Sleep Apnea Physiological Burdens and Cardiovascular Morbidity and Mortality.

Rationale: Obstructive sleep apnea is characterized by frequent reductions in ventilation, leading to oxygen desaturations and/or arousals. Objectives: In this study, association of hypoxic burden with incident cardiovascular disease (CVD) was examined and compared with that of "ventilatory burden" and "arousal burden." Finally, we assessed the extent to which the ventilatory burden, visceral obesity, and lung function explain variations in hypoxic burden. Methods: Hypoxic, ventilatory, and arousal burdens were measured from baseline polysomnograms in the Multi-Ethnic Study of Atherosclerosis (MESA) and the Osteoporotic Fractures in Men (MrOS) studies. Ventilatory burden was defined as event-specific area under ventilation signal (mean normalized, area under the mean), and arousal burden was defined as the normalized cumulative duration of all arousals. The adjusted hazard ratios for incident CVD and mortality were calculated. Exploratory analyses quantified contributions to hypoxic burden of ventilatory burden, baseline oxygen saturation as measured by pulse oximetry, visceral obesity, and spirometry parameters. Measurements and Main Results: Hypoxic and ventilatory burdens were significantly associated with incident CVD (adjusted hazard ratio [95% confidence interval] per 1 SD increase in hypoxic burden: MESA, 1.45 [1.14, 1.84]; MrOS, 1.13 [1.02, 1.26]; ventilatory burden: MESA, 1.38 [1.11, 1.72]; MrOS, 1.12 [1.01, 1.25]), whereas arousal burden was not. Similar associations with mortality were also observed. Finally, 78% of variation in hypoxic burden was explained by ventilatory burden, whereas other factors explained only <2% of variation. Conclusions: Hypoxic and ventilatory burden predicted CVD morbidity and mortality in two population-based studies. Hypoxic burden is minimally affected by measures of adiposity and captures the risk attributable to ventilatory burden of obstructive sleep apnea rather than a tendency to desaturate.

Hypoxic burden to guide CPAP treatment allocation in patients with obstructive sleep apnoea: a post hoc study of the ISAACC trial.

BACKGROUND: Hypoxic burden (HB) has emerged as a strong predictor of cardiovascular risk in obstructive sleep apnoea (OSA). We aimed to assess the potential of HB to predict the cardiovascular benefit of treating OSA with continuous positive airway pressure (CPAP). METHODS: This was a post hoc analysis of the ISAACC trial (ClinicalTrials.gov: NCT01335087) including non-sleepy patients with acute coronary syndrome (ACS) diagnosed with OSA (apnoea-hypopnoea index ≥15 events·h-1) by respiratory polygraphy. Patients were randomised to CPAP or usual care and followed for a minimum of 1 year. HB was calculated as the total area under all automatically identified desaturations divided by total sleep time. Patients were categorised as having high or low baseline HB according to the median value (73.1%min·h-1). Multivariable Cox regression models were used to assess whether the effect of CPAP on the incidence of cardiovascular outcomes was dependent on the baseline HB level. RESULTS: The population (362 patients assigned to CPAP and 365 patients assigned to usual care) was middle-aged (mean age 59.7 years), overweight/obese and mostly male (84.5%). A significant interaction was found between the treatment arm and the HB categories. In the high HB group, CPAP treatment was associated with a significant reduction in the incidence of cardiovascular events (HR 0.57, 95% CI 0.34-0.96). In the low HB group, CPAP-treated patients exhibited a trend toward a higher risk of cardiovascular outcomes than those receiving usual care (HR 1.33, 95% CI 0.79-2.25). The differential effect of the treatment depending on the baseline HB level followed a dose-response relationship. CONCLUSION: In non-sleepy ACS patients with OSA, high HB levels were associated with a long-term protective effect of CPAP on cardiovascular prognosis.

Treatment of Cheyne-Stokes Respiration in Heart Failure with Adaptive Servo-Ventilation: An Integrative Model.

The SERVE-HF (Treatment of Predominant Central Sleep Apnea by Adaptive Servo Ventilation in Patients with Heart Failure) multicenter trial found a small but significant increase in all-cause and cardiovascular mortality in patients assigned to adaptive servo-ventilation (ASV) versus guideline-based medical treatment. To better understand the physiological underpinnings of this clinical outcome, we employ an integrative computer model to simulate congestive heart failure with Cheyne-Stokes respiration (CHF-CSR) in subjects with a broad spectrum of underlying pathogenetic mechanisms, as well as to determine the in silico changes in cardiopulmonary and autonomic physiology resulting from ASV. Our simulation results demonstrate that while the elimination of CSR through ASV can partially restore cardiorespiratory and autonomic physiology toward normality in the vast majority of CHF phenotypes, the degree of restoration can be highly variable, depending on the combination of CHF mechanisms in play. The group with the lowest left ventricular ejection fraction (LVEF) appears to be most vulnerable to the potentially adverse effects of ASV, but the level of pulmonary capillary wedge pressure (PCWP) plays an important role in determining the nature of these effects.

Physiological Determinants of Snore Loudness.

Rationale: The physiological factors modulating the severity of snoring have not been adequately described. Airway collapse or obstruction is generally the leading determinant of snore sound generation; however, we suspect that ventilatory drive is of equal importance. Objective: To determine the relationship between airway obstruction and ventilatory drive on snore loudness. Methods: In 40 patients with suspected or diagnosed obstructive sleep apnea (1-98 events/hr), airflow was recorded via a pneumotachometer attached to an oronasal mask, ventilatory drive was recorded using calibrated intraesophageal diaphragm electromyography, and snore loudness was recorded using a calibrated microphone attached over the trachea. "Obstruction" was taken as the ratio of ventilation to ventilatory drive and termed flow:drive, i.e., actual ventilation as a percentage of intended ventilation. Lower values reflect increased flow resistance. Using 165,063 breaths, mixed model analysis (quadratic regression) quantified snore loudness as a function of obstruction, ventilatory drive, and the presence of extreme obstruction (i.e., apneic occlusion). Results: In the presence of obstruction (flow:drive = 50%, i.e., doubled resistance), snore loudness increased markedly with increased drive (+3.4 [95% confidence interval, 3.3-3.5] dB per standard deviation [SD] change in ventilatory drive). However, the effect of drive was profoundly attenuated without obstruction (at flow:drive = 100%: +0.23 [0.08-0.39] dB per SD change in drive). Similarly, snore loudness increased with increasing obstruction exclusively in the presence of increased drive (at drive = 200% of eupnea: +2.1 [2.0-2.2] dB per SD change in obstruction; at eupneic drive: +0.14 [-0.08 to 0.28] dB per SD change). Further, snore loudness decreased substantially with extreme obstruction, defined as flow:drive <20% (-9.9 [-3.3 to -6.6] dB vs. unobstructed eupneic breathing). Conclusions: This study highlights that ventilatory drive, and not simply pharyngeal obstruction, modulates snore loudness. This new framework for characterizing the severity of snoring helps better understand the physiology of snoring and is important for the development of technologies that use snore sounds to characterize sleep-disordered breathing.

Treatment of Sleep Apnea and Reduction in Blood Pressure: The Role of Heart Rate Response and Hypoxic Burden.

BACKGROUND: Obstructive sleep apnea is associated with increased blood pressure (BP). Obstructive sleep apnea treatment reduces BP with substantial variability, not explained by the apnea-hypopnea index, partly due to inadequate characterization of obstructive sleep apnea's physiological consequences, such as oxygen desaturation, cardiac autonomic response, and suboptimal treatment efficacy. We sought to examine whether a high baseline heart rate response (ΔHR), a marker of high cardiovascular risk in obstructive sleep apnea, predicts a larger reduction in post-treatment systolic BP (SBP). Furthermore, we aimed to assess the extent to which a reduction in SBP is explained by a treatment-related reduction in hypoxic burden (HB). METHODS: ΔHR and HB were measured from pretreatment and posttreatment polygraphy, followed by a 24-hour BP assessment in 168 participants treated with continuous positive airway pressure or nocturnal supplemental oxygen from the HeartBEAT study (Heart Biomarker Evaluation in Apnea Treatment). Multiple linear regression models assessed whether high versus mid (reference) ΔHR predicted a larger reduction in SBP (primary outcome) and whether there was an association between treatment-related reductions in SBP and HB. RESULTS: A high versus mid ΔHR predicted improvement in SBP (adjusted estimate, 5.8 [95% CI, 1.0-10.5] mm Hg). Independently, a greater treatment-related reduction in HB was significantly associated with larger reductions in SBP (4.2 [95% CI, 0.9-7.5] mm Hg per 2 SD treatment-related reduction in HB). Participants with substantial versus minimal treatment-related reductions in HB had a 6.5 (95% CI, 2.5-10.4) mm Hg drop in SBP. CONCLUSIONS: A high ΔHR predicted a more favorable BP response to therapy. Furthermore, the magnitude of the reduction in BP was partly explained by a greater reduction in HB.

Hypoxic Burden Based on Automatically Identified Desaturations Is Associated with Adverse Health Outcomes.

Rationale: Recent studies have shown that sleep apnea-specific intermittent hypoxemia quantified by the hypoxic burden (HB) predicted cardiovascular disease (CVD)-related mortality in community-based and clinical cohorts. Calculation of HB is based on manual scoring of hypopneas and apneas, which is time-consuming and prone to interscorer variability. Objective: To validate a novel method to quantify the HB that is based on automatically scored desaturations. Methods: The sample included 5,655 middle-aged or older adults from the Sleep Heart Health Study (52.8% women; age, 63.2 ± 11.3 yr). The original HB method was based on a subject-specific search window obtained from an ensemble average of oxygen saturation signals (as measured by pulse oximetry) and synchronized with respect to the termination of scored respiratory events. In this study, however, the search window was obtained from ensemble average of oxygen saturation signals that synchronized with respect to the minimum of all automatically identified desaturations (⩾2% and other thresholds, including 3% and 4%, in sensitivity analyses). The time interval between the two maxima around the minimum saturation was defined as the search window. The oximetry-derived HB (HBOxi) was defined as the total area under all desaturation curves (restricted by the search window) divided by the total sleep time. Logistic and Cox regression models assessed the adjusted odds ratio (aOR)/hazard ratio of excessive daytime sleepiness (EDS), hypertension (HTN), and CVD mortality per 1-standard deviation increase in HBOxi after adjusting for several covariates and confounders. Results: The Spearman's rank correlation between HB (median [interquartile range], 34.4 [18.4-59.8] % min/h) and HBOxi (median [interquartile range], 34.5 [21.6-53.8] % min/h) was 0.81 (P < 0.001). Similar to HB, HBOxi was significantly associated with EDS (aOR [95% confidence interval (CI)], 1.17 [1.09-1.26] per standard deviation), HTN (aOR [95% CI], 1.13 [1.05-1.21]), and CVD mortality (adjusted hazard ratio [95% CI], 1.15 [1.01-1.30]) in fully adjusted models. Conclusions: The HBOxi was highly correlated with the HB based on manually scored apneas and hypopneas and was associated with EDS, HTN, and CVD mortality with similar effect sizes as previously reported. This method could be incorporated into wearable technology that accurately records oxygen saturation signals.

Effects of Ventilation-Perfusion Mismatch on Severity of Obstructive Sleep Apnea: A Modeling Study.

Plant gain quantifies the extent and rapidity with which arterial blood gases change following hypopneic or hyperpneic events. High plant gain, acting in concert with a highly collapsible upper airway and low arousal threshold, may contribute significantly towards increasing the severity of obstructive sleep apnea (OSA), even when controller gain is low. Elevated plant gain may be a manifestation of abnormal gas exchange resulting from ventilation-perfusion mismatch in the lungs. Using a mathematical model, we explore in this paper how ventilation-perfusion mismatch can affect plant gain, as well as the severity of OSA.

Siting analyses for water quality sampling in a catchment.

Pollution loads discharged from upstream development or human activities significantly degrade the water quality of a reservoir. The design of an appropriate water quality sampling network is therefore important for detecting potential pollution events and monitoring pollution trends. However, under a limited budgetary constraint, how to site an appropriate number of sampling stations is a challenging task. A previous study proposed a method applying the simulated annealing algorithm to design the sampling network based on three cost factors including the number of reaches, bank length, and subcatchment area. However, these factors are not directly related to the distribution of possible pollution. Thus, this study modified the method by considering three additional factors, i.e. total phosphorus, nitrogen, and sediment loads. The larger the possible load, the higher the probability of a pollution event may occur. The study area was the Derchi reservoir catchment in Taiwan. Pollution loads were derived from the AGNPS model with rainfall intensity estimated using the Thiessen method. Analyses for a network with various numbers of sampling sites were implemented. The results obtained based on varied cost factors were compared and discussed. With the three additional factors, the chosen sampling network is expected to properly detect pollution events and monitor pollution distribution and temporal trends.