Relationship between airflow limitation in response to upper airway negative pressure during wakefulness and obstructive sleep apnea severity.

PURPOSE: The objective was to determine if alteration in airflow induced by negative pressure (NP) applied to participants' upper airways during wakefulness, is related to obstructive sleep apnea (OSA) severity as determined by the apnea-hypopnea index (AHI). METHODS: Adults 18 years of age or greater were recruited. All participants underwent overnight polysomnography to assess their apnea-hypopnea index (AHI). While awake, participants were twice exposed, orally, to -3 cm H2O of NP for five full breaths. The ratio of the breathing volumes of the last two breaths during NP exposure to the last two breaths prior to NP exposure was deemed the NP ratio (NPR). RESULTS: Eighteen participants were enrolled. A strong relationship between the AHI and the exponentially transformed NPR (ExpNPR) for all participants was observed (R2 = 0.55, p < 0.001). A multivariable model using the independent variable ExpNPR, age, body mass index and sex accounted for 81% of variability in AHI (p = 0.0006). A leave-one-subject-out cross-validation analysis revealed that predicted AHI using the multivariable model, and actual AHI from participants' polysomnograms, were strongly related (R2 = 0.72, p < 0.001). CONCLUSION: We conclude that ExpNPR, was strongly related to the AHI, independently of demographic factors known to be related to the AHI.

Validation of a Manual Negative Pressure Wound Therapy Device (PragmaVAC) for Acute and Chronic Wounds: A Prospective, Randomized, Controlled Trial.

BACKGROUND: Negative pressure wound therapy (NPWT) is an alternative to the standard gauze dressings for wound treatment. Due to limited health resources, poor electrical supply, and high costs, NPWT in resource-constrained settings is inaccessible. In conflict-affected settings, civilian injuries typically involve traumatic wounds or chronic wound infections that affect the extremities. METHODS: PragmaVAC® is a manually operated NPWT device designed to increase accessibility to NPWT without the need of electrical power. We aimed to determine the clinical efficacy of PragmaVAC through a controlled, non-blinded open-label clinical trial in a resource-constrained locality. The endpoint was formation of granulation tissue sufficient for wound closure. RESULTS: Fifty-nine patients qualified for analysis (19 Gauze; 40 PragmaVAC). The mean age of participants was 49.25 years, 55.9% were male, and 42.4% were diabetic. Forty three wounds (72.9%) were acute, 44 wounds (74.6%) were clean-contaminated, and 34 wounds (57.6%) were localized to the lower limb. The average duration of treatment was 15.3 days in PragmaVAC vs 36.5 days in control, p = 0.013. Similarly, PragmaVAC required fewer number of dressing changes 2.7 vs 23.2 times, p < 0.0001, at a lower frequency of dressings 0.22/day vs 0.73/day, in the control group, p < 0.0001. CONCLUSIONS: PragmaVAC is associated with accelerated healing and less frequent requirement of dressing changes. The introduction of a manually operated, low-cost device in resource-constrained settings presents an opportunity to improve wound care outcomes, decrease interventions, and optimize usage of material and human resources.

Relative tidal volume and respiratory airflow estimation using tracheal sound and movement during sleep.

Airflow is the reference signal to assess sleep respiratory disorders, such as sleep apnea. Previous studies estimated airflow using tracheal sounds in short segments with specific airflow rates, while requiring calibration or a few breaths for tuning the relationship between sound energy and airflow. Airflow-sound relationship can change by posture, sleep stage and airflow rate or tidal volume. We investigated the possibility of estimating surrogates of tidal volume without calibration in the adult sleep apnea population using tracheal sounds and movements. Two surrogates of tidal volume: thoracoabdominal range of sum movement and airflow level were estimated. Linear regression was used to estimate thoracoabdominal range of sum movement from sound energy and the range of movements. The sound energy lower envelope was found to correlate with airflow level. The agreement between reference and estimated signals was assessed by repeated-measure correlation analysis. The estimated tidal volumes were used to estimate the airflow signal. Sixty-one participants (30 females, age: 51 ± 16 years, body mass index: 29.5 ± 6.4 kg m-2 , and apnoea-hypopnea index: 20.2 ± 21.2) were included. Reference and estimated thoracoabdominal range of sum movement of whole night data were significantly correlated with the reference signal extracted from polysomnography (r = 0.5 ± 0.06). Similarly, significant correlations (r = 0.3 ± 0.05) were found for airflow level. Significant differences in estimated surrogates of tidal volume were found between normal breathing and apnea/hypopnea. Surrogate of airflow can be extracted from tracheal sounds and movements, which can be used for assessing the severity of sleep apnea and even phenotyping sleep apnea patients based on the estimated airflow shape.

Dissociation between objectively quantified snoring and sleep quality.

BACKGROUND: The impact of simple snoring on sleep structure and sleepiness has not been well described. In several studies, self-reported snoring was associated with increased daytime sleepiness. However, most studies did not distinguish patients with simple snoring from those with coexisting obstructive sleep apnea (OSA) using objective measures. We therefore evaluated the relationship between objectively measured snoring and both sleep structure and daytime sleepiness in patients with no or mild OSA. METHODS: Subjects referred for suspected sleep disorders underwent polysomnography (PSG) during which breath sounds were recorded by a microphone. Those with an apnea-hypopnea index (AHI) <15/h were analyzed. Individual snores were identified by a computer algorithm, from which the snore index (SI) was calculated as the number of snores/h of sleep. Sleep stages and arousals were quantified. Daytime sleepiness was evaluated using the Epworth Sleepiness Scale (ESS) score. RESULTS: 74 (35 males) subjects were included (age, mean ±â€¯SD: 46.4 ±â€¯15.3 years and body mass index: 29.8 ±â€¯7.0 kg/m2). The mean SI was 266 ±â€¯243 snores/h. Subjects were categorized according to their SI into 3 tertiles: SI < 100, between 100-350, and >350. No sleep structure indeces, arousals, or ESS score differed among SI tertiles (p > 0.13). There was no correlation between SI and any of these variables (p > 0.29). In contrast, the AHI was significantly related to frequency of arousals (r = 0.23, p = 0.048). CONCLUSIONS: These findings suggest that simple snoring assessed objectively is not related to indices of sleep structure or subjective sleepiness.

In-hospital diagnosis of sleep apnea in stroke patients using a portable acoustic device.

PURPOSE: Sleep apnea (SA) is highly prevalent in post-stroke patients. Due to physical disability and relative inaccessibility of polysomnography (PSG) to test for SA, patients with stroke frequently remain undiagnosed and untreated. Portable SA monitoring can facilitate at-home or in-hospital testing for SA. However, portable SA monitoring is not recommended in those with complex medical conditions, such as stroke, due to the lack of validation of portable monitoring in such patients. METHODS: The objective of our study was to test the accuracy and feasibility of a portable single-channel acoustic device, BresoDx™ for quantifying the apnea-hypopnea index (AHI) and diagnosing SA in a post-stroke population. Patients who recently suffered a stroke and were undergoing rehabilitation in a stroke rehabilitation unit (SRU) underwent testing with BresoDx both simultaneously during attended PSG and unattended on the SRU. RESULTS: We studied 23 stroke patients of whom 78% had SA (defined by AHI ≥15) on PSG. All of the patients tolerated the BresoDx. Using cutoff AHI of ≥15 by PSG to diagnose SA, BresoDx had sensitivity of 90.0%, specificity of 84.6%, and overall accuracy of 87.0% in the laboratory. CONCLUSIONS: This study demonstrates that BresoDx is well tolerated and feasible to use in the post-stroke population where it was found to have excellent positive and negative predictive values for the diagnosis of SA.

Influence of head position on obstructive sleep apnea severity.

OBJECTIVE: Supine body orientation plays an important role in precipitating upper airway collapse in a significant proportion of obstructive sleep apnea (OSA) patients known to have supine-predominant OSA (OSAsup). Traditionally, trunk position is used to assess OSAsup, but the role of the head position has not been established. We hypothesized that head position influences OSA independently of trunk position. METHODS: Head and trunk positions were determined from subjects undergoing overnight polysomnography. The apnea-hypopnea index (AHI), rapid eye movement (REM), and non-REM sleep time of all trunk and head positions (lateral and supine) were calculated and compared against the complete supine position, i.e., head and trunk supine. RESULTS: In 26 subjects, lateral rotation of the head to the right or left with the trunk supine resulted in a significant reduction in AHI from 36.0 ± 22.5 to 25.8 ± 16.6 (p = 0.008), and an AHI drop <10 in 27% of patients. The "trunk lateral-head lateral" position resulted in a more dramatic reduction in AHI from 31.6 ± 20.2 to 4.1 ± 4.1 (p < 0.0001). The distributions of REM and non-REM sleep were not different among positions. In the subgroup with a body mass index (BMI) <32 kg/m2 (15 subjects), the AHI reduction with lateral head rotation was significant (p = 0.005) but not in remaining 11 obese patient with a BMI ≥32 kg/m2 (p = 0.24). CONCLUSION: OSA severity with the trunk in the supine position decreased significantly when the head rotated from supine to lateral, particularly in non-obese patients. These results demonstrate an important influence of head position on the AHI, independently of trunk position and sleep stage, in patients with OSA.

A system for portable sleep apnea diagnosis using an embedded data capturing module.

UNLABELLED: Sleep apnea (SA) is a very common disease with serious health consequences, yet is very under-diagnosed, partially because of the high cost and limited accessibility of in-laboratory polysomnography (PSG). The purpose of this work is to introduce a newly developed portable system for the diagnosis of SA at home that is both reliable and easy to use. The system includes personal devices for recording breath sounds and airflow during sleep and diagnostic algorithms to process the recorded data. The data capturing device consists of a wearable face frame with an embedded electronic module featuring a unidirectional microphone, a differential microphone preamplifier, a microcontroller with an onboard differential analogue to digital converter, and a microSD memory card. The device provides continuous data capturing for 8 h. Upon completion of the recording session, the memory card is returned to a location for acoustic analysis. We recruited 49 subjects who used the device independently at home, after which each subject answered a usability questionnaire. Random data samples were selected to measure the signal-to-noise ratio (SNR) as a gauge of hardware functionality. A subset of 11 subjects used the device on 2 different nights and their results were compared to examine diagnostic reproducibility. Independent of those, system's performance was evaluated against PSG in the lab environment in 32 subject. The overall success rate of applying the device in un-attended settings was 94 % and the overall rating for ease-of-use was 'excellent'. Signal examination showed excellent capturing of breath sounds with an average SNR of 31.7 dB. Nine of the 11 (82 %) subjects had equivalent results on both nights, which is consistent with reported inter-night variability. The system showed 96 % correlation with simultaneously performed in-lab PSG. CONCLUSION: Our results suggest excellent usability and performance of this system and provide a strong rationale to further improve it and test its robustness in a larger study.

Monitoring of breathing phases using a bioacoustic method in healthy awake subjects.

OBJECTIVE: To test the ability of a microphone recording system, located distal to the respiratory outflow tract, to track the timing of the inspiratory and expiratory phases of breathing in awake healthy subjects. METHODS: Fifteen subjects participated. Breath sounds were recorded using a microphone embedded in a face frame in a fixed location in relation to the nostrils and mouth, while simultaneously recording respiratory movements by respiratory inductance plethysmography (RIP). Subjects were studied while supine and were instructed to breathe normally for 2 min: through their noses only (nasal breathing), during the first min, and through their mouths only (oral breathing) during the second min. Five subjects (test group) were chosen randomly to extract features from their acoustic data. Ten breaths (5 nasal and 5 oral breaths) from each subject were studied. Inspiratory and expiratory segments of breath sounds were determined and extracted from the acoustic data by comparing it to the RIP trace. Subsequently, the frequency spectrum of each phase was then determined. Spectral variables derived from the 5 test subjects were applied prospectively to detect breathing phases in the remaining 10 subjects (validation group). RESULTS: Test group data showed that the mean of all inspiratory spectra peaked between 30 and 270 Hz, flattened between 300 and 1,100 Hz, and peaked again with a center frequency of 1,400 Hz. The expiratory spectra peaked between 30 and 180 Hz and its power dropped off exponentially after that. Accordingly, the bands ratio (BR) of frequency magnitudes between 500 and 2500 Hz to frequency magnitudes between 0 and 500 Hz was chosen as a feature to distinguish between breathing phases. BR for the mean inspiratory spectrum was 2.27 and for the mean expiratory spectrum was 0.15. The route of breathing did not affect the BR ratio within the same phase. When this BR was applied to 436 breathing phases in the validation group, 424 (97%) were correctly identified (Kappa = 0.96, P < 0.001) indicating strong agreement between the acoustic method and the RIP. CONCLUSION: Frequency spectra of breathing sounds recorded from a face-frame, reliably identified the inspiratory and expiratory phases of breathing. This technique may have various applications for respiratory monitoring and analysis.

Automatic Respiratory Phase Identification Using Tracheal Sounds and Movements During Sleep.

One of the most important signals to assess respiratory function, especially in patients with sleep apnea, is airflow. A convenient method to estimate airflow is based on analyzing tracheal sounds and movements. However, this method requires accurate identification of respiratory phases. Our goal is to develop an automatic algorithm to analyze tracheal sounds and movements to identify respiratory phases during sleep. Data from adults with suspected sleep apnea who were referred for in-laboratory sleep studies were included. Simultaneously with polysomnography, tracheal sounds and movements were recorded with a small wearable device attached to the suprasternal notch. First, an adaptive detection algorithm was developed to localize the respiratory phases in tracheal sounds. Then, for each phase, a set of morphological features from sound energy and tracheal movement were extracted to classify the localized phases into inspirations or expirations. The average error and time delay of detecting respiratory phases were 7.62% and 181 ms during normal breathing, 8.95% and 194 ms during snoring, and 13.19% and 220 ms during respiratory events, respectively. The average classification accuracy was 83.7% for inspirations and 75.0% for expirations. Respiratory phases were accurately identified from tracheal sounds and movements during sleep.

Toward mitigating pressure injuries: Detecting patient orientation from vertical bed reaction forces.

INTRODUCTION: Prolonged bed rest without repositioning can lead to pressure injuries. However, it can be challenging for caregivers and patients to adhere to repositioning schedules. A device that alerts caregivers when a patient has remained in the same orientation for too long may reduce the incidence and/or severity of pressure injuries. This paper proposes a method to detect a person's orientation in bed using data from load cells placed under the legs of a hospital grade bed. METHODS: Twenty able-bodied individuals were positioned into one of three orientations (supine, left side-lying, or right side-lying) either with no support, a pillow, or a wedge, and the head of the bed either raised or lowered. Breathing pattern characteristics extracted from force data were used to train two machine learning classification systems (Logistic Regression and Feed Forward Neural Network) and then evaluate for their ability to identify each participant's orientation using a leave-one-participant-out cross-validation. RESULTS: The Feed Forward Neural Network yielded the highest orientation prediction accuracy at 94.2%. CONCLUSIONS: The high accuracy of this non-invasive system's ability to a participant's position in bed shows potential for this algorithm to be useful in developing a pressure injury prevention tool.

Portable diagnosis of sleep apnea with the validation of individual event detection.

STUDY OBJECTIVE: To develop an algorithm for improving apnea hypopnea index (AHI) estimation which includes event by event validation and event duration estimation. The algorithm uses breathing sounds, respiratory related movements and blood oxygen saturation (SaO2). METHODS: Adults with suspected sleep apnea underwent overnight polysomnography (PSG) at Toronto Rehabilitations Institute. Simultaneously with PSG, breathing sounds and respiratory related movements were recorded over the suprasternal notch using the Patch. The Patch had a microphone and an accelerometer to record respiratory sounds and movement, respectively. First, we calculated the amount of drops in SaO2 from pulse oximeter. Subsequently, energy of breaths and accelerometer were extracted. Features were normalized, weighted, summed and passed through a threshold to estimate PatchAHI. PatchAHI was compared to the AHI obtained from PSG (PSGAHI). Furthermore, performance of event detection was evaluated using F1-score. Moreover, event duration difference between estimated and PSG-based events was compared. RESULTS: Data from 69 subjects were investigated. PatchAHI had high correlation with PSGAHI (r2 = 0.88). Considering a diagnostic AHI cut-off of ≥15, sensitivity and specificity were 91.42 ± 11.92% and 89.29 ± 7.62%, respectively. F1-score for individual event detection increased from 0.22 ± 0.10 for AHI≤5 to 0.72 ± 0.09 for AHI >30. Moreover, event duration difference between estimated events and PSG-based events was 5.33 ± 8.17 sec. CONCLUSION: Our proposed algorithm had high accuracy in estimating individual respiratory events during sleep. The algorithm can increase reliability of acoustic methods for diagnosis of sleep apnea at home.

Long-term effects of cardiac rehabilitation on sleep apnea severity in patients with coronary artery disease.

STUDY OBJECTIVES: Sleep apnea (SA) is prevalent among patients with coronary artery disease (CAD) and increases cardiovascular risk. A previous study showed that 1 month of cardiac rehabilitation (CR) reduced severity of SA in patients with CAD by reducing fluid accumulation in the legs during the day and the amount of fluid shifting rostrally into the neck overnight. The aim of this study was to evaluate whether CR will lead to longer-term attenuation of SA in patients with CAD. METHODS: Fifteen patients with CAD and SA who had participated in a 1-month randomized trial of the effects of exercise training on SA were followed up until they completed 6 months of CR (age: 65 ± 10 years; body mass index: 27.0 ± 3.9 kg/m²; apnea-hypopnea index [AHI]: 39.0 ± 16.7). The AHI was evaluated at baseline by polysomnography and then at 6 months by portable monitoring at home. Cardiorespiratory fitness (VO2peak) was evaluated via a graded cardiopulmonary exercise test at baseline and 6 months later. The 6-month CR program included once weekly, 90-minute, in-facility exercise sessions, and 4 days per week at-home exercise sessions. RESULTS: After 6 months of CR, there was a 54% reduction in the AHI (30.5 ± 15.2 to 14.1 ± 7.5, P < .001). Body mass index remained unchanged, but VO2peak increased by 27% (20.0 ± 6.1 to 26.0 ± 8.9 mL/kg/min, P = .04). CONCLUSIONS: Participation in CR is associated with a significant long-term decrease in the severity of SA. This finding suggests that attenuation of SA by exercise could be a mechanism underlying reduced mortality following participation in CR in patients with CAD and SA. CLINICAL TRIAL REGISTRATION: This study is registered at www.controlled-trials.com with identifier number ISRCTN50108373.

Blood pressure and thermal responses to repeated whole body cold exposure: effect of winter clothing.

The effect of outdoor clothing and repeated cold exposure on blood pressure, heart rate, skin temperature, and thermal sensation was studied in 16 young (18-34 years) and 8 middle-aged (35-51 years) normotensive participants. Four winter clothing ensembles were used: regular winter clothing without a hat, with a hat, with an extra pair of pants, and with a hat and an extra pair of pants. The participants were exposed four times to -5 degrees C for 15 min wearing different clothing ensembles in counterbalanced order and each cold exposure was followed by 25 min of rewarming at 25 degrees C. The results showed that systolic and diastolic blood pressure increased in cold and increased more when a hat was not used. Wearing hats not only reduced the blood pressure response during cold exposure, but also promoted faster recovery of forehead skin temperature and blood pressure. These findings are encouraging and warrant further investigations to better understand the benefits of wearing appropriate clothing in the winter, especially among older people and patients with cardiovascular diseases.

Objective Relationship Between Sleep Apnea and Frequency of Snoring Assessed by Machine Learning.

STUDY OBJECTIVES: Snoring is perceived to be directly proportional to sleep apnea severity, especially obstructive sleep apnea (OSA), but this notion has not been thoroughly and objectively evaluated, despite its popularity in clinical practice. This might lead to overdiagnosis or underdiagnosis of OSA. The goal of this study is to examine this notion and objectively quantify the relationship between sleep apnea and snoring detected using advanced signal processing algorithms. METHODS: We studied adults referred for polysomnography, from which the apnea-hypopnea index (AHI) was derived. Breath sounds were recorded simultaneously, from which snoring was accurately quantified using acoustic analysis of breath sounds and machine-learning computer algorithms. The snore index (SI) was calculated as the number of snores per hour of sleep. RESULTS: In 235 patients, the mean AHI was 20.2 ± 18.8 and mean SI was 320.2 ± 266.7 events/h. On the one hand, the overall correlation between SI and AHI was weak but significant (r = .32, P < .0001). There was a significant stepwise increase in SI with increasing OSA severity, but with a remarkable overlap in SI among OSA severity categories. On the other hand, SI had weak negative correlation with central AHI (r = -.14, P = .035). SI had modest positive and negative predictive values for OSA (0.63 and 0.62 on average, respectively) and good sensitivity but low specificity (0.91 and 0.31 on average, respectively) attributed to the large number of snorers without OSA. CONCLUSIONS: Snoring on its own is probably of limited usefulness in assessing sleep apnea presence and severity, because of its weak relationship with AHI. Thus, the complaint of snoring should be interpreted with caution to avoid unnecessary referrals for sleep apnea testing. Conversely, clinicians should be aware of the possibility of missing diagnosis of patients with sleep apnea who have minimal snoring.

Sleep Apnea Severity Estimation from Respiratory Related Movements Using Deep Learning.

Sleep apnea is a common chronic respiratory disorder which occurs due to the repetitive complete or partial cessations of breathing during sleep. The gold standard assessment of sleep apnea requires full night polysomnography in a sleep laboratory which is expensive, time consuming, and inconvenient. Hence, there is an urgent need for a convenient, robust and wearable monitoring device for screening of sleep apnea. A simple and convenient accelerometer-based portable system is presented to estimate the severity of sleep apnea by analyzing tracheal movements. Respiratory related movements were recorded over the suprasternal notch using a 3D accelerometer. Twenty-one physiological features (7 features, 3 accelerometer channels) were extracted. Performance of three different deep learning models - convolutional neural network, recurrent neural network, and their combination - were evaluated for estimating the apnea hypopnea index (AHI). The estimated AHI is compared to the gold standard polysomnography. In 3-fold cross-validation experiments with 20 participants (9 female, age=47.8±18.0 years, BMI=30.8±4.8, AHI=22.2±21.8 events/hr), we achieved a correlation coefficient between gold standard and estimated values (r-value = 0.84). The proposed system is an accurate, convenient, and portable device suitable for home sleep apnea screening.

Effect of calf muscle electrical stimulation on rostral fluid shift, snoring and obstructive sleep apnea.

STUDY OBJECTIVES: Overnight fluid shift from the legs into the neck may contribute to the pathogenesis of snoring and obstructive sleep apnea (OSA). The present study investigates the effects of calf muscle electrical stimulation (ES) on reducing leg fluid accumulation while seated, subsequent rostral fluid shift on lying down, and the impact on snoring and OSA. METHODS: Sixteen non-obese, normotensive men with OSA participated in the study. On the first study day, participants sat for 150 min receiving either active or sham ES through random allocation, then lied supine for 60 min. While seated and supine, leg and neck fluid volumes were measured using bioelectrical impedance to determine the magnitude of fluid shift. On the night of the study day, participants wore a portable sleep apnea diagnostic device overnight to measure snoring and sleep apnea severity. One week later, participants crossed over to the other study condition. RESULTS: Active calf muscle ES reduced leg fluid accumulation by 46% while seated. Upon lying supine, active ES reduced fluid shift out of the legs by 17% and reduced neck fluid accumulation by 31%. This led to a 15% reduction in snoring index, but did not alleviate OSA. CONCLUSIONS: One session of calf muscle ES was effective at reducing leg fluid accumulation and rostral fluid shift, which led to a modest reduction in the snoring index, but not OSA. Despite this lack of effect of calf muscle ES in attenuating OSA severity, the reduction in the snoring index suggests that it did have an effect, albeit mild, on upper-airway mechanics.

Heart rate variability in pulmonary hypertension with and without sleep apnea.

OBJECTIVES: Our aims were to evaluate HRV in pulmonary hypertension (WHO Group 1 and 4) compared to control subjects, and to assess whether the presence of sleep apnea in those with pulmonary hypertension would be deleterious and cause greater impairment in HRV. METHODS: This retrospective case-control study analyzed electrocardiogram segments obtained from diagnostic polysomnography. RESULTS: Forty-one pulmonary hypertension patients were compared to 41 age, sex and apnea-hypopnea index matched healthy controls. The pulmonary hypertension group had decreased high frequency, very low frequency, low frequency, and percentage of normal R-R intervals that differ by > 50 ms compared to control subjects. Moderate to severe right ventricle dysfunction on echocardiography was a predictor of lower high frequency in pulmonary hypertension patients. CONCLUSIONS: There were no differences in any HRV measures in pulmonary hypertension patients with or without sleep apnea. Impaired HRV was demonstrated in pulmonary hypertension patients however, the presence of sleep apnea did not appear to further reduce vagal modulation.

Relationship of stroke volume to different patterns of Cheyne-Stokes respiration in heart failure.

STUDY OBJECTIVES: In patients with heart failure (HF) and reduced left ventricular ejection fraction (HFrEF), stroke volume (SV) falls during hyperpnea of Cheyne-Stokes respiration with central sleep apnea (CSR-CSA). We have identified two distinct patterns of hyperpnea: positive, in which end-expiratory lung volume (EELV) remains at or above functional residual capacity (FRC), and negative, in which EELV falls below FRC. The increase in expiratory intrathoracic pressure generated by the latter should have effects on the heart analogous to external chest compression. To test the hypotheses that in HFrEF patients, CSR-CSA with the negative pattern has an auto-resuscitation effect such that compared with the positive pattern, it is associated with a smaller fall in SV and a smaller increase in cardiac workload (product of heart rate and systolic blood pressure). METHODS: In 15 consecutive HFrEF patients with CSR-CSA during polysomnography, hemodynamic data derived from digital photoplethysmography during positive and negative hyperpneas were compared. RESULTS: Compared to the positive, negative hyperpneas were accompanied by reductions in the maximum and mean relative fall in SV of 30% (p = 0.002) and 10% (p = 0.031), respectively, and by reductions in the degree of increases in heart rate and rate pressure product during hyperpnea of 46% (p < 0.001) and 13% (p = 0.007), respectively. CONCLUSIONS: Our findings suggest the novel concept that the negative pattern of CSR-CSA may constitute a form of auto-resuscitation that acts as a compensatory mechanism to maintain SV in patients with severe HF.

Diagnosis of Obstructive Sleep Apnea during Wakefulness Using Upper Airway Negative Pressure and Machine Learning.

Background and Rational: Obstructive Sleep Apnea (OSA) is a common disorder, affecting almost 10% of adults, but very underdiagnosed. This is largely due to limited access to overnight sleep testing using polysomnography (PSG). Our goal was to distinguish OSA from healthy individual using a simple maneuver during wakefulness in combination with machine learning methods. Methods: Participants have undergone an overnight PSG to determine their ground truth OSA severity. Separately, they were asked to breathe through a nasal mask or a mouth piece through which negative pressure (NP) was applied, during wakefulness. Airflow waveforms were acquired and several features were extracted and used to train various classifiers to predict OSA. Results and Discussion: The performance of each classifier and experimental setup was calculated. The best results were obtained using Random Forest classifier for distinguishing OSA from healthy individuals with a very good area under the curve of 0.80. To the best of our knowledge, this is the first study to deploy machine learning and NP with promising path to diagnose OSA during wakefulness.