Philip I. Terrill

Quantifying the ventilatory control contribution to sleep apnoea using polysomnography.

Elevated loop gain, consequent to hypersensitive ventilatory control, is a primary nonanatomical cause of obstructive sleep apnoea (OSA) but it is not possible to quantify this in the clinic. Here we provide a novel method to estimate loop gain in OSA patients using routine clinical polysomnography alone. We use the concept that spontaneous ventilatory fluctuations due to apnoeas/hypopnoeas (disturbance) result in opposing changes in ventilatory drive (response) as determined by loop gain (response/disturbance). Fitting a simple ventilatory control model (including chemical and arousal contributions to ventilatory drive) to the ventilatory pattern of OSA reveals the underlying loop gain. Following mathematical-model validation, we critically tested our method in patients with OSA by comparison with a standard (continuous positive airway pressure (CPAP) drop method), and by assessing its ability to detect the known reduction in loop gain with oxygen and acetazolamide. Our method quantified loop gain from baseline polysomnography (correlation versus CPAP-estimated loop gain: n=28; r=0.63, p<0.001), detected the known reduction in loop gain with oxygen (n=11; mean±sem change in loop gain (ΔLG) −0.23±0.08, p=0.02) and acetazolamide (n=11; ΔLG −0.20±0.06, p=0.005), and predicted the OSA response to loop gain-lowering therapy. We validated a means to quantify the ventilatory control contribution to OSA pathogenesis using clinical polysomnography, enabling identification of likely responders to therapies targeting ventilatory control. Ventilatory instability can be measured by clinical polysomnography to guide nonanatomical sleep apnoea therapy http://ow.ly/AyXT3

Attractor Structure Discriminates Sleep States: Recurrence Plot Analysis Applied to Infant Breathing Patterns

Breathing patterns are characteristically different between infant active sleep (AS) and quiet sleep (QS), and statistical quantifications of interbreath interval (IBI) data have previously been used to discriminate between infant sleep states. It has also been identified that breathing patterns are governed by a nonlinear controller. This study aims to investigate whether nonlinear quantifications of infant IBI data are characteristically different between AS and QS, and whether they may be used to discriminate between these infant sleep states. Polysomnograms were obtained from 24 healthy infants at six months of age. Periods of AS and QS were identified, and IBI data extracted. Recurrence quantification analysis (RQA) was applied to each period, and recurrence calculated for a fixed radius in the range of 0-8 in steps of 0.02, and embedding dimensions of 4, 6, 8, and 16. When a threshold classifier was trained, the RQA variable recurrence was able to correctly classify 94.3% of periods in a test dataset. It was concluded that RQA of IBI data is able to accurately discriminate between infant sleep states. This is a promising step toward development of a minimal-channel automatic sleep state classification system.

Challenges and Emerging Technologies within the Field of Pediatric Actigraphy

Actigraphy as an objective measure of sleep and wakefulness in infants and children has gained popularity over the last 20 years. However, the field lacks published guidelines for sleep–wake identification within pediatric age groups. The scoring rules vary greatly and although sensitivity (sleep agreement with polysomnography) is usually high, a significant limitation remains in relation to specificity (wake agreement). Furthermore, accurate algorithm output and sleep–wake summaries usually require prior entry from daily logs of sleep–wake periods and artifact-related information (e.g., non-wear time), involving significant parent co-operation. Scoring criteria for daytime naps remains an unexplored area. Many of the problems facing accuracy of measurement are inherent within the field of actigraphy itself, particularly where sleep periods containing significant movements are erroneously classified as wake, and within quiet wakefulness when no movements are detected, erroneously classified as sleep. We discuss the challenges of actigraphy for pediatric sleep, briefly describe the technical basis and consider a number of technological approaches that may facilitate improved classification of errors in sleep–wake discrimination.

Development of a continuous multisite accelerometry system for studying movements during sleep

Actigraphy has proven to be a useful tool in the assessment of circadian rhythms, and more recently in the automatic staging of sleep and wake states. Whilst accuracy of commercial systems appears good over 24 hour periods, the sensitivity of detecting wake during time in bed is poor. One possible explanation for these poor results is the technical limitations of currently available commercial actigraphs. In particular, raw data is generally not available to the user. Instead, activity counts for each epoch (typically between 10–60secs) are calculated using various algorithms, from which sleep state is identified. Consequently morphologically different movements observed during sleep and wake states may not be detected as such. In this paper, the development of a continuous multisite, accelerometry system (CMAS) is described. Initial results, comparing data collected using a commercial actigraph (Actiwatch- Mini Motionlogger), and the continuous multisite accelerometry system are presented. The CMAS is able to differentiate brief movement “twitches” from postural changes.

Nocturnal oxygen saturation profiles of healthy term infants

Objective Pulse oximetry is used extensively in hospital and home settings to measure arterial oxygen saturation (SpO2). Interpretation of the trend and range of SpO2 values observed in infants is currently limited by a lack of reference ranges using current devices, and may be augmented by development of cumulative frequency (CF) reference-curves. This study aims to provide reference oxygen saturation values from a prospective longitudinal cohort of healthy infants. Design Prospective longitudinal cohort study. Setting Sleep-laboratory. Patients 34 healthy term infants were enrolled, and studied at 2 weeks, 3, 6, 12 and 24 months of age (N=30, 25, 27, 26, 20, respectively). Interventions Full overnight polysomnography, including 2 s averaging pulse oximetry (Masimo Radical). Main outcome measurements Summary SpO2 statistics (mean, median, 5th and 10th percentiles) and SpO2 CF plots were calculated for each recording. CF reference-curves were then generated for each study age. Analyses were repeated with sleep-state stratifications and inclusion of manual artefact removal. Results Median nocturnal SpO2 values ranged between 98% and 99% over the first 2 years of life and the CF reference-curves shift right by 1% between 2 weeks and 3 months. CF reference-curves did not change with manual artefact removal during sleep and did not vary between rapid eye movement (REM) and non-REM sleep. Manual artefact removal did significantly change summary statistics and CF reference-curves during wake. Conclusions SpO2 CF curves provide an intuitive visual tool for evaluating whether an individuals nocturnal SpO2 distribution falls within the range of healthy age-matched infants, thereby complementing summary statistics in the interpretation of extended oximetry recordings in infants.

Phenotyping Pharyngeal Pathophysiology using Polysomnography in Patients with Obstructive Sleep Apnea

Rationale: Therapies for obstructive sleep apnea (OSA) could be administered on the basis of a patients own phenotypic causes (“traits”) if a clinically applicable approach were available. Objectives: Here we aimed to provide a means to quantify two key contributors to OSA—pharyngeal collapsibility and compensatory muscle responsiveness—that is applicable to diagnostic polysomnography. Methods: Based on physiological definitions, pharyngeal collapsibility determines the ventilation at normal (eupneic) ventilatory drive during sleep, and pharyngeal compensation determines the rise in ventilation accompanying a rising ventilatory drive. Thus, measuring ventilation and ventilatory drive (e.g., during spontaneous cyclic events) should reveal a patients phenotypic traits without specialized intervention. We demonstrate this concept in patients with OSA (N = 29), using a novel automated noninvasive method to estimate ventilatory drive (polysomnographic method) and using “gold standard” ventilatory drive (intraesophageal diaphragm EMG) for comparison. Specialized physiological measurements using continuous positive airway pressure manipulation were employed for further comparison. The validity of nasal pressure as a ventilation surrogate was also tested (N = 11). Measurements and Main Results: Polysomnography‐derived collapsibility and compensation estimates correlated favorably with those quantified using gold standard ventilatory drive (R = 0.83, P < 0.0001; and R = 0.76, P < 0.0001; respectively) and using continuous positive airway pressure manipulation (R = 0.67, P < 0.0001; and R = 0.64, P < 0.001; respectively). Polysomnographic estimates effectively stratified patients into high versus low subgroups (accuracy, 69‐86% vs. ventilatory drive measures; P < 0.05). Traits were near‐identical using nasal pressure versus pneumotach (N = 11, R ≥ 0.98, both traits; P < 0.001). Conclusions: Phenotypes of pharyngeal dysfunction in OSA are evident from spontaneous changes in ventilation and ventilatory drive during sleep, enabling noninvasive phenotyping in the clinic. Our approach may facilitate precision therapeutic interventions for OSA.

Loop Gain Predicts the Response to Upper Airway Surgery in Patients With Obstructive Sleep Apnea

Study Objectives Upper airway surgery is often recommended to treat patients with obstructive sleep apnea (OSA) who cannot tolerate continuous positive airways pressure. However, the response to surgery is variable, potentially because it does not improve the nonanatomical factors (ie, loop gain [LG] and arousal threshold) causing OSA. Measuring these traits clinically might predict responses to surgery. Our primary objective was to test the value of LG and arousal threshold to predict surgical success defined as 50% reduction in apnea-hypopnea index (AHI) and AHI <10 events/hour post surgery. Methods We retrospectively analyzed data from patients who underwent upper airway surgery for OSA (n = 46). Clinical estimates of LG and arousal threshold were calculated from routine polysomnographic recordings presurgery and postsurgery (median of 124 [91-170] days follow-up). Results Surgery reduced both the AHI (39.1 ± 4.2 vs. 26.5 ± 3.6 events/hour; p < .005) and estimated arousal threshold (-14.8 [-22.9 to -10.2] vs. -9.4 [-14.5 to -6.0] cmH2O) but did not alter LG (0.45 ± 0.08 vs. 0.45 ± 0.12; p = .278). Responders to surgery had a lower baseline LG (0.38 ± 0.02 vs. 0.48 ± 0.01, p < .05) and were younger (31.0 [27.3-42.5] vs. 43.0 [33.0-55.3] years, p < .05) than nonresponders. Lower LG remained a significant predictor of surgical success after controlling for covariates (logistic regression p = .018; receiver operating characteristic area under curve = 0.80). Conclusions Our study provides proof-of-principle that upper airway surgery most effectively resolves OSA in patients with lower LG. Predicting the failure of surgical treatment, consequent to less stable ventilatory control (elevated LG), can be achieved in the clinic and may facilitate avoidance of surgical failures.

Pediatric Obstructive Sleep Apnea assessment using pulse oximetry and dual RIP bands

The diagnosis of Obstructive Sleep Apnea (OSA) in children presents a challenging diagnostic problem given the high prevalence (2–3%), the resource intensity of the overnight polysomnography investigation, and the realisation that OSA poses a serious threat to the healthy growth and development of children. Previous attempts to develop OSA diagnostic systems using home pulse oximetry studies have failed to meet the accuracy requirements - particularly the low false normal rate (FNR) - required for a pre-PSG screening test. Thus the aim of this study is to investigate the feasibility of an OSA severity diagnostic system based on both oximetry and dual respiratory inductance plethysmography (RIP) bands. A total of 90 PSG studies (30 each of normal, mild/moderate and severe OSA) were retrospectively analyzed. Quantifications of oxygen desaturations (S), respiratory events (E) and heart rate arousals (A) were calculated and extracted and an empirical rule-based SEA classifier model for normal, mild/moderate and severe OSA defined and developed. In addition, an automated classifier using a decision tree algorithm was trained and tested using a 10-fold cross-validation. The empirical classification system showed a correct classification rate (CCR) of 0.83 (Cohens Kappa κ=0.81, FNR=0.08), and the decision tree classifier achieved a CCR of 0.79 (κ=0.73, FNR=0.08) when compared to gold standard PSG assessment. The relatively high CCR, and low FNR indicate that a OSA severity system based on dual RIP and oximetry is feasible for application as a pre-PSG screening tool.

Developing robust recurrence plot analysis techniques for investigating infant respiratory patterns

Recurrence plot analysis is a useful non-linear analysis tool. There are still no well formalised procedures for carrying out this analysis on measured physiological data, and systemising analysis is often difficult. In this paper, the recurrence based embedding is compared to radius based embedding by studying a logistic attractor and measured breathing data collected from sleeping human infants. Recurrence based embedding appears to be a more robust method of carrying out a recurrence analysis when attractor size is likely to be different between datasets. In the infant breathing data, the radius measure calculated at a fixed recurrence, scaled by average respiratory period, allows the accurate discrimination of active sleep from quiet sleep states (AUC=0.975, Sn=098, Sp=0.94).

Dynamic loop gain increases upon adopting the supine body position during sleep in patients with obstructive sleep apnoea

Obstructive sleep apnoea (OSA) is typically worse in the supine versus lateral sleeping position. One potential factor driving this observation is a decrease in lung volume in the supine position which is expected by theory to increase a key OSA pathogenic factor: dynamic ventilatory control instability (i.e. loop gain). We aimed to quantify dynamic loop gain in OSA patients in the lateral and supine positions, and to explore the relationship between change in dynamic loop gain and change in lung volume with position.