Frequency of flow limitation using airflow shape

SLEEP ◽  
2021 ◽  
Author(s):  
Dwayne L Mann ◽  
Thomas Georgeson ◽  
Shane A Landry ◽  
Bradley A Edwards ◽  
Ali Azarbarzin ◽  
...  
Keyword(s):  
Sleep Disordered Breathing ◽  
Apnea Hypopnea Index ◽  
Flow Limitation ◽  
Automated Method ◽  
Visual Scoring ◽  
Obstructive Sleep ◽  
Ventilatory Drive ◽  
Ordinal Regression Model ◽  
Obstructive Sleep Disordered Breathing ◽  
Good Agreement

Abstract Study Objectives The presence of flow limitation during sleep is associated with adverse health consequences independent of obstructive sleep apnea (OSA) severity (apnea-hypopnea index, AHI), but remains extremely challenging to quantify. Here we present a unique library and an accompanying automated method that we apply to investigate flow limitation during sleep. Methods A library of 117,871 breaths (N=40 participants) were visually classified (certain flow limitation, possible flow limitation, normal) using airflow shape and physiological signals (ventilatory drive per intra-esophageal diaphragm EMG). An ordinal regression model was developed to quantify flow limitation certainty using flow-shape features (e.g. flattening, scooping); breath-by-breath agreement (Cohen’s ƙ) and overnight flow limitation frequency (R 2, %breaths in certain or possible categories during sleep) were compared against visual scoring. Subsequent application examined flow limitation frequency during arousals and stable breathing, and associations with ventilatory drive. Results The model (23 features) assessed flow limitation with good agreement (breath-by-breath ƙ=0.572, p<0.001) and minimal error (overnight flow limitation frequency R 2=0.86, error=7.2%). Flow limitation frequency was largely independent of AHI (R 2=0.16) and varied widely within individuals with OSA (74[32-95]%breaths, mean[range], AHI>15/hr, N=22). Flow limitation was unexpectedly frequent but variable during arousals (40[5-85]%breaths) and stable breathing (58[12-91]%breaths), and was associated with elevated ventilatory drive (R 2=0.26-0.29; R 2<0.01 AHI v. drive). Conclusions Our method enables quantification of flow limitation frequency, a key aspect of obstructive sleep-disordered breathing that is independent of the AHI and often unavailable. Flow limitation frequency varies widely between individuals, is prevalent during arousals and stable breathing, and reveals elevated ventilatory drive.

558 A Surface Electrode Adjacent to Vagal Nerve Stimulator Lead Can Aid in Characterizing VNS Mediated Sleep Disordered Breathing

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A220-A221
Author(s):  
Jeremy Chan ◽  
Joanna Wrede
Keyword(s):  
Sleep Disordered Breathing ◽  
Pediatric Patients ◽  
Refractory Epilepsy ◽  
Vagal Nerve ◽  
Apnea Hypopnea Index ◽  
Surface Electrode ◽  
Patients Âgés ◽  
Vagal Nerve Stimulator ◽  
Obstructive Sleep ◽  
Disordered Breathing

Abstract Introduction Vagal nerve stimulators (VNS) are a nonpharmacological treatment for patients with refractory epilepsy. The VNS can decrease seizure frequency by over 75% in 40% of pediatric patients with refractory epilepsy. An underrecognized side effect is sleep disordered breathing (SDB). The purpose of this study was to demonstrate how a sensor placed adjacent to the VNS lead can distinguish whether SDB is due to VNS discharge. Methods Five pediatric patients (ages: 5–8) with refractory epilepsy with VNS were referred to our sleep center for concern for SDB. Each patient underwent a polysomnogram (PSG) that included a standard PSG montage with a surface electrode placed adjacent to their left lateral neck to detect VNS discharge. VNS associated apnea hypopnea index (vAHI) was calculated by determining the number of hypopneas and obstructive apneas occurring during VNS discharge. Results Of the 5 patients, three met pediatric criteria for obstructive sleep apnea (OSA). Patient 1 had an obstructive AHI (oAHI) of 21.3 events/hr with a vAHI accounting for 79% of the total (16.8 events/hr), patient 2 had an oAHI of 16.6 events/hr with a vAHI accounting for 57% of the total (9.5 events/hr), and patient 3 had an oAHI of 1.9 events/hr with vAHI accounting for 68% of the total (1.3 events/hr). Because of these findings, the VNS settings of all 3 patients were changed with the goal of reducing SDB due to VNS discharge. Upon repeat PSG, patient 2 had reduced OSA with an oAHI of 3 events/hr, with no events associated with VNS discharge. The remaining 2 patients did not exhibit VNS associated SDB, however, both experienced increased respiratory rate during VNS discharge. Conclusion We demonstrated that a surface electrode adjacent to the VNS is able to temporally co-register VNS discharges and enabled us to directly correlate SDB to VNS stimulation in 3 patients with refractory epilepsy. Because of our findings, we titrated the VNS parameters in all 3 patients, with one showing resolution of VNS associated SDB on repeat PSG. We propose that an added surface electrode to detect VNS discharge be considered as standard practice in PSG studies of patients with VNS. Support (if any):

Upper Airway Effective Compliance during Wakefulness and Sleep in Obese Adolescents Studied via 2-Dimensional Dynamic MRI and Semi-automated Image Segmentation

2021 ◽  
Author(s):  
Kok Ren Choy ◽  
Sanghun Sin ◽  
Yubing Tong ◽  
Jayaram K. Udupa ◽  
Dirk M. Luchtenburg ◽  
...  
Keyword(s):  
Upper Airway ◽  
Dynamic Mri ◽  
Cross Sectional Area ◽  
Apnea Hypopnea Index ◽  
Morphological Operations ◽  
Sectional Area ◽  
Cross Sectional ◽  
Automated Method ◽  
Obstructive Sleep ◽  
Effective Compliance

Novel biomarkers of upper airway biomechanics may improve diagnosis of Obstructive Sleep Apnea Syndrome (OSAS). Upper airway effective compliance (EC), the slope of cross-sectional area versus pressure estimated using computational fluid dynamics (CFD), correlates with apnea-hypopnea index (AHI) and critical closing pressure (Pcrit). The study objectives are to develop a fast, simplified method for estimating EC using dynamic MRI and physiological measurements, and to explore the hypothesis that OSAS severity correlates with mechanical compliance during wakefulness and sleep. Five obese children with OSAS and five obese control subjects age 12-17 underwent anterior rhinomanometry, polysomnography and dynamic MRI with synchronized airflow measurement during wakefulness and sleep. Airway cross-section in retropalatal and retroglossal section images was segmented using a novel semi-automated method that uses optimized singular-value decomposition (SVD) image filtering and k-means clustering combined with morphological operations. Pressure was estimated using rhinomanometry Rohrer coefficients and flow rate, and EC calculated from the area-pressure slope during five normal breaths. Correlations between apnea-hypopnea index (AHI), EC, and cross-sectional area (CSA) change were calculated using Spearman rank correlation. The semi-automated method efficiently segmented the airway with average Dice Coefficient above 89% compared to expert manual segmentation. AHI correlated positively with EC at the retroglossal site during sleep (rs=0.74, p=0.014), and with change of EC from wake to sleep at the retroglossal site (rs=0.77, p=0.01). CSA change alone did not correlate significantly with AHI. EC, a mechanical biomarker which includes both CSA change and pressure variation, is a potential diagnostic biomarker for studying and managing OSAS.

Sign in / Sign up

Export Citation Format

Share Document