Obstructive sleep apnea heterogeneity and autonomic function: a role for heart rate variability in therapy selection and efficacy monitoring

Obstructive sleep apnea is a highly prevalent sleep-related breathing disorder, resulting in a disturbed breathing pattern, changes in blood gases, abnormal autonomic regulation, metabolic fluctuation, poor neurocognitive performance, and increased cardiovascular risk. With broad inter-individual differences recognised in risk factors, clinical symptoms, gene expression, physiological characteristics, and health outcomes, various obstructive sleep apnea subtypes have been identified. Therapeutic efficacy and its impact on outcomes, particularly for cardiovascular consequences, may also vary depending on these features in obstructive sleep apnea. A number of interventions such as positive airway pressure therapies, oral appliance, surgical treatment, and pharmaceutical options are available in clinical practice. Selecting an effective obstructive sleep apnea treatment and therapy is a challenging medical decision due to obstructive sleep apnea heterogeneity and numerous treatment modalities. Thus, an objective marker for clinical evaluation is warranted to estimate the treatment response in patients with obstructive sleep apnea. Currently, while the Apnea-Hypopnea Index is used for severity assessment of obstructive sleep apnea and still considered a major guide to diagnosis and managements of obstructive sleep apnea, the Apnea-Hypopnea Index is not a robust marker of symptoms, function, or outcome improvement. Abnormal cardiac autonomic modulation can provide additional insight to better understand obstructive sleep apnea phenotyping. Heart rate variability is a reliable neurocardiac tool to assess altered autonomic function and can also provide cardiovascular information in obstructive sleep apnea. Beyond the Apnea-Hypopnea Index, this review aims to discuss the role of heart rate variability as an indicator and predictor of therapeutic efficacy to different modalities in order to optimise tailored treatment for obstructive sleep apnea.

Magnetocardiography at rest predicts cardiac death in patients with acute chest pain

Introduction

Sudden cardiac arrest is a major cause of morbidity and mortality worldwide and remains a major public health problem for which better non-invasive prediction tools are needed. Primary preventive therapies, such as implantable cardioverter defibrillators, are not personalized and not predictive. Most of these devices do not deliver life-saving therapy during their lifetime. The individual relationship between fatal arrhythmias and cardiac function abnormalities in predicting cardiac death risk has rarely been explored.

Methods

We retrospectively analyzed the measurements at rest for 191 patients with acute chest pain (ACP) magnetocardiographically. Our recently introduced analyses are able to detect inhomogeneities of the depolarization and repolarization. Moreover, electrically silent phenomena-intracellular ionic currents as well as vortex currents-can be measured and quantified. All included ACP patients were recruited in 2009 at Yonsei University Hospital and were followed up until 2022.

Results

During half of the follow-up period (6.5 years), 11 patients died. Out of all the included nine clinical, eight magnetocardiographical, and nine newly introduced magnetoionographical parameters we tested in this study, three parameters revealed themselves to be outstanding at predicting death: heart rate-corrected QT (QTc) prolongation, depression of repolarization current IKr + IKs, and serum creatinine (all significant in Cox regression, p < 0.05). They clearly predicted cardiac death over the 6.5 years duration (sensitivity 90.9%, specificity 85.6%, negative predictive accuracy 99.4%). Cardiac death risk was more than ninefold higher in patients with low repolarization reserve and QTc prolongation in comparison with the remaining patients with ACP (p < 0.001). The non-parametric Kaplan-Meier statistics estimated significantly lower survival functions from their lifetime data (p < 0.001).

Discussion

To the best of our knowledge, these are the first data linking magnetocardiographical and magnetoionographical parameters and subsequent significant fatal events in people, suggesting structural and functional components to clinical life-threatening ventricular arrhythmogenesis. The findings support investigation of new prevention strategies and herald those new non-invasive techniques as complementary risk stratification tools.

Cardiac magnetic field map topology quantified by Kullback-Leibler entropy identifies patients with clinically suspected myocarditis

Background

Myocarditis is a condition that can have severe adverse outcomes and lead to sudden cardiac death if remaining undetected. This study tested the capability of cardiac magnetic field mapping to detect patients with clinically suspected myocarditis. This could open up the way for rapid, non-invasive, and cost-effective screening of suspected cases before a gold standard assessment via endomyocardial biopsy.

Methods

Historical cardiac magnetic field maps (n = 97) and data from a state-of-the-art magnetocardiography device (n = 30) were analyzed using the Kullback-Leibler entropy (KLE) for dimensionality reduction and topological quantification. Linear discriminant analysis was used to discern between patients with ongoing myocarditis and healthy controls.

Results

The STT segment of a magnetocardiogram, i.e., the section between the end of the S wave and the end of the T wave, was best suited to discern both groups. Using a 250-ms excerpt from the onset of the STT segment gave a reliable classification between the myocarditis and control group for both historic data (sensitivity: 0.83, specificity: 0.85, accuracy: 0.84) and recent data (sensitivity: 0.69, specificity: 0.88, accuracy: 0.80) using the KLE to quantify the topology of the cardiac magnetic field map.

Conclusion

The implementation based on KLE can reliably distinguish between clinically suspected myocarditis patients and healthy controls. We implemented an automatized feature selection based on LDA to replace the observer-dependent manual thresholding in previous studies.

Pathological Heart Rate Regulation in Apparently Healthy Individuals

Cardiovascular diseases are the leading cause of morbidity and mortality in adults worldwide. There is one common pathophysiological aspect present in all cardiovascular diseases-dysfunctional heart rhythm regulation. Taking this aspect into consideration for cardiovascular risk predictions opens important research perspectives, allowing for the development of preventive treatment techniques. The aim of this study was to find out whether certain pathologically appearing signs in the heart rate variability (HRV) of an apparently healthy person, even with high HRV, can be defined as biomarkers for a disturbed cardiac regulation and whether this can be treated preventively by a drug-free method. This multi-phase study included 218 healthy subjects of either sex, who consecutively visited the physician at Gesundheit clinic because of arterial hypertension, depression, headache, psycho-emotional stress, extreme weakness, disturbed night sleep, heart palpitations, or chest pain. In study phase A, baseline measurement to identify individuals with cardiovascular risks was done. Therefore, standard HRV, as well as the new cardiorhythmogram (CRG) method, were applied to all subjects. The new CRG analysis used here is based on the recently introduced LF drops and HF counter-regulation. Regarding the mechanisms of why these appear in a steady-state cardiorhythmmogram, they represent non-linear event-based dynamical HRV biomarkers. The next phase of the study, phase B, tested whether the pathologically appearing signs identified via CRG in phase A could be clinically influenced by drug-free treatment. In order to validate the new CRG method, it was supported by non-linear HRV analysis in both phase A and in phase B. Out of 218 subjects, the pathologically appearing signs could be detected in 130 cases (60%), p < 0.01, by the new CRG method, and by the standard HRV analysis in 40 cases (18%), p < 0.05. Thus, the CRG method was able to detect 42% more cases with pathologically appearing cardiac regulation. In addition, the comparative CRG analysis before and after treatment showed that the pathologically appearing signs could be clinically influenced without the use of medication. After treatment, the risk group decreased eight-fold-from 130 people to 16 (p < 0.01). Therefore, progression of the detected pathological signs to structural cardiac pathology or arrhythmia could be prevented in most of the cases. However, in the remaining risk group of 16 apparently healthy subjects, 8 people died due to all-cause mortality. In contrast, no other subject in this study has died so far. The non-linear parameter which is able to quantify the changes in CRGs before versus after treatment is FWRENYI4 (symbolic dynamic feature); it decreased from 2.85 to 2.53 (p < 0.001). In summary, signs of pathological cardiac regulation can be identified by the CRG analysis of apparently healthy subjects in the early stages of development of cardiac pathology. Thus, our method offers a sensitive biomarker for cardiovascular risks. The latter can be influenced by non-drug treatments (acupuncture) to stop the progression into structural cardiac pathologies or arrhythmias in most but not all of the patients. Therefore, this could be a real and easy-to-use supplemental method, contributing to primary prevention in cardiology.

Intraoperative Beat-to-Beat Pulse Transit Time (PTT) Monitoring via Non-Invasive Piezoelectric/Piezocapacitive Peripheral Sensors Can Predict Changes in Invasively Acquired Blood Pressure in High-Risk Surgical Patients

BACKGROUND

Non-invasive tracking of beat-to-beat pulse transit time (PTT) via piezoelectric/piezocapacitive sensors (PES/PCS) may expand perioperative hemodynamic monitoring. This study evaluated the ability for PTT via PES/PCS to correlate with systolic, diastolic, and mean invasive blood pressure (SBP_IBP, DBP_IBP, and MAP_IBP, respectively) and to detect SBP_IBP fluctuations.

METHODS

PES/PCS and IBP measurements were performed in 20 patients undergoing abdominal, urological, and cardiac surgery. A Pearson's correlation analysis (r) between 1/PTT and IBP was performed. The predictive ability of 1/PTT with changes in SBP_IBP was determined by area under the curve (reported as AUC, sensitivity, specificity).

RESULTS

Significant correlations between 1/PTT and SBP_IBP were found for PES (r = 0.64) and PCS (r = 0.55) (p < 0.01), as well as MAP_IBP/DBP_IBP for PES (r = 0.6/0.55) and PCS (r = 0.5/0.45) (p < 0.05). A 7% decrease in 1/PTT_PES predicted a 30% SBP_IBP decrease (0.82, 0.76, 0.76), while a 5.6% increase predicted a 30% SBP_IBP increase (0.75, 0.7, 0.68). A 6.6% decrease in 1/PTT_PCS detected a 30% SBP_IBP decrease (0.81, 0.72, 0.8), while a 4.8% 1/PTT_PCS increase detected a 30% SBP_IBP increase (0.73, 0.64, 0.68).

CONCLUSIONS

Non-invasive beat-to-beat PTT via PES/PCS demonstrated significant correlations with IBP and detected significant changes in SBP_IBP. Thus, PES/PCS as a novel sensor technology may augment intraoperative hemodynamic monitoring during major surgery.

REACT DX registry: Real world REACTion to atrial high rate episodes detected in implantable cardioverter-defibrillator recipients with a DX lead

BACKGROUND

Atrial fibrillation (AF) is associated with significant morbidity and is predicted by atrial high rate events. The early detection of AF is paramount to timely interventions to reduce the morbidity of AF. The DX ICD system combined with Home Monitoring® allows for continuous atrial rhythm monitoring without the need for a dedicated atrial lead.

OBJECTIVE

To establish the reaction to and timing of reactions to the detection of atrial high rate episodes (AHRE).

METHODS

A prospective cohort of DX ICD systems was followed up and the response to AHREs was collected and evaluated.

RESULTS

A total of 234 patients were enrolled; an AHRE ⩾ 6 min was detected in 13.7% of patients (n= 32) within a mean follow-up duration of 16 months. A high rate of oral anticoagulation (OAC) prescription was seen with the detection of AHREs in patients with a not-low risk CHA2DS2-VASc score. There was a delay in this prescription highlighting the potential to improve the timeliness of patient care in this group of patients.

CONCLUSIONS

The DX ICD system provides rapid and ongoing atrial rhythm monitoring such that physicians are rapidly aware of AHRE without the need for a dedicated atrial lead, but local protocols are needed to improve the response time of anti-coagulation prescription.

Automatic Sleep Staging in Children with Sleep Apnea using Photoplethysmography and Convolutional Neural Networks

Sleep staging is of paramount importance in children with suspicion of pediatric obstructive sleep apnea (OSA). Complexity, cost, and intrusiveness of overnight polysomnography (PSG), the gold standard, have led to the search for alternative tests. In this sense, the photoplethysmography signal (PPG) carries useful information about the autonomous nervous activity associated to sleep stages and can be easily acquired in pediatric sleep apnea home tests with a pulse oximeter. In this study, we use the PPG signal along with convolutional neural networks (CNN), a deep-learning technique, for the automatic identification of the three main levels of sleep: wake (W), rapid eye movement (REM), and non-REM sleep. A database of 366 PPG recordings from pediatric OSA patients is involved in the study. A CNN architecture was trained using 30-s epochs from the PPG signal for three-stage sleep classification. This model showed a promising diagnostic performance in an independent test set, with 78.2% accuracy and 0.57 Cohen's kappa for W/NREM/REM classification. Furthermore, the percentage of time in wake stage obtained for each subject showed no statistically significant differences with the manually scored from PSG. These results were superior to the only state-of-the-art study focused on the analysis of the PPG signal in the automated detection of sleep stages in children suffering from OSA. This suggests that CNN can be used along with PPG recordings for sleep stages scoring in pediatric home sleep apnea tests.

The Different Facets of Heart Rate Variability in Obstructive Sleep Apnea

Obstructive sleep apnea (OSA), a heterogeneous and multifactorial sleep related breathing disorder with high prevalence, is a recognized risk factor for cardiovascular morbidity and mortality. Autonomic dysfunction leads to adverse cardiovascular outcomes in diverse pathways. Heart rate is a complex physiological process involving neurovisceral networks and relative regulatory mechanisms such as thermoregulation, renin-angiotensin-aldosterone mechanisms, and metabolic mechanisms. Heart rate variability (HRV) is considered as a reliable and non-invasive measure of autonomic modulation response and adaptation to endogenous and exogenous stimuli. HRV measures may add a new dimension to help understand the interplay between cardiac and nervous system involvement in OSA. The aim of this review is to introduce the various applications of HRV in different aspects of OSA to examine the impaired neuro-cardiac modulation. More specifically, the topics covered include: HRV time windows, sleep staging, arousal, sleepiness, hypoxia, mental illness, and mortality and morbidity. All of these aspects show pathways in the clinical implementation of HRV to screen, diagnose, classify, and predict patients as a reasonable and more convenient alternative to current measures.

Heart rate variability during wakefulness as a marker of obstructive sleep apnea severity

STUDY OBJECTIVES

Patients with obstructive sleep apnea (OSA) exhibit heterogeneous heart rate variability (HRV) during wakefulness and sleep. We investigated the influence of OSA severity on HRV parameters during wakefulness in a large international clinical sample.

METHODS

1247 subjects (426 without OSA and 821 patients with OSA) were enrolled from the Sleep Apnea Global Interdisciplinary Consortium. HRV parameters were calculated during a 5-minute wakefulness period with spontaneous breathing prior to the sleep study, using time-domain, frequency-domain and nonlinear methods. Differences in HRV were evaluated among groups using analysis of covariance, controlling for relevant covariates.

RESULTS

Patients with OSA showed significantly lower time-domain variations and less complexity of heartbeats compared to individuals without OSA. Those with severe OSA had remarkably reduced HRV compared to all other groups. Compared to non-OSA patients, those with severe OSA had lower HRV based on SDNN (adjusted mean: 37.4 vs. 46.2 ms; p < 0.0001), RMSSD (21.5 vs. 27.9 ms; p < 0.0001), ShanEn (1.83 vs. 2.01; p < 0.0001), and Forbword (36.7 vs. 33.0; p = 0.0001). While no differences were found in frequency-domain measures overall, among obese patients there was a shift to sympathetic dominance in severe OSA, with a higher LF/HF ratio compared to obese non-OSA patients (4.2 vs. 2.7; p = 0.009).

CONCLUSIONS

Time-domain and nonlinear HRV measures during wakefulness are associated with OSA severity, with severe patients having remarkably reduced and less complex HRV. Frequency-domain measures show a shift to sympathetic dominance only in obese OSA patients. Thus, HRV during wakefulness could provide additional information about cardiovascular physiology in OSA patients.

CLINICAL TRIAL INFORMATION

A Prospective Observational Cohort to Study the Genetics of Obstructive Sleep Apnea and Associated Co-Morbidities (German Clinical Trials Register - DKRS, DRKS00003966) https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00003966.

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.

Instantaneous Cardiac Baroreflex Sensitivity: xBRS Method Quantifies Heart Rate Blood Pressure Variability Ratio at Rest and During Slow Breathing

Spontaneous baroreflex sensitivity (BRS) is a widely used tool for the quantification of the cardiovascular regulation. Numerous groups use the xBRS method, which calculates the cross-correlation between the systolic beat-to-beat blood pressure and the R-R interval (resampled at 1 Hz) in a 10 s sliding window, with 0-5 s delays for the interval. The delay with the highest correlation is selected and, if significant, the quotient of the standard deviations of the R-R intervals and the systolic blood pressures is recorded as the corresponding xBRS value. In this paper we test the hypothesis that the xBRS method quantifies the causal interactions of spontaneous BRS from non-invasive measurements at rest. We use the term spontaneous BRS in the sense of the sensitivity curve is calculated from non-interventional, i.e., spontaneous, baroreceptor activity. This study includes retrospective analysis of 1828 measurements containing ECG as well as continues blood pressure under resting conditions. Our results show a high correlation between the heart rate - systolic blood pressure variability (HRV/BPV) quotient and the xBRS (r = 0.94, p < 0.001). For a deeper understanding we conducted two surrogate analyses by substituting the systolic blood pressure by its reversed time series. These showed that the xBRS method was not able to quantify causal relationships between the two signals. It was not possible to distinguish between random and baroreflex controlled sequences. It appears xBRS rather determines the HRV/BPV quotient. We conclude that the xBRS method has a potentially large bias in characterizing the capacity of the arterial baroreflex under resting conditions. During slow breathing, estimates for xBRS are significantly increased, which clearly shows that measurements at rest only involve limited baroreflex activity, but does neither challenge, nor show the full range of the arterial baroreflex regulatory capacity. We show that xBRS is exclusively dominated by the heart rate to systolic blood pressure ratio (r = 0.965, p < 0.001). Further investigations should focus on additional autonomous testing procedures such as slow breathing or orthostatic testing to provide a basis for a non-invasive evaluation of baroreflex sensitivity.

Prediction of Sudden Cardiac Death Risk with a Support Vector Machine Based on Heart Rate Variability and Heartprint Indices

Most methods for sudden cardiac death (SCD) prediction require long-term (24 h) electrocardiogram recordings to measure heart rate variability (HRV) indices or premature ventricular complex indices (with the heartprint method). This work aimed to identify the best combinations of HRV and heartprint indices for predicting SCD based on short-term recordings (1000 heartbeats) through a support vector machine (SVM). Eleven HRV indices and five heartprint indices were measured in 135 pairs of recordings (one before an SCD episode and another without SCD as control). SVMs (defined with a radial basis function kernel with hyperparameter optimization) were trained with this dataset to identify the 13 best combinations of indices systematically. Through 10-fold cross-validation, the best area under the curve (AUC) value as a function of γ (gamma) and cost was identified. The predictive value of the identified combinations had AUCs between 0.80 and 0.86 and accuracies between 80 and 86%. Further SVM performance tests on a different dataset of 68 recordings (33 before SCD and 35 as control) showed AUC = 0.68 and accuracy = 67% for the best combination. The developed SVM may be useful for preventing imminent SCD through early warning based on electrocardiogram (ECG) or heart rate monitoring.

Transportation noise impairs cardiovascular function without altering sleep: The importance of autonomic arousals

AIMS

Chronic exposure to nocturnal transportation noise has been linked to cardiovascular disorders with sleep impairment as the main mediator. Here we examined whether nocturnal transportation noise affects the main stress pathways, and whether it relates to changes in the macro and micro structure of sleep.

METHODS AND RESULTS

Twenty-six young healthy participants (12 women, 24.6 ± 0.7 years, mean ± SE) spent five consecutive 24-h days and one last morning in the laboratory. The first (baseline) and last (recovery) nights comprised a quiet ambient scenario. In-between, four different noise scenarios (low/medium/high intermittent road or rail scenarios with an identical equivalent continuous sound level of 45 dB) were randomly presented during the 8-h nights. Participants felt more annoyed from the transportation noise scenarios compared to the quiet ambient scenario played back during the baseline and recovery nights (F_5,117 = 10.2, p < 0.001). Nocturnal transportation noise did not significantly impact polysomnographically assessed sleep macrostructure, blood pressure, nocturnal catecholamine levels and morning cytokine levels. Evening cortisol levels increased after sleeping with highly intermittent road noise compared to baseline (p = 0.002, noise effect: F_4,83 = 4.0, p = 0.005), a result related to increased cumulative duration of autonomic arousals during the noise nights (F_5,106 = 3.4, p < 0.001; correlation: r_pearson = 0.64, p = 0.006).

CONCLUSION

Under controlled laboratory conditions, highly intermittent nocturnal road noise exposure at 45 dB increased the cumulative duration of autonomic arousals during sleep and next-day evening cortisol levels. Our results indicate that, without impairing sleep macrostructure, nocturnal transportation noise of 45 dB is a physiological stressor that affects the hypothalamic-pituitary-adrenal axis during the following day in healthy young good sleepers.

Symbolic analysis of heart rate fluctuations identifies cardiac autonomic modifications during LPS-induced endotoxemia

The present study aimed to compare linear and symbolic dynamics (SD) indices for detecting the autonomic cardiac changes produced by endotoxemia in freely-moving rats. In this context, we analyzed ECG-derived R-R time series in freely moving Dark Agouti rats, which received lipopolysaccharide (LPS, n = 9), or vehicle (V, n = 7). Five minutes R-R time series were assessed every hour up to +12 h and + 24 h post-LPS injection. We found that SD indices showed significant differences at +7 h between V vs. LPS groups and at +9 h between basal levels of LPS (-3 h) and post-LPS injection (pre-LPS vs. post-LPS). In general, SD seems more appropriate than linear indices to evaluate the autonomic changes of endotoxemic rats. Overall, the symbolic parameters detected decreased R-R variability and complexity, which indicate a modification of the autonomic regulation during LPS-induced endotoxemia. This modification is probably related to a reduced activity of the cholinergic anti-inflammatory pathway at the long term.

Screening for Obstructive Sleep Apnea in Commercial Drivers Using EKG-Derived Respiratory Power Index

STUDY OBJECTIVES

Obstructive sleep apnea (OSA) is common in commercial motor vehicle operators (CMVOs); however, polysomnography (PSG), the gold-standard diagnostic test, is expensive and inconvenient for screening. OSA is associated with changes in heart rate and voltage on electrocardiography (EKG). We evaluated the utility of EKG parameters in identifying CMVOs at greater risk for sleepiness-related crashes (apnea-hypopnea index [AHI] ≥ 30 events/h).

METHODS

In this prospective study of CMVOs, we performed EKGs with concurrent PSG, and calculated the respiratory power index (RPI) on EKG, a surrogate for AHI calculated from PSG. We evaluated the utility of two-stage predictive models using simple clinical measures (age, body mass index [BMI], neck circumference, Epworth Sleepiness Scale score, and the Multi-Variable Apnea Prediction [MVAP] score) in the first stage, followed by RPI in a subset as the second-stage. We assessed area under the receiver operating characteristic curve (AUC), sensitivity, and negative posttest probability (NPTP) for this two-stage approach and for RPI alone.

RESULTS

The best-performing model used the MVAP, which combines BMI, age, and sex with three OSA symptoms, in the first stage, followed by RPI in the second. The model yielded an estimated (95% confidence interval) AUC of 0.883 (0.767-0.924), sensitivity of 0.917 (0.706-0.962), and NPTP of 0.034 (0.015-0.133). Predictive characteristics were similar using a model with only BMI as the first-stage screen.

CONCLUSIONS

A two-stage model that combines BMI or the MVAP score in the first stage, with EKG in the second, had robust discriminatory power to identify severe OSA in CMVOs.

Angiotensin-(1-7) Receptor Mas in Hemodynamic and Thermoregulatory Dysfunction After High-Level Spinal Cord Injury in Mice: A Pilot Study

Spinal cord injury (SCI) above mid-thoracic levels leads to autonomic dysfunction affecting both the cardiovascular system and thermoregulation. The renin-angiotensin system (RAS) which is a potent regulator of blood pressure, including its novel beneficial arm with the receptor Mas could be an interesting target in post-SCI hemodynamics. To test the hypothesis that hemodynamics, activity and diurnal patterns of those are more affected in the Mas deficient mice post-SCI we used a mouse model of SCI with complete transection of spinal cord at thoracic level 4 (T4-Tx) and performed telemetric monitoring of blood pressure (BP) and heart rate (HR). Our data revealed that hypothermia deteriorated physiological BP and HR control. Preserving normothermia by keeping mice at 30°C prevented severe hypotension and bradycardia post-SCI. Moreover, it facilitated rapid return of diurnal regulation of BP, HR and activity in wild type (WT) mice. In contrast, although Mas deficient mice had comparable reacquisition of diurnal HR rhythm, they showed delayed recovery of diurnal rhythmicity in BP and significantly lower nocturnal activity. Exposing mice with T4-Tx (kept in temperature-controlled cages) to 23°C room temperature for one hour at different time-points post-SCI, demonstrated their inability to maintain core body temperature, Mas deficient mice being significantly more impaired than WT littermates. We conclude that Mas deficient mice were more resistant to acute hypotension, delayed nocturnal recovery, lower activity and more severely impaired thermoregulation. The ambient temperature had significant effect on hemodynamics and, thus it should be taken into account when assessing cardiovascular parameters post-SCI in mice.

Is dynamic desaturation better than a static index to quantify the mortality risk in heart failure patients with Cheyne-Stokes respiration?

Cheyne-Stokes respiration (CSR) is a periodic, highly dynamic, respiratory pattern and a known comorbidity in congestive heart failure (CHF) patients. It is generally seen as an indicator for a negative prognosis, even if no distinction in degree is known or understood. This paper aims to improve on existing attempts by creating a quantification of the behavior of the dynamic desaturation process of oxygen in the blood. We performed this work on a cohort of 11 subjects with CHF, reduced left ventricular ejection fraction, and CSR. The dynamic desaturation process was evaluated according to changes to peripheral capillary oxygenation S p O 2 resulting from highly nonlinear relationships in the ventilatory system perturbed by periodic breathing. Hypoxaemic burden expressed as a static index T 90 was compared to a novel relative desaturation index R D I , developed in this paper. While T 90 represents a single value calculated using a static cut-off value of 90 % S p O 2 , the R D I is more sensitive to dynamic influences as it uses the specific maximum change in saturation for each CSR episode. The threshold of T 90 = 22 min per night as suggested by Oldenburg et al. could not be confirmed to predict survival, but all central apneas resulting in a relative desaturation of S p O 2 above a cut-off value of 8 % were a 100 % positive predictor of mortality. The R D I proved sufficiently stable in intraindividual measurements across CSR epochs. Across the cohort, it showed a bimodal distribution for the deceased group, indicative of a possible aetiological difference. Hence, it is our conclusion that a dynamic approach to analyse desaturation of oxygen during Cheyne-Stokes respiration is to be strongly favoured over a static approach to analysis.

Forecasting of Life Threatening Arrhythmias Using the Compression Entropy of Heart Rate

Objectives: Ventricular tachycardia (VT) provoking sudden cardiac death (SCD) are a major cause of mortality in the developed countries. The most efficient therapy for SCD prevention are implantable cardioverter defibrillators (ICD). In this study heart rate variability (HRV) measures were analyzed for short-term forecasting of VT in order to improve VT sensing and to enable a patient warning of forthcoming shocks.

Methods: The last 1000 normal beat-to-beat intervals before 50 VT episodes stored by the ICD were analyzed and compared to individually acquired control time series (CON). HRV analysis was performed with standard parameters of time and frequency domain as suggested by the HRV Task Force and furthermore with a newly developed and optimized nonlinear parameter that assesses the compression entropy of heart rate (Hc).

Results: Except of meanNN (p = 0.02) we found no significant differences in standard HRV parameters. In contrast, Hc revealed highly significant (p = 0.007) alterations in VT compared with CON suggesting a decreased complexity before the onset of VT.

Conclusion: Compression entropy might be a suitable parameter for short-term forecasting of life-threatening tachycardia in ICD.

Investigation of an Automatic Sleep Stage Classification by Means of Multiscorer Hypnogram

Objectives: Scoring sleep visually based on polysomnography is an important but time-consuming element of sleep medicine. Whereas computer software assists human experts in the assignment of sleep stages to polysomnogram epochs, their performance is usually insufficient. This study evaluates the possibility to fully automatize sleep staging considering the reliability of the sleep stages available from human expert sleep scorers.

Methods: We obtain features from EEG, ECG and respiratory signals of polysomnograms from ten healthy subjects. Using the sleep stages provided by three human experts, we evaluate the performance of linear discriminant analysis on the entire polysomnogram and only on epochs where the three experts agree in their sleep stage scoring.

Results: We show that in polysomnogram intervals, to which all three scorers assign the same sleep stage, our algorithm achieves 90% accuracy. This high rate of agreement with the human experts is accomplished with only a small set of three frequency features from the EEG. We increase the performance to 93% by including ECG and respiration features. In contrast, on intervals of ambiguous sleep stage, the sleep stage classification obtained from our algorithm, agrees with the human consensus scorer in approximately 61%.

Conclusions: These findings suggest that machine classification is highly consistent with human sleep staging and that error in the algorithm’s assignments is rather a problem of lack of well-defined criteria for human experts to judge certain polysomnogram epochs than an insufficiency of computational procedures.

On the difference of cardiorespiratory synchronisation and coordination

Cardiorespiratory phase synchronisation (CRS) is a type of cardiorespiratory coupling that manifests through a prediliction for heart beats to occur at specific points relative to the phase of the respiratory cycle. It has been under investigation for nearly 20 years, and while it seems to be mostly occurring in relaxed states such as deep sleep and anesthesia, no clear clinical implications have been established. Cardiorespiratory coordination (CRC) is a recent development in this field where the relationship between the respiratory onset and heart beat is analysed in the time domain and the possible relationship of each heart beat is considered for both the previous and the next respiratory onset. This ostensibly closely related effect must not only show relevant information content but also do so independent of CRS in order to be relevant for future studies. In this paper, we investigate CRC and its relation to CRS mainly using graphical and statistical methods on two exemplary datasets: measurements from a pregnant woman participating in a preeclampsia study and those from a man suffering from sleep apnea. We show fundamental differences between the results of both approaches and are able to show a formerly unknown dependency between the heart activity and respiratory rate, potentially indicating heartbeat-initiated inspiration. Despite their differences, methods developed for the quantification of CRS can be adapted to CRC. Completing the comparison is an investigation into the relationship between CRC and respiratory sinus arrhythmia. Similar to previous results for CRS, the two effects are found to be orthogonal, meaning that they can be observed independently or in conjunction.