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BACKGROUND: Respiratory sleep studies are frequently performed to identify sleep disruption resulting from upper airway obstruction. Traditional polysomnographic studies may not detect brief recurrent sleep disruption and thus fail to recognise a significant problem when apnoea, hypopnoea, or arterial desaturation are not present. Arousal from sleep causes a transient blood pressure rise, and each inspiration causes a transient blood pressure fall. This study assesses whether these blood pressure changes are a useful indirect marker of disturbed sleep, obstructed sleep apnoea, and snoring related sleep disturbance. METHODS: Computer algorithms were developed to identify blood pressure falls caused by inspiration and rises related to arousal from 286 sleeping blood pressure samples of a consistent respiratory state drawn from 51 polysomnographic studies. From these samples, normal ranges for the number of arousal related systolic rises and the average size of the inspiratory falls were established. These were then applied prospectively to all night unedited blood pressure recordings from a further 20 subjects. RESULTS: The size of the inspiratory falls in blood pressure progressively increased from normal sleep, through snoring, to frank obstructive sleep apnoea. The 95th centile of normal was 12.5 mm Hg. The number of arousal related blood pressure rises also increased during obstructive sleep apnoea and periods of snoring with associated arousals, compared with normal undisturbed sleep, and all these periods of disturbed sleep included more than 30 such rises per hour. When these blood pressure features were examined in the 20 subjects studied prospectively, the six with a sleep related breathing disorder could all have been identified from their systolic blood pressure profile alone. CONCLUSIONS: The systolic blood pressure profile may be helpful in identifying patients with obstructive sleep apnoea, snoring with arousals, or other sleep disruption syndromes.


Journal article



Publication Date





1242 - 1247


Adult, Aged, Algorithms, Blood Pressure, Diagnosis, Computer-Assisted, Female, Humans, Male, Middle Aged, Prospective Studies, Respiration, Sleep Apnea Syndromes, Software