 years) were studied with diagnostic polysomnography, including electrocardiography. R-wave intervals were calculated and extracted during respiratory events terminating with/without arousals and during spontaneous and respiratory arousals. The symbolic dynamics tool “heart rate fragmentation” was applied to quantify HRV during the events, whereby the percentage of inflection points (PIP), defined as beat-to-beat transitions from heart-rate acceleration to heart-rate deceleration, were calculated. Statistical analysis was conducted with the Wilcoxon rank sum test. Results PIP was higher during respiratory events terminated with arousal compared with those without arousal (52.9±6.4% vs. 48.5±6.7%, P<0.05). PIP was also higher during spontaneous arousals than during respiratory arousals (51.3±6.1% vs. 45.8±6.7%, P<0.05). Discussion Previous mechanistic experiments have associated increased PIP with greater parasympathetic activity. Thus, our preliminary results suggest greater parasympathetic activity during respiratory events terminated by arousal than those without; and during spontaneous arousals compared with respiratory arousals. Further work is required to understand the pathophysiology underlying this and other similar metrics, potentially leading to novel obstructive sleep apnoea-related cardiorespiratory pathology biomarkers.