Review and perspective on sleep-disordered breathing research and translation to clinics.

Sleep-disordered breathing, ranging from habitual snoring to severe obstructive sleep apnea, is a prevalent public health issue. Despite rising interest in sleep and awareness of sleep disorders, sleep research and diagnostic practices still rely on outdated metrics and laborious methods reducing the diagnostic capacity and preventing timely diagnosis and treatment. Consequently, a significant portion of individuals affected by sleep-disordered breathing remain undiagnosed or are misdiagnosed. Taking advantage of state-of-the-art scientific, technological, and computational advances could be an effective way to optimize the diagnostic and treatment pathways. We discuss state-of-the-art multidisciplinary research, review the shortcomings in the current practices of SDB diagnosis and management in adult populations, and provide possible future directions. We critically review the opportunities for modern data analysis methods and machine learning to combine multimodal information, provide a perspective on the pitfalls of big data analysis, and discuss approaches for developing analysis strategies that overcome current limitations. We argue that large-scale and multidisciplinary collaborative efforts based on clinical, scientific, and technical knowledge and rigorous clinical validation and implementation of the outcomes in practice are needed to move the research of sleep-disordered breathing forward, thus increasing the quality of diagnostics and treatment.

Modification of Endotypic Traits in OSA by the Carbonic Anhydrase Inhibitor Sulthiame.

BACKGROUND: The carbonic anhydrase inhibitor sulthiame reduces OSA severity, increases overnight oxygenation, and improves sleep quality. Insights into how sulthiame modulates OSA pathophysiologic features (endotypic traits) adds to our understanding of the breathing disorder itself, as well as the effects of carbonic anhydrases in respiratory regulation. RESEARCH QUESTION: How does sulthiame treatment modify endotypic traits in OSA? STUDY DESIGN AND METHODS: Per-protocol tertiary analysis of a randomized controlled trial with the inclusion criteria as follow: BMI, ≥ 20 to ≤ 35 kg/m2; age, 18-75 years; apnea-hypopnea index (AHI) ≥ 15 events/h; Epworth sleepiness scale score, ≥ 6; as well as nonacceptance or nontolerance of positive airway pressure treatment. Patients were randomized to receive placebo (n = 22), sulthiame 200 mg (n = 12), or sulthiame 400 mg (n = 24) during 4 weeks of treatment. Polysomnography was applied twice at baseline and follow-up. Endotypic traits were determined from polysomnography tracings (PUPBeta). Sulthiame plasma concentration was analyzed. Differences from baseline to follow-up (Δs) were analyzed with the analysis of covariance or Kruskal-Wallis H test and Pearson (r) or Spearman correlations (rs). RESULTS: Sulthiame (200-mg and 400-mg groups) consistently reduced loop gain (response to a 1-cycle/min disturbance, LG1; mean, -0.16 [95% CI, -0.18 to -0.13]; P < .05) in addition to increased ventilation at lowest decile of ventilatory drive (Vmin; median, +12 [95% CI, 4-20]; P < .05) and median ventilation at eupneic ventilatory drive (Vpassive; median, +4 [95% CI, 0-5]; P < .05). ΔLG1 correlated with ΔAHI percentage (200 mg: r = 0.65; P < .05). Vmin and Vpassive correlated with ΔAHI (all sulthiame: rs = -0.59 and rs = -0.65; P < .05 for all). The reduction of LG1 was seen already in the lower sulthiame concentration range, whereas changes in Vmin peaked in the higher range. INTERPRETATION: The effect of sulthiame in OSA may be explained by a reduction of ventilatory instability (LG1) as well as upper airway collapsibility (Vmin and Vpassive). TRIAL REGISTRY: European Union Drug Regulating Authorities Clinical Trials Database; No.: EudraCT 2017-004767-13; URL: https://www.clinicaltrialsregister.eu.

Night-to-Night Variability of Polysomnography-Derived Physiologic Endotypic Traits in Patients With Moderate to Severe OSA.

BACKGROUND: Emerging data suggest that determination of physiologic endotypic traits (eg, loop gain) may enable precision medicine in OSA. RESEARCH QUESTION: Does a single-night assessment of polysomnography-derived endotypic traits provide reliable estimates in moderate to severe OSA? STUDY DESIGN AND METHODS: Two consecutive in-lab polysomnography tests from a clinical trial (n = 67; male, 69%; mean ± SD age, 61 ± 10 years; apnea-hypopnea index [AHI] 53 ± 22 events/h) were used for the reliability analysis. Endotypic traits, reflecting upper airway collapsibility (ventilation at eupneic drive [Vpassive]), upper airway dilator muscle tone (ventilation at the arousal threshold [Vactive]), loop gain (stability of ventilatory control, LG1), and arousal threshold (ArTh) were determined. Reliability was expressed as an intraclass correlation coefficient (ICC). Minimal detectable differences (MDDs) were computed to provide an estimate of maximum spontaneous variability. Further assessment across four repeated polysomnography tests was performed in a subcohort (n = 22). RESULTS: Reliability of endotypic traits between the two consecutive nights was moderate to good (ICC: Vpassive = 0.82, Vactive = 0.76, LG1 = 0.72, ArTh = 0.83). Variability in AHI, but not in body position or in sleep stages, was associated with fluctuations in Vpassive and Vactive (r = -0.49 and r = -0.41, respectively; P < .001 for both). MDDs for single-night assessments were: Vpassive = 22, Vactive = 34, LG1 = 0.17, and ArTh = 21. Multiple assessments (mean of two nights, n = 22) further reduced MDDs by approximately 20% to 30%. INTERPRETATION: Endotypic trait analysis using a single standard polysomnography shows acceptable reliability and reproducibility in patients with moderate to severe OSA. The reported MDDs of endotypic traits may facilitate the quantification of relevant changes and may guide future evaluation of interventions in OSA.

Beyond the AHI-pulse wave analysis during sleep for recognition of cardiovascular risk in sleep apnea patients.

Recent evidence supports the use of pulse wave analysis during sleep for assessing functional aspects of the cardiovascular system. The current study compared the influence of pulse wave and sleep study-derived parameters on cardiovascular risk assessment. In a multi-centric study design, 358 sleep apnea patients (age 55 ± 13 years, 64% male, body mass index 30 ± 6 kg m-2 , apnea-hypopnea index 13 [5-26] events per hr) underwent a standard overnight sleep recording. A novel cardiac risk index was computed based on pulse wave signals derived from pulse oximetry, reflecting vascular stiffness, cardiac variability, vascular autonomic tone and nocturnal hypoxia. Cardiovascular risk was determined using the ESC/ESH cardiovascular risk matrix, and categorized to high/low added cardiovascular risk. Comparisons between cardiac risk index and sleep parameters were performed for cardiovascular risk prediction. Apnea-hypopnea index, oxygen desaturation index and cardiac risk index were associated with high cardiovascular risk after adjustment for confounders (p = .002, .001, < .001, respectively). In a nested reference model consisting of age, gender and body mass index, adding cardiac risk index but not apnea-hypopnea index or oxygen desaturation index significantly increased the area under the receiver operating characteristic curve (p = .012, .22 and .16, respectively). In a direct comparison of oxygen desaturation index and cardiac risk index, only the novel risk index had an independent effect on cardiovascular risk prediction (pCRI  < .001, pODI  = .71). These results emphasize the association between nocturnal pulse wave and overall cardiovascular risk determined by an established risk matrix. Thus, pulse wave analysis during sleep provides a powerful approach for cardiovascular risk assessment in addition to conventional sleep study parameters.

Overnight pulse wave analysis to assess autonomic changes during sleep in insomnia patients and healthy sleepers.

Insomnia has been associated with increased cardiovascular (CV) risk, which may be linked to sympathetic activation. Non-invasive overnight pulse wave analysis may be a useful tool to detect early signs of autonomic changes during sleep in insomniacs. Fifty-two participants (26 men, 37±13 years, BMI: 24±5 kg/m2, 26 insomniacs/ 26 controls) underwent overnight polysomnography with pulse oximetry and pulse wave analysis including pulse rate, vascular stiffness (pulse propagation time, PPT), and a composite cardiac risk index based on autonomic function and overnight hypoxia. We identified two subgroups of insomniacs, with and without objectively disturbed sleep (sleep efficiency SE≤80%, n = 14 vs. SE>80%, n = 12), and observed increased pulse rate and vascular stiffness in insomnia cases when diagnosis was based on both, subjective and objective criteria. Both insomnia groups were associated with higher overnight pulse rate than controls (median/ IQR: low-SE (low sleep efficiency): 67/ 58-70bpm; high-SE: 66/ 63-69bpm; controls: 58/ 52-63bpm; p = 0.01). Vascular stiffness was higher (reduction of PPT) in low-SE insomniacs compared with high-SE insomniacs and controls (169/ 147-232ms; 237/ 215-254ms; 244/ 180-284ms; p = 0.01). The cardiac risk index was increased in low-SE insomniacs (0.2/ 0.0-0.7; 0.0/ 0.0-0.4; 0.0/ 0.0-0.3; p = 0.05). Our results suggest a hyperarousal state in young and otherwise healthy insomniacs during sleep. The increased pulse rate and vascular stiffness in insomniacs with low SE suggest early signs of rigid vessels and potentially, an elevated CV risk. Overnight pulse wave analysis may be feasible for CV risk assessment in insomniacs and may provide a useful tool for phenotyping insomnia in order to provide individualized therapy.