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Differentiation between obstructive and central apneas and hypopneas requires quantitative measurement of respiratory effort (RE) using esophageal pressure (PES), which is rarely implemented. This study investigated whether the sleep mandibular movements (MM) signal recorded with a tri-axial gyroscopic chin sensor (Sunrise, Namur, Belgium) is a reliable surrogate of PES in patients with suspected obstructive sleep apnea (OSA). In-laboratory polysomnography (PSG) with PES and concurrent MM monitoring was performed. PSGs were scored manually using AASM 2012 rules. Data blocks (n=8042) were randomly sampled during normal breathing (NB), obstructive or central apnea/hypopnea (OA/OH/CA/CH), respiratory effort-related arousal (RERA), and mixed apnea (MxA). Analyses were evaluation of the similarity and linear correlation between PES and MM using the longest common subsequence (LCSS) algorithm and Pearson's coefficient; description of signal amplitudes; estimation of the marginal effect for crossing from NB to a respiratory disturbance for a given change in MM signal using a mixed linear-regression. Participants (n=38) had mild to severe OSA (median AH index 28.9/h; median arousal index 23.2/h). MM showed a high level of synchronization with concurrent PES signals. Distribution of MM amplitude differed significantly between event types: median (95% confidence interval) values of 0.60 (0.16-2.43) for CA, 0.83 (0.23-4.71) for CH, 1.93 (0.46-12.43) for MxA, 3.23 (0.72-18.09) for OH, and 6.42 (0.88-26.81) for OA. Mixed regression indicated that crossing from NB to central events would decrease MM signal amplitude by -1.23 (CH) and -2.04 (CA) units, while obstructive events would increase MM amplitude by +3.27 (OH) and +6.79 (OA) units (all p<10 ). In OSA patients, MM signals facilitated the measurement of specific levels of RE associated with obstructive, central or mixed apneas and/or hypopneas. A high degree of similarity was observed with the PES gold-standard signal.

Background: The capacity to diagnose obstructive sleep apnoea (OSA) must be expanded to meet an estimated disease burden of nearly one billion people worldwide. Validated alternatives to the gold standard polysomnography (PSG) will improve access to testing and treatment. This study aimed to evaluate the diagnosis of OSA, using measurements of mandibular movement (MM) combined with automated machine learning analysis, compared to in-home PSG. Methods: 40 suspected OSA underwent single overnight in-home sleep testing with PSG (Nox A1, ResMed, Australia) and simultaneous MM monitoring (Sunrise, Sunrise SA, Belgium). PSG recordings were manually analysed by two expert sleep centres (Grenoble and London); MM analysis was automated. The Obstructive Respiratory Disturbance Index calculated from the MM monitoring (MM-ORDI) was compared to the PSG (PSG-ORDI) using intraclass correlation coefficient and Bland-Altman analysis. Receiver operating characteristic curves (ROC) were constructed to optimise the diagnostic performance of the MM monitor at different PSG-ORDI thresholds (5, 15 and 30 events/hour). Results: 31 patients were included in the analysis (58% men; mean (SD) age: 48 (15) years; BMI: 30.4 (7.6) kg/m2). Good agreement was observed between MM-ORDI and PSG-ORDI (median bias 0.00; 95% CI -23.25 to +9.73 events/hour). However, for patients with no or mild OSA, MM monitoring overestimated disease severity (PSG-ORDI 5-15: MM-ORDI overestimation +3.70 (95% CI -0.53 to +18.32) events/hour). In patients with moderate-severe OSA, there was an underestimation (PSG-ORDI >15: MM-ORDI underestimation -8.70 (95% CI -28.46 to +4.01) events/hour). ROC optimal cut-off values for PSG-ORDI thresholds of 5, 15, 30 events/hour were: 9.53, 12.65 and 24.81 events/hour, respectively. These cut-off values yielded a sensitivity of 88, 100 and 79%, and a specificity of 100, 75, 96%. The positive predictive values were: 100, 80, 95% and the negative predictive values 89, 100, 82%, respectively. Conclusion: The diagnosis of OSA, using MM with machine learning analysis, is comparable to manually scored in-home PSG. Therefore, this novel monitor could be a convenient diagnostic tool that can easily be used in the patients’ own home.

Sleep bruxism (SBx) activity is classically identified by capturing masseter and/or temporalis masticatory muscles electromyographic activity (EMG-MMA) during in-laboratory polysomnography (PSG). We aimed to identify stereotypical mandibular jaw movements (MJM) in patients with SBx and to develop rhythmic masticatory muscles activities (RMMA) automatic detection using an artificial intelligence (AI) based approach. This was a prospective, observational study of 67 suspected obstructive sleep apnea (OSA) patients in whom PSG with masseter EMG was performed with simultaneous MJM recordings. The system used to collect MJM consisted of a small hardware device attached on the chin that communicates to a cloud-based infrastructure. An extreme gradient boosting (XGB) multiclass classifier was trained on 79,650 10-second epochs of MJM data from the 39 subjects with a history of SBx targeting 3 labels: RMMA episodes (n=1072), micro-arousals (n=1311), and MJM occurring at the breathing frequency (n=77,267). Validated on unseen data from 28 patients, the model showed a very good epoch-by-epoch agreement (Kappa = 0.799) and balanced accuracy of 86.6% was found for the MJM events when using RMMA standards. The RMMA episodes were detected with a sensitivity of 84.3%. Class-wise receiver operating characteristic (ROC) curve analysis confirmed the well-balanced performance of the classifier for RMMA (ROC area under the curve: 0.98, 95% confidence interval [CI] 0.97-0.99). There was good agreement between the MJM analytic model and manual EMG signal scoring of RMMA (median bias -0.80 events/h, 95% CI -9.77 to 2.85). SBx can be reliably identified, quantified, and characterized with MJM when subjected to automated analysis supported by AI technology.

Recent evidence suggests that activation of RhoA/Rho‐kinase accounts for systemic and pulmonary endothelial dysfunction in smokers with normal lung function. However, its role in patients with chronic obstructive pulmonary disease (COPD) has not yet been investigated. The aim of this study was to evaluate the regulation of RhoA/Rho‐kinase pathway and pulmonary endothelial dysfunction in patients with COPD. Pulmonary arteries were obtained from nonsmokers (control subjects) and patients with nonhypoxemic and hypoxemic COPD (n = 6–7/group). Endothelium‐dependent and ‐independent relaxations were evaluated by acetylcholine and sodium nitroprusside, respectively. Gene and protein expressions of endothelial nitric oxide synthase (eNOS) were measured by RT‐PCR, Western blot, and immunohistochemistry. Nitrate, cGMP, and endothelin‐1 (ET‐1) concentrations, as well as Rho‐kinase activity were measured by ELISA. Protein expressions of total RhoA and GTP‐RhoA were measured by Western blot and pull‐down assay, respectively. Endothelium‐dependent relaxation, and nitrate and cGMP levels were significantly reduced in pulmonary arteries of COPD patients as compared with control subjects. Conversely, activity of RhoA/Rho‐kinase was increased in pulmonary arteries of COPD patients as compared with control subjects. In patients with COPD, pulmonary endothelial dysfunction was related to the downregulation of eNOS activity and upregulation of RhoA/Rho‐kinase activity. e00105 This study showed the presence of endothelial dysfunction in pulmonary arteries of patients with COPD where downregulation of eNOS activity and upregulation of RhoA/Rho‐kinase activity also occurred. The interaction between RhoA/Rho‐kinase pathway and eNOS/NO/cGMP pathway in endothelial dysfunction in the pathogenesis of COPD needs to be further studied.

BackgroundRespiratory failure is a life-threatening and unpredictable complication of systemic sclerosis (SSc). A study was undertaken to assess the value of alveolar nitric oxide (NO) in predicting the risk of lung function deterioration leading to respiratory failure or death in patients with SSc.Methods105 patients with SSc were enrolled in this prospective cohort and were followed longitudinally over a 3-year period during which the risk of occurrence of deleterious events was analysed according to alveolar concentration (CAno), conducting airway output (J′awno) and fractional concentration (FEno0.05) of exhaled NO measured at inclusion. Comparison was made between each NO parameter to predict the occurrence of deleterious events, defined as a 10% decrease in total lung capacity or forced vital capacity from baseline, or death.ResultsThe area under the receiver operating characteristic curve of CAno to predict the occurrence of the combined events was 0.84 (95% CI 0.76 to 0.92; p<0.001), which was significantly higher than those of J′awno and FEno0.05 (p<0.001). A cut-off of CAno of 5.3 ppb had a sensitivity of 88% and a specificity of 62% for the prediction of the occurrence of combined events during follow-up, and was validated in an independent cohort of patients with SSc. Combined events occurred more frequently in patients whose CAno was >5.3 ppb. The adjusted HR for patients with CAno >5.3 ppb was 6.06 (95% CI 2.36 to 15.53; p<0.001). CAno accurately predicted the occurrence of combined events irrespective of forced vital capacity values or the presence of interstitial lung disease at baseline.ConclusionsIncreased CAno accurately identifies patients with SSc with a high risk of developing lung function deterioration and may help to initiate early appropriate treatment.

Background The patterns of mandibular movements (MM) during sleep can be used to identify increased respiratory effort periodic large-amplitude MM (LPM), and cortical arousals associated with “sharp” large-amplitude MM (SPM). We hypothesized that Cheyne Stokes breathing (CSB) may be identified by periodic abnormal MM patterns. The present study aims to evaluate prospectively the concordance between CSB detected by periodic MM and polysomnography (PSG) as gold-standard. The present study aims to evaluate prospectively the concordance between CSB detected by periodic MM and polysomnography (PSG) as gold-standard. Methods In 573 consecutive patients attending an in-laboratory PSG for suspected sleep disordered breathing (SDB), MM signals were acquired using magnetometry and scored manually while blinded from the PSG signal. Data analysis aimed to verify the concordance between the CSB identified by PSG and the presence of LPM or SPM. The data were randomly divided into training and validation sets (985 5-min segments/set) and concordance was evaluated using 2 classification models. Results In PSG, 22 patients (mean age ± SD: 65.9 ± 15.0 with a sex ratio M/F of 17/5) had CSB (mean central apnea hourly indice ± SD: 17.5 ± 6.2) from a total of 573 patients with suspected SDB. When tested on independent subset, the classification of CSB based on LPM and SPM is highly accurate (Balanced-accuracy = 0.922, sensitivity = 0.922, specificity = 0.921 and error-rate = 0.078). Logistic models based odds-ratios for CSB in presence of SPM or LPM were 172.43 (95% CI: 88.23–365.04; p  < 0.001) and 186.79 (95% CI: 100.48–379.93; p  < 0.001), respectively. Conclusion CSB in patients with sleep disordered breathing could be accurately identified by a simple magnetometer device recording mandibular movements.

The measure of fractional exhaled nitric oxide (FENO) in the airways is a useful tool to guide the diagnosis and titration of inhaled corticosteroids in patients with asthma. However, its role in diagnosis of allergic rhinitis (AR), especially in subjects with asthma, is not well established. To study the cutoff of nasal FENO in the diagnosis of subjects with AR and AR-asthma compared to age-matched subjects without AR or asthma and its correlations with the clinical and functional characteristics. The study was cross sectional and descriptive. Subjects were grouped into control subjects, AR, and AR-asthma, based on the inclusion criteria. Exhaled NO (nasal FENO, bronchial FENO, and alveolar concentration of NO) was measured by multiple flow electro-luminescence device. Six hundred twenty-eight subjects were included: 217 control subjects (children: n=98, 10±4 years; adults: n=119, 50±16 years), 168 subjects with AR (children: n=54, 10±3 years; adults: n=114, 49±15 years), and 243 subjects with AR-asthma (children: n=115, 10±3 years; adults: n=128, 51±14 years). Nasal peak inspiratory flow and peak expiratory flow were lower in subjects with AR and AR-asthma than in control subjects ( <0.01 and <0.01; and <0.05 and <0.01, respectively). Nasal FENO levels were significantly higher in subjects with AR and AR-asthma than in control subjects (1614±629 and 1686±614 ppb vs 582±161 ppb; <0.001 and <0.001, respectively). In subjects with AR non-asthma, the cutoffs of nasal FENO for those diagnosed with AR were 775 ppb in children, 799 ppb in adults, and 799 in the general population (sensitivity: 92.68%, 92.63%, and 92.65%, respectively; specificity: 91.67%, 95.00%, and 96.87%, respectively). In subjects with AR-asthma, the cutoffs of nasal FENO were higher, especially in asthma children (1458 ppb; sensitivity: 72.97% and specificity: 95.83%). Nasal FENO measurement is a useful technique for the diagnosis of AR in subjects with and without asthma.

Background and Objective. The concentration of exhaled nitric oxide (eNO), reflecting the activity of inducible NO synthase in airway epithelium, has been found to increase in patients with obstructive sleep apnea (OSA). This study aimed to measure eNO concentration in patients with suspected OSA and to correlate different eNO parameters with clinical and sleep apnea characteristics. Methods. In this cross-sectional study, all patients underwent in-lab overnight polysomnography (PSG) and eNO measurement using a method of multiple flow rates before and after PSG (pre- and post-PSG). Results. According to the result of PSG, 82 persons were divided into two groups: control subjects (n=30; 54±14 years) and patients with OSA defined as apnea-hypopnea index (AHI) ≥ 5/hour (n=52; 53±12 years). Body mass index (BMI) and neck and abdomen circumferences of OSA patients were significantly higher than those from control subjects. In OSA group, post-PSG alveolar NO concentration (CANO) (5.3±1.9 ppb) was significantly higher than pre-PSG CANO (4.0±1.7 ppb; P<0.001). Significant correlations have been found between CANO and AHI (P<0.001) and between CANO and nadir SpO2 (P<0.05). The daytime CANO value of more than 4.1 ppb can be used to screen symptomatic subjects for the presence of OSA with a high specificity of 93.3%. Conclusion. Our findings indicate CANO as a surrogate marker for OSA in persons with suggestive symptoms.

Given the high prevalence of obstructive sleep apnea (OSA), there is a need for simpler and automated diagnostic approaches. To evaluate whether mandibular movement (MM) monitoring during sleep coupled with an automated analysis by machine learning is appropriate for OSA diagnosis. Diagnostic study of adults undergoing overnight in-laboratory polysomnography (PSG) as the reference method compared with simultaneous MM monitoring at a sleep clinic in an academic institution (Sleep Laboratory, Centre Hospitalier Universitaire Université Catholique de Louvain Namur Site Sainte-Elisabeth, Namur, Belgium). Patients with suspected OSA were enrolled from July 5, 2017, to October 31, 2018. Obstructive sleep apnea diagnosis required either evoking signs or symptoms or related medical or psychiatric comorbidities coupled with a PSG-derived respiratory disturbance index (PSG-RDI) of at least 5 events/h. A PSG-RDI of at least 15 events/h satisfied the diagnosis criteria even in the absence of associated symptoms or comorbidities. Patients who did not meet these criteria were classified as not having OSA. Agreement analysis and diagnostic performance were assessed by Bland-Altman plot comparing PSG-RDI and the Sunrise system RDI (Sr-RDI) with diagnosis threshold optimization via receiver operating characteristic curves, allowing for evaluation of the device sensitivity and specificity in detecting OSA at 5 events/h and 15 events/h. Among 376 consecutive adults with suspected OSA, the mean (SD) age was 49.7 (13.2) years, the mean (SD) body mass index was 31.0 (7.1), and 207 (55.1%) were men. Reliable agreement was found between PSG-RDI and Sr-RDI in patients without OSA (n = 46; mean difference, 1.31; 95% CI, -1.05 to 3.66 events/h) and in patients with OSA with a PSG-RDI of at least 5 events/h with symptoms (n = 107; mean difference, -0.69; 95% CI, -3.77 to 2.38 events/h). An Sr-RDI underestimation of -11.74 (95% CI, -20.83 to -2.67) events/h in patients with OSA with a PSG-RDI of at least 15 events/h was detected and corrected by optimization of the Sunrise system diagnostic threshold. The Sr-RDI showed diagnostic capability, with areas under the receiver operating characteristic curve of 0.95 (95% CI, 0.92-0.96) and 0.93 (95% CI, 0.90-0.93) for corresponding PSG-RDIs of 5 events/h and 15 events/h, respectively. At the 2 optimal cutoffs of 7.63 events/h and 12.65 events/h, Sr-RDI had accuracy of 0.92 (95% CI, 0.90-0.94) and 0.88 (95% CI, 0.86-0.90) as well as posttest probabilities of 0.99 (95% CI, 0.99-0.99) and 0.89 (95% CI, 0.88-0.91) at PSG-RDIs of at least 5 events/h and at least 15 events/h, respectively, corresponding to positive likelihood ratios of 14.86 (95% CI, 9.86-30.12) and 5.63 (95% CI, 4.92-7.27), respectively. Automatic analysis of MM patterns provided reliable performance in RDI calculation. The use of this index in OSA diagnosis appears to be promising.