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Abstract Background Sleep apnea syndrome, characterized by recurrent cessation (apnea) or reduction (hypopnea) of breathing during sleep, is a major risk factor for postoperative respiratory depression. Challenges in sleep apnea assessment have led to the proposal of alternative metrics derived from oxyhemoglobin saturation (SpO2), such as oxygen desaturation index (ODI) and percentage of cumulative sleep time spent with SpO2 below 90% (CT90), as predictors of postoperative respiratory depression. However, their performance has been limited with area under the curve of 0.60 for ODI and 0.59 for CT90. Our objective was to propose novel features from preoperative overnight SpO2 which are correlated with sleep apnea severity and predictive of postoperative respiratory depression. Methods Preoperative SpO2 signals from 235 surgical patients were retrospectively analyzed to derive seven features to characterize the sleep apnea severity. The features included entropy and standard deviation of SpO2 signal; below average burden characterizing the area under the average SpO2; average, standard deviation, and entropy of desaturation burdens; and overall nocturnal desaturation burden. The association between the extracted features and sleep apnea severity was assessed using Pearson correlation analysis. Logistic regression was employed to evaluate the predictive performance of the features in identifying postoperative respiratory depression. Results Our findings indicated a similar performance of the proposed features to the conventional apnea–hypopnea index (AHI) for assessing sleep apnea severity, with average area under the curve ranging from 0.77 to 0.81. Notably, entropy and standard deviation of overnight SpO2 signal and below average burden showed comparable predictive capability to AHI but with minimal computational requirements and individuals’ burden, making them promising for screening purposes. Our sex-based analysis revealed that compared to entropy and standard deviation, below average burden exhibited higher sensitivity in detecting respiratory depression in women than men. Conclusion This study underscores the potential of preoperative SpO2 features as alternative metrics to AHI in predicting postoperative respiratory.

Abstract Failure to employ suitable measures before administering full anesthesia to patients with obstructive sleep apnea (OSA) who are undergoing surgery may lead to developing complications after surgery. Therefore, it is very important to screen OSA before performing a surgery, which is currently done by subjective questionnaires such as STOP-Bang, Berlin scores. These questionnaires have 10–36% specificity in detecting sleep apnea, along with no information given on anatomy of upper airway, which is important for intubation. To address these challenges, we performed a pilot study to understand the utility of ultrasonography and vowel articulation in screening OSA. Our objective was to investigate the influence of OSA risk factors in vowel articulation through ultrasonography and acoustic features analysis. To accomplish this, we recruited 18 individuals with no risk of OSA and 13 individuals with high risk of OSA and asked them to utter vowels, such as /a/ (as in “Sah”), /e/ (as in “See”). An expert ultra-sonographer measured the parasagittal anterior–posterior (PAP) and transverse diameter of the upper airway. From the recorded vowel sounds, we extracted 106 features, including power, pitch, formant, and Mel frequency cepstral coefficients (MFCC). We analyzed the variation of the PAP diameters and vowel features from "See: /i/" to "Sah /a/" between control and OSA groups by two-way repeated measures ANOVA. We found that, there was a variation of upper airway diameter from “See” to “Sah” was significantly smaller in OSA group than control group (OSA: ∆12.8 ± 5.3 mm vs. control: ∆22.5 ± 3.9 mm OSA, p

Abstract Background Persons with asthma may experience excessive airway narrowing due to exercise or exposure to cold air, worsening their daily functionality. Exercise has several benefits for asthma control, but it may induce airway narrowing in some persons with asthma. When combined with cold temperatures, it introduces another layer of challenges. Therefore, managing this interaction is crucial to increase the quality of life in individuals with asthma. The purpose of this study was to develop a reliable experimental protocol to assess the effects of exercise and cold air on airway narrowing in adults with asthma in a controlled and safe environment. Methods This study was a randomized cross-over study in adults with and without asthma. Participants underwent a protocol involving a 10-min seated rest, followed by a 10-min cycling on a stationary bike in different temperatures of 0, 10, or 20 $$^{\circ }$$ ∘ C. The sequence of room temperatures was randomized, and there was a 30-min interval for recovery between each temperature transition. In each temperature, to measure lung function and respiratory symptoms, oscillometry and a questionnaire were used at 0 min (baseline), after 10 min of sitting and before starting biking (pre-exercise), and after 10 min of biking (post-exercise). At each room temperature, the changes in airway mechanics and asthma symptoms among baseline, pre-exercise, and post-exercise were compared with one-way repeated measures ANOVA or Friedman Rank Test. Within each arm, cardiac and thoraco-abdominal motion respiration signals were also measured continuously using electrodes and calibrated respiratory inductance plethysmographs, respectively. Results A total of 23 persons with asthma (11 females, age: 56.3 ± 10.9 years, BMI: 27.4 ± 5.7 kg/m2) and 6 healthy subjects (3 females, age: 61.8 ± 9.1 years, BMI: 28.5 ± 3.1 kg/m2) were enrolled in the study. Cold temperature of 0 $$^{\circ }$$ ∘ C induced airway narrowing in those with and without asthma after 10 and 20 min, respectively. Exercise intervention had significant changes in airway narrowing in participants with asthma in the range of 10–20 $$^{\circ }$$ ∘ C. Our results showed that in asthma, changes in subjective respiratory symptoms were due to both cold temperatures of 0 and 10 $$^{\circ }$$ ∘ C and exercise in the 0–20 $$^{\circ }$$ ∘ C range. Respiratory symptoms were not noticed among the healthy participants. Conclusion In conclusion, our findings suggest that exposure to cold temperatures of 0 $$^{\circ }$$ ∘ C could serve as a reliable method in the experimental protocol for inducing airway narrowing in asthma. The impact of exercise on airway narrowing was more variable among participants. Understanding these triggers in the experimental protocol is essential for the successful management of asthma in future studies.

Abstract Background The severity of sleep-disordered breathing is known to worsen postoperatively and is associated with increased cardio-pulmonary complications and increased resource implications. In the general population, the semi-upright position has been used in the management of OSA. We hypothesized that the use of a semi-upright position versus a non-elevated position will reduce postoperative worsening of OSA in patients undergoing non-cardiac surgeries. Methods This study was conducted as a prospective randomized controlled trial of perioperative patients, undergoing elective non-cardiac inpatient surgeries. Patients underwent a preoperative sleep study using a portable polysomnography device. Patients with OSA (apnea hypopnea index (AHI) > 5 events/hr), underwent a sleep study on postoperative night 2 (N2) after being randomized into an intervention group (Group I): semi-upright position (30 to 45 degrees incline), or a control group (Group C) (zero degrees from horizontal). The primary outcome was postoperative AHI on N2. The secondary outcomes were obstructive apnea index (OAI), central apnea index (CAI), hypopnea index (HI), obstructive apnea hypopnea index (OAHI) and oxygenation parameters. Results Thirty-five patients were included. Twenty-one patients were assigned to the Group 1 (females-14 (67%); mean age 65 ± 12) while there were fourteen patients in the Group C (females-5 (36%); mean age 63 ± 10). The semi-upright position resulted in a significant reduction in OAI in the intervention arm (Group C vs Group I postop AHI: 16.6 ± 19.0 vs 8.6 ± 11.2 events/hr; overall p = 0.01), but there were no significant differences in the overall AHI or other parameters between the two groups. Subgroup analysis of patients with “supine related OSA” revealed a decreasing trend in postoperative AHI with semi-upright position, but the sample size was too small to evaluate statistical significance. Conclusion In patients with newly diagnosed OSA, the semi-upright position resulted in improvement in obstructive apneas, but not the overall AHI. Trial registration This trial was retrospectively registered in clinicaltrials.gov NCT02152202 on 02/06/2014.

Objective: Sleep apnea is a chronic respiratory disorder and its standard assessment requires full night in-laboratory polysomnography (PSG). However, PSG is expensive, time-consuming, and inconvenient. Thus, there is a need to monitor sleep apnea with more convenient wearable devices. The objective of this study was to implement deep learning algorithms to monitor sleep apnea severity based on respiratory movements that can be easily recorded over the trachea. Methods: Adult individuals referred to the sleep laboratory at the Toronto Rehabilitation Institute for overnight sleep studies were included (N=69). Simultaneously with the PSG, an accelerometer was attached to the participant's suprasternal notch to record tracheal respiratory movements. Twenty-one features were extracted from the tracheal movements and used in a deep learning classifier to detect respiratory events. The apnea hypopnea index (AHI) was estimated as the number of events per hour of sleep. Results: The F1 score of the event-by-event detection algorithm was between 12% and 71% for different groups of sleep apnea severity. There was a strong correlation between the estimated and the PSG-derived AHI (r=0.86, p

BackgroundSleep apnea is a respiratory disorder characterized by frequent breathing cessation during sleep. Sleep apnea severity is determined by the apnea-hypopnea index (AHI), which is the hourly rate of respiratory events. In positional sleep apnea, the AHI is higher in the supine sleeping position than it is in other sleeping positions. Positional therapy is a behavioral strategy (eg, wearing an item to encourage sleeping toward the lateral position) to treat positional apnea. The gold standard of diagnosing sleep apnea and whether or not it is positional is polysomnography; however, this test is inconvenient, expensive, and has a long waiting list. ObjectiveThe objective of this study was to develop and evaluate a noncontact method to estimate sleep apnea severity and to distinguish positional versus nonpositional sleep apnea. MethodsA noncontact deep-learning algorithm was developed to analyze infrared video of sleep for estimating AHI and to distinguish patients with positional vs nonpositional sleep apnea. Specifically, a 3D convolutional neural network (CNN) architecture was used to process movements extracted by optical flow to detect respiratory events. Positional sleep apnea patients were subsequently identified by combining the AHI information provided by the 3D-CNN model with the sleeping position (supine vs lateral) detected via a previously developed CNN model. ResultsThe algorithm was validated on data of 41 participants, including 26 men and 15 women with a mean age of 53 (SD 13) years, BMI of 30 (SD 7), AHI of 27 (SD 31) events/hour, and sleep duration of 5 (SD 1) hours; 20 participants had positional sleep apnea, 15 participants had nonpositional sleep apnea, and the positional status could not be discriminated for the remaining 6 participants. AHI values estimated by the 3D-CNN model correlated strongly and significantly with the gold standard (Spearman correlation coefficient 0.79, P

A reliable, accessible, and non-intrusive method for tracking respiratory and heart rate is important for improving monitoring and detection of sleep apnea. In this study, an algorithm based on motion analysis of infrared video recordings was validated in 50 adults referred for clinical overnight polysomnography (PSG). The algorithm tracks the displacements of selected feature points on each sleeping participant and extracts respiratory rate using principal component analysis and heart rate using independent component analysis. For respiratory rate estimation (mean ± standard deviation), 89.89 % ± 10.95 % of the overnight estimation was accurate within 1 breath per minute compared to the PSG-derived respiratory rate from the respiratory inductive plethysmography signal, with an average root mean square error (RMSE) of 2.10 ± 1.64 breaths per minute. For heart rate estimation, 77.97 % ± 18.91 % of the overnight estimation was within 5 beats per minute of the heart rate derived from the pulse oximetry signal from PSG, with mean RMSE of 7.47 ± 4.79 beats per minute. No significant difference in estimation of RMSE of either signal was found according to differences in body position, sleep stage, or amount of the body covered by blankets. This vision-based method may prove suitable for overnight, non-contact monitoring of respiratory rate. However, at present, heart rate monitoring is less reliable and will require further work to improve accuracy.

Obstructive sleep apnea (OSA) is a respiratory disorder characterized by interruption to breathing during sleep. Usually, the OSA is more severe in the supine sleeping position. Recent studies also demonstrated that the head position may play an important role in the pathophysiology of the OSA. Therefore, monitoring the sleeping body and the head position has high clinical importance to optimize the treatment of the OSA. In this paper, three machine learning approaches were used to detect the head position during sleep in infrared images. In the first two methods, supervised classifiers were trained to estimate the head position based on different feature sets extracted from infrared images. In the third method, three different convolutional neural network (CNN) structures (ResNet50, MobileNet, and Darknet19) were trained to detect the head position during sleep. To detect the body position, the same CNN architectures were trained on infrared images. Overnight sleeping data (sleep duration =5±1h) from 50 participants (age: 53 ± 15 years, BMI: 29 ± 6 kg/m2, and 30 men/20 women) with various levels of OSA severity as measured by the apnea-hypopnea index (AHI =25±29 events/h and OSA severity: 12 normal, 13 mild, 11 moderate, and 14 severe) were collected for this paper. The models were trained on the data collected in one laboratory room from half of the participants and tested on the data from the other half collected in a different laboratory room. The best performing model (Darknet19) correctly estimated the lateral versus supine head position with 92% accuracy and 94% F1-Score and the lateral versus supine body position with 87% accuracy and 87% F1-Score.

Abstract Introduction Although the precise cause of obstructive sleep apnea (OSA) remains unknown, various anatomical or structural factors are thought to influence upper airway patency. Recent clinical studies show that OSA is frequently observed among patients with fluid‐retaining states, such as heart/renal failure and postsurgery. It is important to note that a cause–effect relationship is not yet established, and our understanding of the effects of fluid overload is limited. The goal of this study was to investigate an animal model that can characterize the physiological changes that occur in response to fluid overload. Method Acute nonsurvival experiments were conducted in 16 Sprague–Dawley rats. Rats were initially anesthetized by inhaled isoflurane, while the femoral vein was cannulated and urethane (1.2–1.5 g/Kg body weight) was gradually delivered intravenously to induce anesthesia. Additional doses of urethane were delivered as necessary to maintain a surgical plane of anesthesia. A surgical incision was made on the cervical area to catheterize carotid artery to measure blood pressure. A pair of stainless‐steel wires was injected into the tongue to measure genioglossus muscle activity (GGEMG). All physiological measurements were recorded as intravenous infusion of saline was provided to the rat (infusion rate = 22 ml/kg over 30 min). Results Acute saline overloading resulted in a 33% decrease in GGEMG, when compared to baseline. There was also a gradual drop in the respiratory rate (13% decrease) that reached statistical significance at 10 min after infusion was stopped. The blood pressure exhibited a 14% increase which subsequently returned to baseline within 40 min stopping infusion. There were no significant changes in the heart rate. Conclusion The results of this study indicate that systemic fluid overload can affect significant changes in different physiological systems including reduction in genioglossus muscle activity, increase in blood pressure, and change autonomic nervous system function.

Abstract Leg fluid accumulation during sedentary behaviours such as sitting can lead to leg edema and associated adverse health consequences. This study investigates the use calf muscle electrical stimulation (ES) to reduce seated leg fluid accumulation. Thirteen non-obese, normotensive men (mean age 51 yr.) with sleep apnea were enrolled in the study. Participants first lay supine for 30 minutes to equalize fluid distribution and then sat for 150 minutes. While seated, participants received either active or sham ES of the calf muscles, according to random assignment. Participants returned one-week later to cross over to the other study condition. Leg fluid was measured continuously while sitting using the bioelectrical impedance method. Fluid accumulation in the leg was reduced by more than 40% using active ES, compared to sham ES (∆ = 51.9 ± 8.8 ml vs. ∆ = 91.5 ± 8.9 ml, P

INTRODUCTION:Nocturnal worsening of asthma symptoms is a common feature of asthma. Physical exercise training improves general asthma control; however, there is no evidence showing the effects of physical exercise on nocturnal asthma symptoms. Indeed, asthma patients with daytime and nighttime symptoms are physiologically different, and thus the effects of physical exercise on asthma may also be different in these two groups. The objective of this systematic review is to explore the effects of physical exercise on nocturnal asthma symptoms. METHODS:Searches were conducted in MEDLINE, Embase, Cochrane Central Register of Controlled Trials, CINAHL and SPORTdiscus (last search on November 2017). Authors from studies that did not report nocturnal symptoms but used questionnaires and/or diaries were contacted for detailed information. Studies that provided results on nocturnal symptoms before and after physical activity intervention were included. Prevalence of nocturnal symptoms was calculated for each study from the percentage of study participants with nocturnal symptoms before and after intervention. RESULTS:Eleven studies were included (5 with children and 6 with adults). The prevalence of nocturnal symptoms at baseline ranged from 0% to 63% among children and from 50-73% among adults. In children and adults with nocturnal asthma, aerobic physical exercise reduced the prevalence and frequency of nocturnal symptoms. CONCLUSIONS:Aerobic physical exercise improves nocturnal asthma in children and adults by reducing the prevalence and frequency of nocturnal symptoms. Physical exercise training could be used with conventional treatments to improve quality of life and asthma control in patients with nocturnal worsening of asthma.

Background: We have previously shown that when asthmatics go supine, fluid shifts out of the legs, accumulates in the thorax, and exacerbates lower airway narrowing. In the retrospective analysis of our previous work presented here, we test the hypothesis that the sensitivity of this process relates inversely to baseline caliber of the lower airways.Methods: Eighteen healthy (six women) and sixteen asthmatic subjects (nine women) sat for 30 min, and then lay supine for 30 min. While supine, lower body positive pressure (LBPP, 40 mm Hg) was applied to displace fluid from the legs similar in amount to the overnight fluid shift. Respiratory resistance and reactance at 5 Hz (R5 and X5) and leg and thoracic fluid volumes (LFV and TFV) were measured at the beginning and end of the supine period.Results: With LBPP, healthy, and asthmatic subjects had similar changes in the LFV and TFV (p = 0.3 and 0.1, respectively). Sensitivity to fluid shift, defined by ΔR5/ΔTFV, was larger in the asthmatics than in the healthy subjects (p = 0.0001), and correlated with baseline R5 in the supine position in the asthmatics (p = 0.7, p = 0.003). No such association was observed in the healthy subjects (p = 0.6). In the asthmatics, women showed a greater reduction in X5 than men with LBPP (p = 0.009).Conclusions: Smaller baseline airway caliber, as assessed by larger R5, was associated with increased sensitivity to fluid shift in the supine position. We conclude that asthmatics with narrower small airways such as obese asthma patients, women with asthma and those with severe asthma may be more sensitive to the effects fluid shift while supine as during sleep.