High night-to-night variability in sleep apnea severity is associated with uncontrolled hypertension

Abstract

Obstructive sleep apnea (OSA) severity can vary markedly from night-to-night. However, the impact of night-to-night variability in OSA severity on key cardiovascular outcomes such as hypertension is unknown. Thus, the primary aim of this study is to determine the effects of night-to-night variability in OSA severity on hypertension likelihood. This study uses in-home monitoring of 15,526 adults with ~180 nights per participant with an under-mattress sleep sensor device, plus ~30 repeat blood pressure measures. OSA severity is defined from the mean estimated apnea–hypopnoea index (AHI) over the ~6-month recording period for each participant. Night-to-night variability in severity is determined from the standard deviation of the estimated AHI across recording nights. Uncontrolled hypertension is defined as mean systolic blood pressure ≥140 mmHg and/or mean diastolic blood pressure ≥90 mmHg. Regression analyses are performed adjusted for age, sex, and body mass index. A total of 12,287 participants (12% female) are included in the analyses. Participants in the highest night-to-night variability quartile within each OSA severity category, have a 50–70% increase in uncontrolled hypertension likelihood versus the lowest variability quartile, independent of OSA severity. This study demonstrates that high night-to-night variability in OSA severity is a predictor of uncontrolled hypertension, independent of OSA severity. These findings have important implications for the identification of which OSA patients are most at risk of cardiovascular harm.

Reconsidering screening thresholds in health assessments for obstructive sleep apnea using operational and safety incident data

“…Given that OSA is associated with major incidents, and in some cases fatalities, in the rail industry 32 , the increased costs associated with screening are likely to be offset by the potential to reduce risk of major incidents in train drivers. Management is also likely to improve the negative associations of OSA sickness absenteeism 33 , poorer quality of life 34 , hypertension 20 and poorer mental health 35 which are all costly to the individual, the workplace and the health system.…”

“…Also of relevance, night-to-night variability in OSA severity can be significant, leading to misclassification of disease severity and misdiagnosis in 20–50% of cases when diagnosis is made using single-night PSG 42 , 43 . Multi-night assessment of OSA severity using low-cost ‘nearable’ sleep measurement devices has been shown to provide more reliable estimates of OSA severity and associated health outcomes compared to traditional PSG 20 , 44 . Using similar approaches for this worker population may facilitate more detailed analysis of the application of the Standard, and any future amendments or iterations, relative to OSA status in train drivers.…”

“…The final variable was OSA risk according to clinical markers. For the purpose of this variable, to be ‘at risk’ by BMI category, workers had to meet BMI threshold (≥37.5 kg/m 2 ), and/or have a BMI > 35 with an indication of current cardiometabolic burden (e.g., type II diabetes 19 , high blood pressure requiring ≥ 1 medications 20 , 21 , systolic blood pressure ≥ 135 & diastolic blood pressure ≥ 85 and/or any heart diseases 22 ). This more conservative criteria for OSA risk was selected given the associations with OSA in existing literature, and availability of clinical marker data in the cohort to demonstrate proof of concept.…”

Reliable Contactless Monitoring of Heart Rate, Breathing Rate and Breathing Disturbance During Sleep in Aging: A Digital Health Technology Evaluation Study

“…They also allow investigation into the night-to-night variation in sleep and vital signs and how this variation associates with health outcomes and daytime function. Such approaches have already shown that night to night variation in sleep apnea associates with uncontrolled hypertension [57] and that night-to-night variation in sleep continuity associated with day-to-day variation in symptoms in people living with Alzheimer's [58].…”

“…The breathings disturbance detection has been performed using Emfit raw ballistography data in literature, but these algorithms are not open source or available directly from the manufacturer and hence not used in our analysis [55, 56]. The availability of these breathing disturbance estimates along with the acceptable agreement of the vital signs measures generated by the contactless technologies demonstrates their immediate potential usefulness in population wide deployment for home monitoring and care [57].…”