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.

Sleep and Circadian Health of Critical Survivors: A 12-Month Follow-Up Study.

OBJECTIVES: To investigate the sleep and circadian health of critical survivors 12 months after hospital discharge and to evaluate a possible effect of the severity of the disease within this context. DESIGN: Observational, prospective study. SETTING: Single-center study. PATIENTS: Two hundred sixty patients admitted to the ICU due to severe acute respiratory syndrome coronavirus 2 infection. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The cohort was composed of 260 patients (69.2% males), with a median (quartile 1-quartile 3) age of 61.5 years (52.0-67.0 yr). The median length of ICU stay was 11.0 days (6.00-21.8 d), where 56.2% of the patients required invasive mechanical ventilation (IMV). The Pittsburgh Sleep Quality Index (PSQI) revealed that 43.1% of the cohort presented poor sleep quality 12 months after hospital discharge. Actigraphy data indicated an influence of the disease severity on the fragmentation of the circadian rest-activity rhythm at the 3- and 6-month follow-ups, which was no longer significant in the long term. Still, the length of the ICU stay and the duration of IMV predicted a higher fragmentation of the rhythm at the 12-month follow-up with effect sizes (95% CI) of 0.248 (0.078-0.418) and 0.182 (0.005-0.359), respectively. Relevant associations between the PSQI and the Hospital Anxiety and Depression Scale (rho = 0.55, anxiety; rho = 0.5, depression) as well as between the fragmentation of the rhythm and the diffusing lung capacity for carbon monoxide (rho = -0.35) were observed at this time point. CONCLUSIONS: Our findings reveal a great prevalence of critical survivors presenting poor sleep quality 12 months after hospital discharge. Actigraphy data indicated the persistence of circadian alterations and a possible impact of the disease severity on the fragmentation of the circadian rest-activity rhythm, which was attenuated at the 12-month follow-up. This altogether highlights the relevance of considering the sleep and circadian health of critical survivors in the long term.

Sleep and Circadian Health of Critical COVID-19 Survivors 3 Months After Hospital Discharge.

OBJECTIVES: To evaluate the sleep and circadian rest-activity pattern of critical COVID-19 survivors 3 months after hospital discharge. DESIGN: Observational, prospective study. SETTING: Single-center study. PATIENTS: One hundred seventy-two consecutive COVID-19 survivors admitted to the ICU with acute respiratory distress syndrome. INTERVENTIONS: Seven days of actigraphy for sleep and circadian rest-activity pattern assessment; validated questionnaires; respiratory tests at the 3-month follow-up. MEASUREMENTS AND MAIN RESULTS: The cohort included 172 patients, mostly males (67.4%) with a median (25th-75th percentile) age of 61.0 years (52.8-67.0 yr). The median number of days at the ICU was 11.0 (6.00-24.0), and 51.7% of the patients received invasive mechanical ventilation (IMV). According to the Pittsburgh Sleep Quality Index (PSQI), 60.5% presented poor sleep quality 3 months after hospital discharge, which was further confirmed by actigraphy. Female sex was associated with an increased score in the PSQI (p < 0.05) and IMV during ICU stay was able to predict a higher fragmentation of the rest-activity rhythm at the 3-month follow-up (p < 0.001). Furthermore, compromised mental health measured by the Hospital Anxiety and Depression Scale was associated with poor sleep quality (p < 0.001). CONCLUSIONS: Our findings highlight the importance of considering sleep and circadian health after hospital discharge. Within this context, IMV during the ICU stay could aid in predicting an increased fragmentation of the rest-activity rhythm at the 3-month follow-up. Furthermore, compromised mental health could be a marker for sleep disruption at the post-COVID period.

Impact of time to intubation on mortality and pulmonary sequelae in critically ill patients with COVID-19: a prospective cohort study.

QUESTION: We evaluated whether the time between first respiratory support and intubation of patients receiving invasive mechanical ventilation (IMV) due to COVID-19 was associated with mortality or pulmonary sequelae. MATERIALS AND METHODS: Prospective cohort of critical COVID-19 patients on IMV. Patients were classified as early intubation if they were intubated within the first 48 h from the first respiratory support or delayed intubation if they were intubated later. Surviving patients were evaluated after hospital discharge. RESULTS: We included 205 patients (140 with early IMV and 65 with delayed IMV). The median [p25;p75] age was 63 [56.0; 70.0] years, and 74.1% were male. The survival analysis showed a significant increase in the risk of mortality in the delayed group with an adjusted hazard ratio (HR) of 2.45 (95% CI 1.29-4.65). The continuous predictor time to IMV showed a nonlinear association with the risk of in-hospital mortality. A multivariate mortality model showed that delay of IMV was a factor associated with mortality (HR of 2.40; 95% CI 1.42-4.1). During follow-up, patients in the delayed group showed a worse DLCO (mean difference of - 10.77 (95% CI - 18.40 to - 3.15), with a greater number of affected lobes (+ 1.51 [95% CI 0.89-2.13]) and a greater TSS (+ 4.35 [95% CI 2.41-6.27]) in the chest CT scan. CONCLUSIONS: Among critically ill patients with COVID-19 who required IMV, the delay in intubation from the first respiratory support was associated with an increase in hospital mortality and worse pulmonary sequelae during follow-up.

New forehead device in positional obstructive sleep apnoea: a randomised clinical trial.

RATIONALE: Approximately 60% of the patients with obstructive sleep apnoea suffer from a positional effect, and approximately 25% of these patients present events only in the supine position. OBJECTIVE: To validate a new positional vibrating device and evaluate its efficacy in reducing the Apnoea-Hypopnoea Index and the total sleep time in the supine position without disturbing sleep. METHODS: A total of 128 patients were recruited for this multicentre, prospective, parallel, randomised controlled trial and were distributed in three arms (general recommendations, inactive and active device). Full overnight polysomnography was performed at baseline and at 12 weeks. Anthropometric variables and sleep and quality of life questionnaires were collected at 4, 8 and 12 weeks. RESULTS: The Apnoea-Hypopnoea Index decreased from 30.6 per hour to 20.4 per hour (p<0.001) in the active device (AD) group. In this group the reduction was 2.3-fold and 3.3-fold than the ones in the general recommendations (GR) and inactive device (ID) groups, respectively (p=0.014). Sleep time in supine position decreased 17.7%±26.3% in GR group (p<0.001), 13.0%±22.4% with ID group (p<0.001) and 21.0%±25.6% in the AD group (p<0.001). Furthermore, total sleep time increased significantly only in the AD group (22.1±57.5 min, p=0.016), with an increased percentage of time in the N3 (deep sleep) and N3+REM (rapid eye movement) stages, without sleep fragmentation. CONCLUSION: The device was effective in reducing the Apnoea-Hypopnoea Index and time spent in the supine position also in improving sleep architecture. Therefore, the device could be a good option for the management of patients with positional obstructive sleep apnoea. TRIAL REGISTRATION DETAILS: The trial was registered at www.clinicaltrials.gov (NCT03336515).

Management and Treatment of Patients With Obstructive Sleep Apnea Using an Intelligent Monitoring System Based on Machine Learning Aiming to Improve Continuous Positive Airway Pressure Treatment Compliance: Randomized Controlled Trial.

BACKGROUND: Continuous positive airway pressure (CPAP) is an effective treatment for obstructive sleep apnea (OSA), but treatment compliance is often unsatisfactory. OBJECTIVE: The aim of this study was to assess the effectiveness and cost-effectiveness of an intelligent monitoring system for improving CPAP compliance. METHODS: This is a prospective, open label, parallel, randomized controlled trial including 60 newly diagnosed patients with OSA requiring CPAP (Apnea-Hypopnea Index [AHI] >15) from Lleida, Spain. Participants were randomized (1:1) to standard management or the MiSAOS intelligent monitoring system, involving (1) early compliance detection, thus providing measures of patient's CPAP compliance from the very first days of usage; (2) machine learning-based prediction of midterm future CPAP compliance; and (3) rule-based recommendations for the patient (app) and care team. Clinical and anthropometric variables, daytime sleepiness, and quality of life were recorded at baseline and after 6 months, together with patient's compliance, satisfaction, and health care costs. RESULTS: Randomized patients had a mean age of 57 (SD 11) years, mean AHI of 50 (SD 27), and 13% (8/60) were women. Patients in the intervention arm had a mean (95% CI) of 1.14 (0.04-2.23) hours/day higher adjusted CPAP compliance than controls (P=.047). Patients' satisfaction was excellent in both arms, and up to 88% (15/17) of intervention patients reported willingness to keep using the MiSAOS app in the future. No significant differences were found in costs (control: mean €90.2 (SD 53.14) (US $105.76 [SD 62.31]); intervention: mean €96.2 (SD 62.13) (US $112.70 [SD 72.85]); P=.70; €1=US $1.17 was considered throughout). Overall costs combined with results on compliance demonstrated cost-effectiveness in a bootstrap-based simulation analysis. CONCLUSIONS: A machine learning-based intelligent monitoring system increased daily compliance, reported excellent patient satisfaction similar to that reported in usual care, and did not incur in a substantial increase in costs, thus proving cost-effectiveness. This study supports the implementation of intelligent eHealth frameworks for the management of patients with CPAP-treated OSA and confirms the value of patients' empowerment in the management of chronic diseases. TRIAL REGISTRATION: ClinicalTrials.gov NCT03116958; https://clinicaltrials.gov/ct2/show/NCT03116958.

MicroRNA Profile of Cardiovascular Risk in Patients with Obstructive Sleep Apnea.

BACKGROUND: Obstructive sleep apnea (OSA) is a common disease caused by repeated episodes of collapse of the upper airway during sleep and is associated with the development of cardiovascular disease (CVD). However, there is high heterogeneity in the impact of OSA on patients. Until now, the profile of OSA patients at risk of developing CVD has not been defined, including the measurable variables that could be used to predict the CVD risk of a patient with OSA. OBJECTIVE: The aim of this study was to identify the microRNA (mi-RNA) profile associated with CVD in patients with OSA. METHOD: This is an observational, cross-sectional study that included 132 male patients. Three groups were defined as OSA patients, OSA patients with hypertension, and OSA patients who developed a major cardiovascular event. Polysomnography and ambulatory blood pressure measurements were performed. The expression profiling of 188 miRNAs in plasma was performed in 21 subjects (matched by BMI and age) by the TaqMan low density array (TLDA). miRNAs differentially expressed in the different subgroups of patients and miRNAs that correlated with the cardiovascular risk SCORE were selected for validation by RT-qPCR in the 111 remaining patients. RESULTS: From the TLDA analysis, 7 miRNAs were selected for validation. Differential expression was not confirmed in any of the miRNAs. miR-143 was associated with nocturnal systolic blood pressure. miR-107 correlated with 24-h blood pressure parameters and with nocturnal hypertension. miR-486 was associated with the cardiovascular risk SCORE. CONCLUSIONS: The circulating profile of miRNAs does not seem to be different in any of the subgroups of patients with OSA and different cardiovascular risk factors. Nevertheless, miR-107 and miR-143 are associated with specific blood pressure parameters in patients with OSA and miR-486 is associated with the cardiovascular risk SCORE.

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.

The Effect of Obstructive Sleep Apnea on Subclinical Target Organ Damage in Patients With Resistant Hypertension.

INTRODUCTION: Among all patients with hypertension, those with resistant hypertension (RH) have the highest rates of subclinical organ damage (SOD). The prevalence of obstructive sleep apnea (OSA) is high in RH patients, and it could contribute to SOD. We aimed to investigate how OSA and its treatment are related to SOD in a large cohort of RH patients. METHODS: This is an ancillary analysis to the SARAH study, a multicentre observational cohort aiming to evaluate the impact of OSA on RH. Individuals with RH who were undergoing a sleep study and have information on at least one of the SOD variables (vascular, cardiac or renal damage) were selected. Patients were followed-up for three years. RESULTS: In total, 503 subjects were included. The participants were predominantly male, obese, and the median (IQR) apnea-hypopnea index (AHI) was 15.5 (7.90-31.5)events/h. No differences in the presence of vascular or cardiac damage were observed between OSA and non-OSA patients. A lower estimated glomerular filtration rate (eGFR) was observed in participants with OSA than in those without OSA, with an adjusted effect of -8.69mL/min/1.73m2 (-13.59, -3.79; p value<0.001). Kidney damage was also greater in subjects with OSA, with an adjusted OR (95% CI) of 1.77 (1.09, 2.87; p value=0.02). The eGFR showed a linear dose-response relationship with OSA severity. Among patients treated with CPAP, lower eGFR values were observed in noncompliant subjects. CONCLUSIONS: OSA could contribute to worsening renal function in patients with RH. No compliance with CPAP was associated with lower values of eGFR.

Patient compliance and satisfaction with a new forehead device for positional obstructive sleep apnoea treatment: a post hoc analysis of a randomised controlled trial.

BACKGROUND: The influence of body position in obstructive sleep apnoea patients is well known. A positional therapy device placed at the forehead has proven to be effective in reducing the severity of positional obstructive sleep apnoea (POSA) symptoms. The aim of the study was to evaluate patients' therapy compliance and satisfaction in the short term and mid-term. METHODS: A post hoc analysis of a randomised controlled trial was conducted using an inactive device (ID) or an active device (AD) for 3 months. The primary outcomes were device usage and the percentage of patients with good compliance (defined as device use for more than 4 hours per night and more than 70% of nights per week). Secondary outcomes included time spent with head in the supine position, patient satisfaction and side effects. RESULTS: The median duration of using the device was 6.9 hours in the ID group and 6.7 hours in the AD group (p=0.309), and the durations were similar throughout the follow-up period and from the first day of use. The percentage of patients with good compliance was similar and greater than 60% in both groups. The median time spent with head in the supine position was significantly lower in the AD group (2.9%) than in the ID group (12.4%) since the first day of treatment. Both groups showed satisfaction scores values above 8.5 (out of 10) in all items, while side effects were scarcely reported. CONCLUSION: High device compliance was achieved in POSA patients, both in terms of device usage time and percentage of days used. Patients were highly satisfied, and the device effectively reduced the time spent with the head in the supine position from the first day of use.

Breathing cessation events that compose the apnea-hypopnea index are distinctively associated with the adverse outcomes in Alzheimer's disease.

BACKGROUND: Previous studies challenge the impact of obstructive sleep apnea (OSA) once patients are diagnosed with Alzheimer's disease (AD). Nevertheless, OSA recognizably disrupts sleep, and relevant associations between sleep, AD pathological markers, and cognition have been demonstrated. We aimed to further explore this, evaluating the associations between each breathing cessation event that compose the apnea-hypopnea index (AHI) and the sleep structure to finally investigate whether this was related to increased levels of AD markers and higher cognitive decline. METHODS: Observational, prospective study, including consecutive patients diagnosed with mild-moderate AD. The participants were submitted to overnight polysomnography followed by a cerebrospinal fluid collection for AD pathological markers levels determination. Neuropsychological assessment was performed at baseline and after 12 months of follow-up. RESULTS: The cohort was composed of 116 patients (55.2% females) with a median [p25;p75] age of 76.0 [72.0;80.0] years and an AHI of 25.9 [15.1;48.5], which was mainly defined by the presence of hypopneas and obstructive apneas. These were distinctively associated with the sleep structure, with obstructive apneas being related to arousals and sleep lightening and hypopneas being related to an increased number of arousals only. Despite having a lower frequency, mixed and central apneas also presented associations with the sleep structure, particularly increasing the time spent in the lighter sleep stages. In relation to AD pathological markers, obstructive and mixed apneas were related to an augment in neurofilament light levels while hypopneas were associated with a higher phosphorylated-tau/amyloid-beta protein ratio. Hypopneas were the most important event for an increased cognitive decline at the 12-month follow-up. CONCLUSIONS: Our findings highlight the importance of a patient-centered approach, with a comprehensive and detailed analysis of the AHI to effectively predict the different outcomes and tailor the appropriate therapeutic strategies.

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.

One Year Overview and Follow-Up in a Post-COVID Consultation of Critically Ill Patients.

The long-term clinical management and evolution of a cohort of critical COVID-19 survivors have not been described in detail. We report a prospective observational study of COVID-19 patients admitted to the ICU between March and August 2020. The follow-up in a post-COVID consultation comprised symptoms, pulmonary function tests, the 6-minute walking test (6MWT), and chest computed tomography (CT). Additionally, questionnaires to evaluate the prevalence of post-COVID-19 syndrome were administered at 1 year. A total of 181 patients were admitted to the ICU during the study period. They were middle-aged (median [IQR] of 61 [52;67]) and male (66.9%), with a median ICU stay of 9 (5-24.2) days. 20% died in the hospital, and 39 were not able to be included. A cohort of 105 patients initiated the follow-up. At 1 year, 32.2% persisted with respiratory alterations and needed to continue the follow-up. Ten percent still had moderate/severe lung diffusion (DLCO) involvement (<60%), and 53.7% had a fibrotic pattern on CT. Moreover, patients had a mean (SD) number of symptoms of 5.7 ± 4.6, and 61.3% met the criteria for post-COVID syndrome at 1 year. During the follow-up, 46 patients were discharged, and 16 were transferred to other consultations. Other conditions, such as emphysema (21.6%), COPD (8.2%), severe neurocognitive disorders (4.1%), and lung cancer (1%) were identified. A high use of health care resources is observed in the first year. In conclusion, one-third of critically ill COVID-19 patients need to continue follow-up beyond 1 year, due to abnormalities on DLCO, chest CT, or persistent symptoms.

A new postural device for the treatment of positional obstructive sleep apnea. A pilot study.

BACKGROUND: Approximately 60% of obstructive sleep apnea (OSA) diagnoses are position-dependent, and avoidance of the supine position could represent an effective treatment. Nevertheless, the majority of the available anti-supine treatments result in discomfort and low adherence. This study evaluated the effectiveness of a new vibrating supine avoidance device in reducing time spent in the supine position and the apnea-hypopnea index (AHI) without affecting sleep structure. Furthermore, the tolerability and satisfaction were also scored. METHODS: Observational prospective study of patients suffering from positional OSA. They were treated with a vibrating device and followed up at the first and fourth weeks after starting the treatment, and further polysomnographic studies were conducted while patients' wore the device. The comparison of the results was carried out through non-parametric tests. Significance level was 5%. RESULTS: Twelve patients had complete data. The device reduced time spent in the supine position (from 51.5 ±â€¯14.8% to 25.2 ±â€¯21.0%, p = 0.005), median AHI (from 30.7 (23.2-38.2) at baseline to 21.5 (12.4-24.3) at the fourth week, p = 0.002). Also an improvement in the minimum SaO2 (from 82.2 ±â€¯7.5 to 87.2 ±â€¯3.6 at the 4th week) was also observed. No variations in sleep quality or quantity were identified. All patients evaluated the device positively. CONCLUSION: Our device was effective in reducing the time spent in the supine position and improving AHI, SaO2 variables and sleep architecture. The device was well tolerated by the patients.