Sleep apnea-hypopnea quantification by cardiovascular data analysis

Cardiac Autonomic Dysfunction and Incidence of de novo Atrial Fibrillation: Heart Rate Variability vs. Heart Rate Complexity

BACKGROUND

The REACT DX registry evaluates standard therapies to episodes of long-lasting atrial tachyarrhythmias and assesses the quality of sensing and stability of the lead and the implantable cardioverter-defibrillator (ICD) (BIOTRONIK Lumax VR-T DX and successors) over at least a 1-year follow-up period.

OBJECTIVE

To study the association between the risk of de novo device-detected atrial fibrillation (AF), the autonomic perturbations before the onset of paroxysmal AF and a 7-days heart rate variability (7dHRV) 1 month after ICD implantation.

METHODS

The registry consists of 234 patients implanted with an ICD, including 10 with de novo long-lasting atrial tachyarrhythmias with no prior history of AF. The patients were matched via the propensity-score methodology as well as for properties directly influencing the ECGs recorded using GE CardioMem CM 3000. Heart rate variability (HRV) analysis was performed using standard parameters from time- and frequency-domains, and from non-linear dynamics.

RESULTS

No linear HRV was associated with an increased risk of AF (p = n.s.). The only significant approach was derived from symbolic dynamics with the parameter "forbidden words" which distinguished both groups on all 7 days of measurements (p < 0.05), thereby quantifying the heart rate complexity (HRC) as drastically lower in the de novo AF group.

CONCLUSION

Cardiac autonomic dysfunction denoted by low HRC may be associated with higher AF incidence. For patients with mild to moderate heart failure, standard HRV parameters are not appropriate to quantify cardiac autonomic perturbations before the onset of AF. Further studies are needed to determine the individual risk for AF that would enable interventions to restore autonomic balance in the general population.

Risk detection in patients with obstructive sleep apnea syndrome based on cardiovascular time series analysis

Obstructive sleep apnea represents the most common form of sleep-disordered breathing and has a high prevalence in patients with cardiovascular disease. Disturbed sleep is a potential risk factor for cardiovascular disorders such as arterial hypertension, cardiac ischemia, sudden cardiac death, and stroke. In this study we investigated polysomnographic records and analyzed the ECG, plethysmogram, respiration and SpO2 time series during wakefulness (WK), NREM, and REM sleep stages applying variability and coupling analyses methods. We enrolled 55 patients with obstructive sleep apnea syndrome (OSAS) and 29 healthy control subjects (CON: 45.9±14.9 years, 21 male) in this study. OSAS patients were subdivided into a low- and high-risk group (LR: 50.8±14.1 years, n=29, 21 male; HR: 57.2±13.4 years, n=26, 19 male) based on the Apnea-Hypopnea Index (AHI) (CON: 0-5 AHI, LR: 5-15 AHI, HR: >15 AHI). We could demonstrate the presence of an altered autonomic function in OSAS patients, differing from healthy controls. This altered autonomic function was mainly based on heart rate-, respiratory-, SpO2- and plethysmogram variability and their couplings. The discriminant analysis showed that the optimal set consisting of two autonomic indices revealed a high classification power (ACC=86.7%, AUC=90.3%, SENS=89.5% and SPEC=84.6%) when comparing low-risk and high-risk OSAS patients during WK. These results were slightly improved when analyzing REM sleep stages. Based on these results it seems to be possible to perform optimal risk stratification for OSAS patients based on autonomic indices. Based on our findings it is possible to differentiate between high-risk OSAS patient and low-risk OSAS patient at an early stage and in a promising manner allowing to set up therapy strategies for those patients in an early stage.

Obstructive sleep apnea increases systolic and diastolic blood pressure variability in hypertensive patients

OBJECTIVE

Obstructive sleep apnea (OSA) has been identified as the most common secondary contributing factor for the development and worsening of hypertension. However, the underlying relationships between blood pressure variability (BPV) and OSA are still not very clear. Therefore, we investigated the influences of OSA on BPV in hypertensive patients and explored the potential pathophysiologic mechanisms.

PARTICIPANTS AND METHODS

Ambulatory blood pressure (BP) monitoring was carried out and polysomnography was performed to detect sleep apnea. A total of 86 hypertensive individuals were divided into patients without OSA (n=43) and patients with severe OSA (n=43). Systolic and diastolic BPV were obtained by calculating the SD, coefficient of variation, and average real variability during day-time, night-time, and over 24 h. The relationship between OSA and BPV was assessed after adjustment for potential confounding variables (age, sex, BMI, neck circumference, heart rate, and snoring history).

RESULTS

Compared with participants without OSA, nocturnal systolic BPV and 24-h systolic BP average real variability from OSA participants were obviously increased (P<0.05), but there were no statistically significant differences in day-time and 24-h systolic BP SD and coefficient of variation (P>0.05). Compared with participants without OSA, 24-h diastolic BPV and day-time diastolic BP SD from OSA participants were markedly increased (P<0.05), but nocturnal indices showed no significant differences between the two groups.

CONCLUSION

OSA mainly increases night-time systolic and 24-h diastolic BPV in hypertensive patients. This may provide a plausible explanation for OSA remaining a major risk determinant for cardiovascular diseases.

P4 medicine approach to obstructive sleep apnoea

P4 medicine is an evolving approach to personalized medicine. The four Ps offer a means to: Predict who will develop disease and co-morbidities; Prevent rather than react to disease; Personalize diagnosis and treatment; have patients Participate in their own care. P4 medicine is very applicable to obstructive sleep apnoea (OSA) because each OSA patient has a different pathway to disease and its consequences. OSA has both structural and physiological mechanisms with different clinical subgroups, different molecular profiles and different consequences. This may explain why there are different responses to alternative therapies, such as intraoral devices and hypoglossal nerve stimulation therapy. Currently, technology facilitates patients to participate in their own care from screening for OSA (snoring and apnoea apps) to monitoring response to therapy (sleep monitoring, blood pressure, oxygen saturation and heart rate) as well as monitoring their own continuous positive airway pressure (CPAP) compliance. We present a conceptual framework that provides the basis for a new, P4 medicine approach to OSA and should be considered more in depth: predict and prevent those at high risk for OSA and consequences, personalize the diagnosis and treatment of OSA and build in patient participation to manage OSA.