A novel quantitative arousal-associated EEG-metric to predict severity of respiratory distress in obstructive sleep apnea patients

Respiratory arousals (RA) on polysomnography (PSG) are an important predictor of obstructive sleep apnea (OSA) disease severity. Additionally, recent reports suggest that more global indices of desaturation such as the hypoxic burden, namely the area under the curve (AUC) of the oxygen saturation (SaO2) PSG trace may better depict the desaturation burden in OSA. Here we investigated possible associations between a new metric, namely the AUC of the respiratory arousal electroencephalographic (EEG) recording, and already established parameters as the apnea/hypopnea index (AHI), arousal index and hypoxic burden in patients with OSA. In this data-driven study, polysomnographic data from 102 patients with OSAS were assessed (32 female; 70 male; mean value of age: 52 years; mean value of Body-Mass-Index-BMI: 31 kg/m2). The marked arousals from the pooled EEG signal (C3 and C4) were smoothed and the AUC was estimated. We used a support vector regressor (SVR) analysis to predict AHI, arousal index and hypoxic burden as captured by the PSG. The SVR with the arousal-AUC metric could quite reliably predict the AHI with a high correlation coefficient (0,58 in the training set, 0,65 in the testing set and 0,64 overall), as well as the hypoxic burden (0,62 in the training set, 0,58 in the testing set and 0,59 overall) and the arousal index (0,58 in the training set, 0,67 in the testing set and 0,66 overall). This novel arousal-AUC metric may predict AHI, hypoxic burden and arousal index with a quite high correlation coefficient and therefore could be used as an additional quantitative surrogate marker in the description of obstructive sleep apnea disease severity

Sleep stage classification using spectral analyses and support vector machine algorithm on C3- and C4-EEG signals [Abstract]

Introduction Sleep stage classification currently relies largely on visual classification methods. We tested a new pipeline for automated offline classification based upon power spectrum at six different frequency bands. The pipeline allowed sleep stage classification and provided whole-night visualization of sleep stages. Materials and methods 102 subjects (69 male; 53.74 ± 12.4 years) underwent full-night polysomnography. The recording system included C3- and C4-EEG channels. All signals were measured at sampling rate of 200 Hz. Four epochs (30 seconds each) of each sleep stage (N1, N2, N3, REM, awake) were marked in the visually scored recordings of each one of the 102 patients. Scoring of sleep stages was performed according to AASM 2007-criteria. In total 408 epochs for each sleep stage were included in the sleep stage classification analyses. Recordings of all these epochs were fed into the pipeline to estimate the power spectrum at six different frequency bands, namely from very low frequency (VLF, 0.1-1 Hz) to gamma frequency (30-50 Hz). The power spectrum was measured with a method called multitaper method. In this method the spectrum is estimated by multiplying the data with K windows (i.e tapers).The estimated parameters were given as input to the support vector machine (SVM) algorithm to classify the five different sleep stages based on the mean power amplitude estimated from six different frequency bands. The SVM algorithm was trained with 51 subjects and the testing was done with the other 51 subjects. In order to avoid bias of the training dataset, a 10-fold cross validation was additionally done to check the performance of the SVM algorithm Results The estimated testing accuracy of prediction of the sleep stages was 84.1% for stage N1 using the mean power amplitude from the delta frequency band. Accuracy was 67.8% for stage N2 from the delta frequency band and 74.9% for stage N3 from the VLF. Accuracy was 79.7% for REM stage from the delta frequency band and 84,8% for the wake stage from the theta frequency band. Conclusions We were able to successfully classify the sleep stages using the mean power amplitude at six different frequency bands separately and achieved up to 85% accuracy using the electrophysiological EEG signals. The delta and theta frequency bands gave the best accuracy of classification among all sleep stages

EEG-EMG-coherence in SDB patients with utilization of a support vector machine-algorithm [Poster Abstract]

Background We investigated whether the EEG-EMG-coherence allows a differentiation between patients with sleep-disordered breathing (SDB) without OSA and SDB-patients with mild, moderate or severe OSA. Methods Polysomnographic recordings of 102 patients with SDB (33 female; age: 53,± 12,4 years) were analyzed with the multitaper coherence method (MTM). Recordings contained 2 EEG-channels (C3 and C4) and a chin EMG-channel for one night. Four epochs (each 30 seconds, classified manually by AASM 2007 criteria) of each sleep stage were marked (1632 epochs in total), which were included in the classification analysis. The collected data sets were supplied to the support vector machine (SVM) algorithm to classify OSA severity. Twenty patients had a mild (RDI ≥10/h and < 15/h), 30 patients had a moderate (RDI ≥15/h and < 30/h) and 27 patients had a severe OSA (RDI ≥30/h). 25 patients had a RDI < 10/h. The AUC (area under the curve) value was calculated for each receiver operator curve (ROC) curve. Results EEG-EMG coherence was able to distinguish between the SDB-patients without OSA and SDB-patients with OSA in each of the 3 severity groups using an SVM algorithm. In mild OSA, the AUC was 0.616 (p = 0.024), in moderate OSA the AUC was 0.659 (p = 0.003), and in severe OSA the AUC was 0.823 (p < 0.001). Conclusions SDB patients with OSA can be differentiated from SDB patients without OSA on the basis of EEG-EMG coherence by using the Multitaper Coherence Method (MTM) and SVM algorithm

The role of structured reporting and structured operation planning in functional endoscopic sinus surgery

Computed tomography (CT) scans represent the gold standard in the planning of functional endoscopic sinus surgeries (FESS). Yet, radiologists and otolaryngologists have different perspectives on these scans. In general, residents often struggle with aspects involved in both reporting and operation planning. The aim of this study was to compare the completeness of structured reports (SR) of preoperative CT images and structured operation planning (SOP) to conventional reports (CR) and conventional operation planning (COP) to potentially improve future treatment decisions on an individual level. In total, 30 preoperative CT scans obtained for surgical planning of patients scheduled for FESS were evaluated using SR and CR by radiology residents. Subsequently, otolaryngology residents performed a COP using free texts and a SOP using a specific template. All radiology reports and operation plannings were evaluated by two experienced FESS surgeons regarding their completeness for surgical planning. User satisfaction of otolaryngology residents was assessed by using visual analogue scales. Overall radiology report completeness was significantly higher using SRs regarding surgically important structures compared to CRs (84.4 vs. 22.0%, p<0.001). SOPs produced significantly higher completeness ratings (97% vs. 39.4%, p<0.001) regarding pathologies and anatomical variances. Moreover, time efficiency was not significantly impaired by implementation of SR (148 s vs. 160 s, p = 0.61) and user satisfaction was significantly higher for SOP (VAS 8.1 vs. 4.1, p<0.001). Implementation of SR and SOP results in a significantly increased completeness of radiology reports and operation planning for FESS. Consequently, the combination of both facilitates surgical planning and may decrease potential risks during FESS

EEG-EMG-Kohärenz bei Rhonchopathie-Patienten unter Verwendung eines Support Vector Machine-Algorithmus [Abstract]

Einleitung: Untersucht wurde, ob die EEG-EMG-Kohärenz die Differenzierung zwischen Rhonchopathie-Patienten ohne obstruktive Schlafapnoe (OSA) und Patienten mit OSA eines gering-, mäßig- oder schwergradigen Ausmaßes erlaubt. Methoden: Polysomnographische Aufzeichnungen von 102 Rhonchopathie-Patienten (33 weiblich Alter: 53,74 ± 12,4 Jahre) wurden mit der Multitaper-Kohärenz-Methodik (MTM) analysiert. Die Aufnahmen umfassten u.a. die C3- und C4-EEG-Kanäle und einen Kinn-EMG-Kanal. Vier Epochen (30 Sekunden, manuell nach AASM 2007-Kriterien klassifiziert) jedes Schlafstadiums wurden markiert (insgesamt 1632 Epochen), die in die Klassifikation-Analysen aufgenommen wurden. Die erhobenen Datensätze wurden als Input für den support vector machine (SVM) – Algorithmus eingegeben, um die 4 verschiedenen OSA-Schweregrade zu klassifizieren. Zwanzig Patienten hatten an einer milden (RDI ≥10/h und < 15/h), 30 Patienten an einer mäßigen (RDI ≥15/h und < 30/h) und 27 Patienten an einer schweren OSA (RDI ≥30/h) gelitten. 25 Patienten hatten ein RDI < 10/h. Der AUC (area under the curve)-Wert wurde bei jeder ROC (receiver operator curve)-Kurve errechnet. Ergebnisse: Mithilfe der EEG-EMG-Kohärenz konnte unter Verwendung eines SVM-Algorithmus zwischen den Rhonchopathie-Patienten ohne OSA und den OSA-Patienten der jeweiligen 3 Schweregrad-Gruppen unterschieden werden. Bei milder OSA lag der AUC-Wert bei 0.616 (p = 0.024), bei mäßiger OSA lag der AUC-Wert bei 0.659 (p = 0.003) und bei schwerer OSA lag der AUC-Wert bei 0.823 (p < 0.001). Schlussfolgerung: Rhonchopathie-Patienten mit OSA lassen sich von Rhonchopathie-Patienten ohne OSA allein durch die EEG-EMG-Kohärenz der Polysomnografie mithilfe der Multitaper-Kohärenz -Methodik (MTM) unter Verwendung eines SVM-Algorithmus unterscheiden

Positive airway pressure (PAP) treatment reduces glycated hemoglobin (HbA1c) levels in obstructive sleep apnea patients with concomitant weight loss: Longitudinal data from the ESADA

Patients with obstructive sleep apnea (OSA) are at increased risk of developing metabolic disease such as diabetes. The effects of positive airway pressure on glycemic control are contradictory. We therefore evaluated the change in glycated hemoglobin (HbA1c) in a large cohort of OSA patients after long-term treatment with positive airway pressure. HbA1c levels were assessed in a subsample of the European Sleep Apnea Database [n=1608] at baseline and at long-term follow up with positive airway pressure therapy (mean 378.9±423.0 days). In a regression analysis, treatment response was controlled for important confounders. Overall, HbA1c decreased from 5.98±1.01% to 5.93±0.98% (p=0.001). Patient subgroups with a more pronounced HbA1c response included patients with diabetes (−0.15±1.02, p=0.019), those with severe OSA baseline (−0.10±0.68, p=0.005), those with morbid obesity (−0.20±0.81, p&lt;0.001). The strongest HbA1c reduction was observed in patients with a concomitant weight reduction &gt;5 kilos (−0.38±0.99, p&lt;0.001). In robust regression analysis, severe OSA (p=0.038) and morbid obesity (p=0.005) at baseline, and weight reduction &gt;5 kilos (p&lt;0.001) during follow up were independently associated with a reduction of HbA1c following PAP treatment. In contrast, PAP treatment alone without weight reduction was not associated with significant Hb1Ac reduction. In conclusion, positive airway pressure therapy is associated with HbA1c reduction in patients with severe OSA, in morbidly obese patients. and most obviously in those with significant weight lost during the follow-up. Our study underlines the importance to combine positive airway pressure use with adjustments in lifestyle to substantially modify metabolic complications in OSA

Arterial bicarbonate is associated with hypoxic burden and uncontrolled hypertension in obstructive sleep apnea - The ESADA cohort

Objective: Blood bicarbonate concentration plays an important role for obstructive sleep apnea (OSA) patients to maintain acid-base balance. We investigated the association between arterial standard bicarbonate ([HCO3-]) and nocturnal hypoxia as well as comorbid hypertension in OSA. Methods: A cross-sectional analysis of 3329 patients in the European Sleep Apnea Database (ESADA) was performed. Arterial blood gas analysis and lung function test were performed in conjunction with polysomnographic sleep studies. The 4% oxygen desaturation index (ODI), mean and minimum oxygen saturation (SpO2), and percentage of time with SpO2 below 90% (T90%) were used to reflect nocturnal hypoxic burden. Arterial hypertension was defined as a physician diagnosis of hypertension with ongoing antihypertensive medication. Hypertensive patients with SBP/DBP below or above 140/90 mmHg were classified as controlled-, uncontrolled hypertension, respectively. Results: The [HCO3-] level was normal in most patients (average 24.0 ± 2.5 mmol/L). ODI, T90% increased whereas mean and minimum SpO2 decreased across [HCO3-] tertiles (ANOVA, p = 0.030, &lt;0.001, &lt;0.001, and &lt;0.001, respectively). [HCO3-] was independently associated with ODI, mean SpO2, minimum SpO2, and T90% after adjusting for confounders (β value [95%CI]: 1.21 [0.88–1.54], −0.16 [-0.20 to −0.11], −0.51 [-0.64 to −0.37], 1.76 [1.48–2.04], respectively, all p &lt; 0.001). 1 mmol/L elevation of [HCO3-] was associated with a 4% increased odds of uncontrolled hypertension (OR: 1.04 [1.01–1.08], p = 0.013). Conclusion: We first demonstrated an independent association between [HCO3-] and nocturnal hypoxic burden as well as uncontrolled hypertension in OSA patients. Bicarbonate levels as an adjunctive measure provide insight into the pathophysiology of hypertension in OSA

Management of obstructive sleep apnea in Europe-A 10-year follow-up

Objective: In 2010, a questionnaire-based study on obstructive sleep apnea (OSA) management in Europe identified differences regarding reimbursement, sleep specialist qualification, and titration procedures. Now, 10 years later, a follow-up study was conducted as part of the ESADA (European Sleep Apnea Database) network to explore the development of OSA management over time.Methods: The 2010 questionnaire including questions on sleep diagnostic, reimbursement, treatment, and certification was updated with questions on telemedicine and distributed to European Sleep Centers to reflect European OSA management practice.Results: 26 countries (36 sleep centers) participated, representing 20 ESADA and 6 non-ESADA countries. All 21 countries from the 2010 survey participated. In 2010, OSA diagnostic procedures were performed mainly by specialized physicians (86%), whereas now mainly by certified sleep specialists and specialized physicians (69%). Treatment and titration procedures are currently quite homogenous, with a strong trend towards more Autotitrating Positive Airway Pressure treatment (in hospital 73%, at home 62%). From 2010 to 2020, home sleep apnea testing use increased (76%-89%) and polysomnography as sole diagnostic procedure decreased (24%-12%). Availability of a sleep specialist qualification increased (52%-65%) as well as the number of certified polysomnography scorers (certified physicians: 36%-79%; certified technicians: 20%-62%). Telemedicine, not surveyed in 2010, is now in 2020 used in diagnostics (8%), treatment (50%), and follow-up (73%). Conclusion: In the past decade, formal qualification of sleep center personnel increased, OSA diagnostic and treatment procedures shifted towards a more automatic approach, and telemedicine became more prominent.(c) 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)