Long-term effect of obstructive sleep apnoea management on blood pressure in patients with resistant hypertension: the SARAH study.

BACKGROUND: There is a close relationship between obstructive sleep apnoea (OSA) and resistant hypertension (RH). However, studies assessing the long-term effect of diagnosing and treating OSA on blood pressure (BP) control in these patients are lacking. METHODS: To address this gap, we recruited 478 RH patients from hypertension units and followed them prospectively after they were screened for OSA through a sleep study. By performing 24-h ambulatory BP monitoring (ABPM) annually, the effect of OSA management was assessed. RESULTS: The patients had a median (interquartile range (IQR)) age of 64.0 (57.2-69.0) years, 67% were males and most were nonsleepy, with a median (IQR) apnoea-hypopnoea index (AHI) of 15.8 (7.9-30.7) events·h-1. The median (IQR) follow-up time was 3.01 (2.93-3.12) years. At baseline, severe OSA was associated with uncontrolled BP, nocturnal hypertension and a nondipper circadian BP pattern. Moreover, these patients had higher BP values during follow-up than did patients in the other groups. However, among patients with moderate and severe OSA, the management of sleep disordered breathing, including the implementation of continuous positive airway pressure treatment, was associated with a reduction in 24-h ABPM parameters, especially night-time BP values, at the 1-year follow-up. These benefits were attenuated over time and only subjects with severe OSA maintained an ABPM night-time reduction at 3 years. Furthermore, clinical variables such as uncontrolled BP, sex and age showed a predictive value for the BP response at 1 year of follow-up. CONCLUSION: A favourable long-term decrease in BP was detected by diagnosing and treating OSA in a cohort of RH patients from hypertension units, but over time this decrease was only partially maintained in severe OSA patients.

The Hypoxic Burden, Clinical Implication of a New Biomarker in the Cardiovascular Management of Sleep Apnea Patients: A Systematic Review.

Background: Obstructive sleep apnea (OSA) is a highly prevalent sleep-disordered breathing. It is associated with adverse co-morbidities, being the most scientific evidence of cardiovascular (CV) disease. Currently, OSA is measured through the apnea-hypopnea index (AHI), the total number of respiratory events per hour of sleep. However, different studies have questioned its utility in OSA management, highlighting the need to search for new parameters that better reflect the heterogeneity of the disease. Hypoxic burden (HB) has emerged as a novel biomarker that informs about the frequency, duration and depth of the desaturation related to the respiratory events. We conducted a systematic review in order to find publications about the heterogeneity of OSA measured by HB and its associations with future disease. Methods: Systematic review was conducted using PubMed and Web of Science. The terms "sleep apne" and "hypoxic burden" were used to look for publications from the date of inception to August 15, 2023. Inclusion criteria: articles in English published in peer-reviewed journals. Exclusion criteria: (1) not available publications; (2) duplicated articles; (3) letters, editorials, and congress communications; (4) articles not including information about HB as a specific biomarker of OSA. Results: 33 studies were included. The results were classified in 2 main sections: (1) HB implication in the CV sphere: HB showed to be a better predictor of CV risk in OSA patients than traditional measures such as AHI with possible clinical management implication in OSA. (2) HB response to OSA treatment: pharmacological and nonpharmacological treatments have demonstrated to be effective in improving hypoxia measured through the HB. Conclusions: HB could be a better and more effective parameter than traditional measurements in terms of diagnosis, risk prediction and therapeutic decisions in patients with OSA. This measure could be incorporated in sleep units and could play a role in OSA management, driving the clinic to a more personalized medicine.

Predicting Alzheimer's disease CSF core biomarkers: a multimodal Machine Learning approach.

Introduction: Alzheimer's disease (AD) is a progressive neurodegenerative disorder. Current core cerebrospinal fluid (CSF) AD biomarkers, widely employed for diagnosis, require a lumbar puncture to be performed, making them impractical as screening tools. Considering the role of sleep disturbances in AD, recent research suggests quantitative sleep electroencephalography features as potential non-invasive biomarkers of AD pathology. However, quantitative analysis of comprehensive polysomnography (PSG) signals remains relatively understudied. PSG is a non-invasive test enabling qualitative and quantitative analysis of a wide range of parameters, offering additional insights alongside other biomarkers. Machine Learning (ML) gained interest for its ability to discern intricate patterns within complex datasets, offering promise in AD neuropathology detection. Therefore, this study aims to evaluate the effectiveness of a multimodal ML approach in predicting core AD CSF biomarkers. Methods: Mild-moderate AD patients were prospectively recruited for PSG, followed by testing of CSF and blood samples for biomarkers. PSG signals underwent preprocessing to extract non-linear, time domain and frequency domain statistics quantitative features. Multiple ML algorithms were trained using four subsets of input features: clinical variables (CLINVAR), conventional PSG parameters (SLEEPVAR), quantitative PSG signal features (PSGVAR) and a combination of all subsets (ALL). Cross-validation techniques were employed to evaluate model performance and ensure generalizability. Regression models were developed to determine the most effective variable combinations for explaining variance in the biomarkers. Results: On 49 subjects, Gradient Boosting Regressors achieved the best results in estimating biomarkers levels, using different loss functions for each biomarker: least absolute deviation (LAD) for the Aß42, least squares (LS) for p-tau and Huber for t-tau. The ALL subset demonstrated the lowest training errors for all three biomarkers, albeit with varying test performance. Specifically, the SLEEPVAR subset yielded the best test performance in predicting Aß42, while the ALL subset most accurately predicted p-tau and t-tau due to the lowest test errors. Conclusions: Multimodal ML can help predict the outcome of CSF biomarkers in early AD by utilizing non-invasive and economically feasible variables. The integration of computational models into medical practice offers a promising tool for the screening of patients at risk of AD, potentially guiding clinical decisions.

Effect of CPAP Treatment on Cardiovascular Outcomes.

INTRODUCTION: Randomized controlled trials (RCT) have not demonstrated a role for continuous positive airway pressure (CPAP) on the secondary prevention of major cardiovascular events in obstructive sleep apnea (OSA) patients. However, participants in RCTs are substantially different from real-world patients. Therefore, we aimed to assess the effect of CPAP treatment on major cardiovascular events in real-world OSA patients. METHODS: Population-based longitudinal observational study including all OSA patients with an active CPAP prescription at the beginning of 2011 in Catalonia, Spain, that terminated CPAP treatment during 2011 and did not have CPAP prescriptions between 2012-2015; and propensity-score-matched OSA patients that continued CPAP treatment until the end of 2015 or death. Adjusted hazard ratios were used to assess the association between CPAP treatment and overall and cardiovascular mortality, cardiovascular hospitalizations, or major adverse cardiovascular events (MACEs). RESULTS: 3638 CPAP terminators and 10,914 propensity-score-matched continuators were included (median age 67 [57-77] years, 71.4% male). During a median follow-up of 47.9 months CPAP continuators showed a lower risk of cardiovascular death than terminators (hazard ratio [HR]: 0.61; 95% confidence interval [CI]: 0.50-0.75) after adjusting by age, sex and key comorbidities. Similar results were found for cardiovascular hospitalizations (HR: 0.87; 95% CI: 0.76-0.99) and MACEs (HR: 0.84; 95% CI: 0.75-0.95). CONCLUSION: CPAP treatment continuation could be associated with a significantly lower risk of major cardiovascular events in real-world OSA patients. This result highlights the importance of including real-world patients in studies on OSA.

Obstructive sleep apnea and cardiovascular risk. / Apnea obstructiva del sueño y riesgo cardiovascular.

Patients with obstructive sleep apnea (OSA) experience repetitive episodes of upper airway obstruction due to recurrent collapse during sleep. This leads to intermittent hypoxia episodes, which, through complex pathophysiological mechanisms, trigger sympathetic overactivation, endothelial dysfunction, hypercoagulation, and metabolic dysregulation. Consequently, other cardiovascular risk factors such as hypertension, metabolic syndrome, and diabetes are induced. Furthermore, this enhances target organ damage, affecting the heart, arteries, and kidneys, leading to an increased risk of cardiovascular morbidity and mortality. Among the various treatments for OSA, Continuous Positive Airway Pressure (CPAP) has been extensively studied. To date, this treatment has shown mild benefits in reducing blood pressure, particularly noticeable in patients with resistant hypertension. Furthermore, CPAP treatment appears to reduce cardiovascular events, both in primary and secondary prevention, though this benefit is limited to individuals with good compliance (CPAP use ≥4h/night). Future research perspectives in OSA seem to focus on identifying patients in whom the condition significantly influences cardiovascular risk, thus determining those who would benefit the most from treatment in the reduction of cardiovascular risk.

ERS International Congress 2023: highlights from the Sleep Disordered Breathing Assembly.

The topic of sleep-related breathing disorders is always evolving, and during the European Respiratory Society (ERS) International Congress 2023 in Milan, Italy, the latest research and clinical topics in respiratory medicine were presented. The most interesting issues included new diagnostic tools, such as cardiovascular parameters and artificial intelligence, pathophysiological traits of sleep disordered breathing from routine polysomnography or polygraphy signals, and new biomarkers and the diagnostic approach in patients with excessive daytime sleepiness. This article summarises the most relevant studies and topics presented at the ERS International Congress 2023. Each section has been written by early career members of ERS Assembly 4.

Heterogeneous Effects of Continuous Positive Airway Pressure in Non-Sleepy Obstructive Sleep Apnea on Cardiovascular Disease Outcomes: Post Hoc Machine Learning Analysis of the ISAACC Trial (ECSACT Study).

Rationale: Randomized controlled trials of continuous positive airway pressure (CPAP) therapy for cardiovascular disease (CVD) prevention among patients with obstructive sleep apnea (OSA) have been largely neutral. However, given that OSA is a heterogeneous disease, there may be unidentified subgroups demonstrating differential treatment effects. Objectives: We sought to apply a novel data-drive approach to identify nonsleepy OSA subgroups with heterogeneous effects of CPAP on CVD outcomes within the Impact of Sleep Apnea Syndrome in the Evolution of Acute Coronary Syndrome (ISAACC) study. Methods: Participants were randomly partitioned into two datasets. One for training (70%) our machine-learning model and a second (30%) for validation of significant findings. Model-based recursive partitioning was applied to identify subgroups with heterogeneous treatment effects. Survival analysis was conducted to compare treatment (CPAP vs. usual care [UC]) outcomes within subgroups. Results: A total of 1,224 nonsleepy OSA participants were included. Of 55 features entered into our model, only two appeared in the final model (i.e., average OSA event duration and hypercholesterolemia). Among participants at or below the model-derived average event duration threshold (19.5 s), CPAP was protective for a composite of CVD events (training hazard ratio [HR], 0.46; P = 0.002). For those with longer event duration (>19.5 s), an additional split occurred by hypercholesterolemia status. Among participants with longer event duration and hypercholesterolemia, CPAP resulted in more CVD events compared with UC (training HR, 2.24; P = 0.011). The point estimate for this harmful signal was also replicated in the testing dataset (HR, 1.83; P = 0.118). Conclusions: We discovered subgroups of nonsleepy OSA participants within the ISAACC study with heterogeneous effects of CPAP. Among the training dataset, those with longer OSA event duration and hypercholesterolemia had nearly 2.5 times more CVD events with CPAP compared with UC, whereas those with shorter OSA event duration had roughly half the rate of CVD events if randomized to CPAP.

Metabolipidomic Analysis in Patients with Obstructive Sleep Apnea Discloses a Circulating Metabotype of Non-Dipping Blood Pressure.

A non-dipping blood pressure (BP) pattern, which is frequently present in patients with obstructive sleep apnea (OSA), confers high cardiovascular risk. The mechanisms connecting these two conditions remain unclear. In the present study we performed a comprehensive analysis of the blood metabolipidome that aims to provide new insights into the molecular link between OSA and the dysregulation of circadian BP rhythmicity. This was an observational prospective longitudinal study involving adults with suspected OSA who were subjected to full polysomnography (PSG). Patients with an apnea-hypopnea index ≥ 5 events/h were included. Fasting plasma samples were obtained the morning after PSG. Based on the dipping ratio (DR; ratio of night/day BP values) measured via 24 h ambulatory BP monitoring, two groups were established: dippers (DR ≤ 0.9) and non-dippers (DR > 0.9). Treatment recommendations for OSA followed the clinical guidelines. Untargeted metabolomic and lipidomic analyses were performed in plasma samples via liquid chromatography-tandem mass spectrometry. Non-dipper patients represented 53.7% of the cohort (88/164 patients). A set of 31 metabolic species and 13 lipidic species were differentially detected between OSA patients who present a physiologic nocturnal BP decrease and those with abnormal BP dipping. Among the 44 differentially abundant plasma compounds, 25 were putatively identified, notably glycerophospholipids, glycolipids, sterols, and fatty acid derivates. Multivariate analysis defined a specific metabotype of non-dipping BP, which showed a significant dose-response relationship with PSG parameters of OSA severity, and with BP dipping changes after 6 months of OSA treatment with continuous positive airway pressure (CPAP). Bioinformatic analyses revealed that the identified metabolipidomic profile was found to be implicated in multiple systemic biological pathways, with potential physiopathologic implications for the circadian control of BP among individuals with OSA.