Breath-holding as a means to estimate the loop gain contribution to obstructive sleep apnoea.

KEY POINTS: A hypersensitive ventilatory control system or elevated "loop gain" during sleep is a primary phenotypic trait causing obstructive sleep apnoea (OSA). Despite the multitude of methods available to assess the anatomical contributions to OSA during wakefulness in the clinical setting (e.g. neck circumference, pharyngometry, Mallampati score), it is currently not possible to recognize elevated loop gain in patients in this context. Loop gain during sleep can now be recognized using simplified testing during wakefulness, specifically in the form of a reduced maximal breath-hold duration, or a larger ventilatory response to voluntary 20-second breath-holds. We consider that easy breath-holding manoeuvres will enable daytime recognition of a high loop gain in OSA for more personalized intervention. ABSTRACT: Increased "loop gain" of the ventilatory control system promotes obstructive sleep apnoea (OSA) in some patients and offers an avenue for more personalized treatment, yet diagnostic tools for directly measuring loop gain in the clinical setting are lacking. Here we test the hypothesis that elevated loop gain during sleep can be recognized using voluntary breath-hold manoeuvres during wakefulness. Twenty individuals (10 OSA, 10 controls) participated in a single overnight study with voluntary breath-holding manoeuvres performed during wakefulness. We assessed (1) maximal breath-hold duration, and (2) the ventilatory response to 20 s breath-holds. For comparison, gold standard loop gain values were obtained during non-rapid eye movement (non-REM) sleep using the ventilatory response to 20 s pulses of hypoxic-hypercapnic gas (6% CO2 -14% O2 , mimicking apnoea). Continuous positive airway pressure (CPAP) was used to maintain airway patency during sleep. Additional measurements included gold standard loop gain measurement during wakefulness and steady-state loop gain measurement during sleep using CPAP dial-ups. Higher loop gain during sleep was associated with (1) a shorter maximal breath-hold duration (r2  = 0.49, P < 0.001), and (2) a larger ventilatory response to 20 s breath-holds during wakefulness (second breath; r2  = 0.50, P < 0.001); together these factors combine to predict high loop gain (receiver operating characteristic area-under-curve: 92%). Gold standard loop gain values were remarkably similar during wake and non-REM sleep. The results show that elevated loop gain during sleep can be identified using simple breath-holding manoeuvres performed during wakefulness. This may have implications for personalizing OSA treatment.

Phenotyping-based treatment improves obstructive sleep apnea symptoms and severity: a pilot study.

BACKGROUND: Obstructive sleep apnea is a common disorder characterized by multiple pathogenetic roots. Continuous positive airway pressure (CPAP) is almost always prescribed as the first-line treatment to all patients regardless of the heterogeneous pathophysiology, because it mechanically splints the airways open and reduces the collapsibility of the upper airway. Despite its high efficacy, CPAP is burdened by poor adherence and compliance rates. In this pilot study, we treated OSA patients with composite approaches different than CPAP, tailoring the therapeutic choice on OSA phenotypic traits. METHODS: We used the CPAP dial down technique to assess phenotypic traits in eight OSA patients with BMI<35. According to these traits, patients received personalized therapies for 2-week period, after which we ran a second polygraphy to compare apnea-hypopnea index (AHI) before and after therapy. RESULTS: Two weeks of combined behavioral and pharmacological therapy induced a significant reduction in mean AHI, which dropped from 26 ± 15 at baseline to 9 ± 7 post-treatment (p = 0.01). Furthermore, there was a significant reduction in mean ODI (p = 0.03) and subjective sleepiness (p = 0.01) documented by Epworth Sleepiness Scale (ESS) from baseline to post-treatment recordings. CONCLUSIONS: Treating OSA patients with a personalized combination of pharmacological and behavioral therapies according to phenotypic traits leads to a significant improvement in AHI, ODI, and subjective sleepiness.

A Validation Study of Four Different Cluster Analyses of OSA and the Incidence of Cardiovascular Mortality in a Hispanic Population.

BACKGROUND: Previous studies reported a strong association between sleepiness-related symptoms and comorbidities with poor cardiovascular outcomes among patients with moderate to severe OSA (msOSA). However, the validation of these associations in the Hispanic population from South America and the ability to predict incident cardiovascular disease remain unclear. RESEARCH QUESTION: In Hispanic patients with msOSA, are four different cluster analyses reproducible and able to predict incident cardiovascular mortality? STUDY DESIGN AND METHODS: Using the SantOSA cohort, we reproduced four cluster analyses (Sleep Heart Health Study [SHHS], Icelandic Sleep Apnea Cohort [ISAC], Sleep Apnea Cardiovascular Endpoints [SAVE], and The Institute de Recherche en Sante Respiratoire des Pays de la Loire [IRSR] cohorts) following a cluster analysis similar to each training dataset. The incidence of cardiovascular mortality was constructed using a Kaplan-Meier (log-rank) model, and Cox proportional hazards models were adjusted by confounders. RESULTS: Among 780 patients with msOSA in our cohort, two previous cluster analyses (SHHS and ISAC) were reproducible. The SAVE and IRSR cluster analyses were not reproducible in our sample. We identified the following subtypes for SHHS: "minimally symptomatic," "disturbed sleep," "moderate sleepiness," and "severe sleepiness." For ISAC, three different subtypes ("minimally symptomatic," "disturbed sleep," and "excessive sleepiness") were similar to the original dataset. Compared with "minimally symptomatic," we found a significant association between "excessive sleepiness" and cardiovascular mortality after 5 years of follow-up in SantOSA, hazard ratio (HR), 5.47; 95% CI, 1.74-8.29; P < .01; and HR, 3.23; 95% CI, 1.21-8.63; P = .02, using the SHHS and ISAC cluster analyses, respectively. INTERPRETATION: Among patients with msOSA, a symptom-based approach can validate different OSA patient subtypes, and those with excessive sleepiness have an increased risk of incident cardiovascular mortality in the Hispanic population from South America.

Lung air trapping lowers respiratory arousal threshold and contributes to sleep apnea pathogenesis in COPD patients with overlap syndrome.

STUDY OBJECTIVES: Overlap syndrome occurs when obstructive sleep apnea (OSA) and chronic obstructive pulmonary disorder (COPD) coexist in the same patient. Although several studies highlighted the importance of clinical phenotyping in OSA, the trait contribution to OSA pathogenesis in overlap syndrome has not been investigated. With this pilot study, we aimed to measure OSA determinants and their relationship with functional respiratory parameters in a sample of patients with overlap syndrome. In particular, we hypothesize that patients with COPD have in the low arousal threshold a major contributor for the development of OSA. METHODS: Ten consecutive non-hypercapnic COPD patients (body mass index<35 kg/m2) suffering from overlap syndrome with no other relevant comorbidities underwent a phenotyping polysomnography. Traits were measured with CPAP dial-downs. RESULTS: Arousal threshold was found to be inversely associated to functional measures of lung air trapping and static hyperinflation. Particularly, correlations with residual volume (r2 = 0.49, p =  0.024) and residual volume to total lung capacity ratio (r2 = 0.48, p =  0.026) were evident. Only 20% of patients showed a high upper airway passive collapsibility as single pathological trait. In contrast, among those patients with multiple altered traits (6 out of 10), all had an elevated loop gain and 4 (∼65%) a low arousal threshold. CONCLUSIONS: High loop gain and particularly low arousal threshold seem important contributors to OSA pathogenesis and severity in patients with COPD. Recognizing in COPD patients these features as key traits may open avenues for personalized medicine in the field of overlap syndrome.

Fenotipos clínicos en el síndrome de apnea obstructiva del sueño / Clinical phenotypes in obstructive sleep apnea

El síndrome de apnea e hipopnea obstructiva del sueño se caracteriza por episodios repetitivos de obstrucción de vía aérea superior y es reconocida cada vez más, como un trastorno heterogéneo y complejo, proponiéndose múltiples fenotipos en base a su mecanismo patogénico, alteraciones polisomnográficas y la presentación clínica. El fenotipo clínico se enfoca en identificar características de un paciente basándose en signos, síntomas, antropometría, comorbilidades, medidas fisiológicas, anatómicas o respuesta al tratamiento. Al ser una enfermedad sub diagnosticada, de alta prevalencia y que produce elevada morbi-mortalidad, se debe estar atento a la pesquisa precoz y en las poblaciones de riesgo. Su diagnóstico se basa en el índice de apnea-hipopnea (IAH) y se requiere un IAH •5 eventos/hora para confirmar el diagnóstico. Sin embargo, cada vez hay más evidencia que el IAH por sí solo es insuficiente para comprender la presentación clínica, respuesta al tratamiento, calidad de vida y mortalidad de los pacientes con apnea del sueño. El fenotipo clínico puede servir de este modo, para entender mejor las diferentes formas de presentación teniendo como finalidad la medicina personalizada con el objetivo de favorecer la conducta terapéutica individualizada. El objetivo de esta revisión es abordar los fenotipos clínicos y proponer una huella digital en los pacientes con apnea del sueño

Obstructive sleep apnea and hypopnea syndrome is characterized by repetitive episodes of upper airway obstruction and is increasingly recognized as a heterogeneous and complex disorder, proposing multiple phenotypes based on its pathogenic mechanism, polysomnographic alterations, and clinical presentation. The clinical phenotype focuses on identifying a patient's characteristics based on signs, symptoms, anthropometry, comorbidities, physiological, anatomical measures or response to treatment. As it is an underdiagnosed disease of high prevalence associated to high morbidity and mortality, we must be alert to early screening and risk populations. Diagnosis is based on the apnea-hypopnea index (AHI) AHI •5 events/hour is required to confirm it, however, there is increasing evidence that AHI alone is insufficient to understand the clinical presentation, the response to treatment, the quality of life and the mortality of patients with sleep apnea. In this way, the clinical phenotype can serve to better understand the different forms of presentation and looks for a personalized medicine that favors an individualized therapeutic behavior. The aim of this review is to address clinical phenotypes and propose a fingerprint in patients with sleep apnea