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Current studies agree on the impact of sleep and circadian rest–activity rhythm alterations in acute respiratory distress syndrome (ARDS) survivors. However, research on the duration of this impact is scarce. In this study, we evaluate the impact of ARDS on the sleep and circadian rest–activity rhythm of COVID-19 survivors twelve months after hospital discharge. This is a prospective study including COVID-19 survivors with and without ARDS during hospitalization. Data was collected four and twelve months after hospital discharge. The interventions included one-week wrist actigraphy and a home sleep apnea test (HSAT), and evaluations were conducted according to the Pittsburgh sleep quality index (PSQI), Epworth sleepiness scale (ESS), and insomnia severity index (ISI). Fifty-two patients were evaluated (ARDS = 31 and non-ARDS = 21); they had a median age of 49.0 [39.0;57.2] years and 53.8% were male. After twelve months, 91.3% presented poor sleep quality, 58.7% presented insomnia, 50% presented daytime somnolence, and 37% presented comorbid insomnia and obstructive sleep apnea (COMISA). No significant improvement was observed in relation to sleep or the circadian rest–activity rhythm between four and twelve months. A tendency of poor sleep quality, insomnia, daytime somnolence, and COMISA was observed. Finally, there was no significant impact on the circadian rest–activity rhythm between four and twelve months or between the groups.

Abstract Recent studies have evaluated the potential of circulating microRNAs (miRNAs) as valuable biomarkers for characterizing obstructive sleep apnea (OSA) in males. The potential use of miRNAs as clinical indicators in females is unknown. The objective is to identify a set of miRNAs to be used as endogenous controls (ECs) in female patients with OSA. Then, to analyze differences in the miRNA expression profile between patients with and without OSA. This observational, longitudinal study included 85 females with suspected OSA who underwent a polysomnography. OSA was defined as an apnea hypopnea index ≥ 15 events/h. The study population was stratified into 50 OSA patients and 38 non-OSA patients. Exploratory expression profiling of 188 miRNAs consistent and reliable in plasma was performed in a discovery cohort of 21 patients by TaqMan-Low-Density-Array (TLDA). The best ECs were identified by mean centre + standard deviation normalization and concordance correlation restricted normalization. Differentially expressed candidate miRNAs were selected for RT-qPCR validation in a validation cohort of 64 patients. Three circulating miRNAs (miR-30a-5p, miR-93-3p and miR-532-5p) were identified as most stable for use as ECs. Twenty-seven miRNA candidates were identified as potential biomarkers for OSA screening (p value

Abstract Background COVID-19 can course with respiratory and extrapulmonary disease. SARS-CoV-2 RNA is detected in respiratory samples but also in blood, stool and urine. Severe COVID-19 is characterized by a dysregulated host response to this virus. We studied whether viral RNAemia or viral RNA load in plasma is associated with severe COVID-19 and also to this dysregulated response. Methods A total of 250 patients with COVID-19 were recruited (50 outpatients, 100 hospitalized ward patients and 100 critically ill). Viral RNA detection and quantification in plasma was performed using droplet digital PCR, targeting the N1 and N2 regions of the SARS-CoV-2 nucleoprotein gene. The association between SARS-CoV-2 RNAemia and viral RNA load in plasma with severity was evaluated by multivariate logistic regression. Correlations between viral RNA load and biomarkers evidencing dysregulation of host response were evaluated by calculating the Spearman correlation coefficients. Results The frequency of viral RNAemia was higher in the critically ill patients (78%) compared to ward patients (27%) and outpatients (2%) (p

Background: Little is known about the prevalence of cerebral microangiopathy (CM), which is related to cognitive impairment, in an asymptomatic population. Pulsatility index (PI) is an easily measurable parameter of cerebral vascular resistance in transcranial duplex of the middle cerebral artery (MCA) study. We aimed to determine the prevalence of CM measured by PI of MCA in low to moderate vascular risk subjects.Methods: We included 3,721 subjects between 45 and 70 years without previous history of vascular disease or diabetes mellitus and with at least one other vascular risk factor from the cross-sectional study ILERVAS (Lleida, Spain). Patients underwent transcranial duplex to determine MCA-PI. Possible CM was defined by MCA-PI >1.1. Carotid and femoral arteries ultrasound registration was done to determine the presence, the number, and the area of atheromatous plaques. Body mass index (BMI), pulse pressure (PP) and laboratory data were also recorded.Results: 439 (11.8%) subjects were excluded due to the low quality of transcranial duplex images. Median age was 57 [IQR 52, 62] years. Possible CM was found in 424 (12.9%) subjects. CM patients had higher prevalence of plaques than non-CM (77.4 vs. 66.4%, p < 0.001). PI showed a positive linear correlation with the number of territories with plaques (r = 0.130, p < 0.001), and the total plaque area (r = 0.082, p < 0.001). The predictors of possible CM were the age, male gender, and PP.Conclusions: In low-to-moderate vascular risk asymptomatic population, the proportion of abnormal brain microvascular bed determined by MCA-PI is not negligible. The planned 10-year follow-up will describe the clinical relevance of these findings.

The objective was to describe the clinical characteristics and outcomes of hospitalized COVID-19 patients during the two different epidemic periods. Prospective, observational, cohort study of hospitalized COVID-19. A total of 421 consecutive patients were included, 188 during the first period (March-May 2020) and 233 in the second wave (July-December 2020). Clinical, epidemiological, prognostic and therapeutic data were compared. Patients of the first outbreak were older and more comorbid, presented worse PaO2/FiO2 ratio and an increased creatinine and D-dimer levels at hospital admission. The hospital stay was shorter (14.5[8;29] vs 8[6;14] days, p

Hypertension is one of the most frequent cardiovascular risk factors. The population of hypertensive patients includes some phenotypes whose blood pressure levels are particularly difficult to control, thus putting them at greater cardiovascular risk. This is especially true of so-called resistant hypertension (RH) and refractory hypertension (RfH). Recent findings suggest that the former may be due to an alteration in the renin−angiotensin−aldosterone axis, while the latter seems to be more closely related to sympathetic hyper-activation. Both these pathophysiological mechanisms are also activated in patients with obstructive sleep apnoea (OSA). It is not surprising, therefore, that the prevalence of OSA in RH and RfH patients is very high (as reflected in several studies) and that treatment with continuous positive airway pressure (CPAP) manages to reduce blood pressure levels in a clinically significant way in both these groups of hypertensive patients. It is therefore necessary to incorporate into the multidimensional treatment of patients with RH and RfH (changes in lifestyle, control of obesity and drug treatment) a study of the possible existence of OSA, as this is a potentially treatable disease. There are many questions that remain to be answered, especially regarding the ideal combination of treatment in patients with RH/RfH and OSA (drugs, renal denervation, CPAP treatment) and patients’ varying response to CPAP treatment.

The global public health crisis caused by the COVID-19 pandemic has intensified the global concern regarding viral respiratory tract infections. Despite their considerable impact on health, society and the economy, effective management of these conditions remains a significant challenge. Integrating high-throughput analyses is pivotal for early detection, prognostication of adverse outcomes, elucidating pathogenetic pathways and developing therapeutic approaches. In recent years, microRNAs (miRNAs), a subset of small noncoding RNAs (ncRNAs), have emerged as promising tools for molecular phenotyping. Current evidence suggests that miRNAs could serve as innovative biological markers, aiding in informed medical decision-making. The cost-effective quantification of miRNAs in standardized samples using techniques routinely employed in clinical laboratories has become feasible. In this context, samples obtained from the airways represent a valuable source of information due to their direct exposure to the infectious agent and host response within the respiratory tract. This review explores viral and host miRNA profiling in airway-derived biosamples as a source of molecular information to guide patient management, with a specific emphasis on SARS-CoV-2 infection.

Objectives: Identifying patients with COVID-19 who are at risk of poor evolution is key to early decide on their hospitalization. We evaluated the combined impact of nucleocapsid (N)-antigenemia profiled by a rapid test and antibodies against the S1 subunit of the SARS-CoV S protein (S1) on the hospitalization risk of patients with COVID-19. Methods: N-antigenemia and anti-S1 antibodies were profiled at admission to the emergency department in 146 patients with COVID-19 using the Panbio® antigen Rapid Test and the SARS-CoV-2 immunoglobulin G II Quant/SARS-CoV-2 immunoglobulin G assay from Abbott. A multivariable analysis was used to evaluate the impact of these factors on hospitalization. Results: Patients with a positive N-antigen test in plasma and anti-S1 levels

Acute respiratory distress syndrome (ARDS) poses a significant and widespread public health challenge. Extensive research conducted in recent decades has considerably improved our understanding of the disease pathophysiology. Nevertheless, ARDS continues to rank among the leading causes of mortality in intensive care units and its management remains a formidable task, primarily due to its remarkable heterogeneity. As a consequence, the syndrome is underdiagnosed, prognostication has important gaps and selection of the appropriate therapeutic approach is laborious. In recent years, the noncoding transcriptome has emerged as a new area of attention for researchers interested in biomarker development. Numerous studies have confirmed the potential of long noncoding RNAs (lncRNAs), transcripts with little or no coding information, as noninvasive tools for diagnosis, prognosis and prediction of the therapeutic response across a broad spectrum of ailments, including respiratory conditions. This article aims to provide a comprehensive overview of lncRNAs with specific emphasis on their role as biomarkers. We review current knowledge on the circulating lncRNAs as potential markers that can be used to enhance decision making in ARDS management. Additionally, we address the primary limitations and outline the steps that will be essential for integration of the use of lncRNAs in clinical laboratories. Our ultimate objective is to provide a framework for the implementation of lncRNAs in the management of ARDS.

IntroductionAlzheimer'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.MethodsMild-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.ResultsOn 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 Aβ42, 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 Aβ42, while the ALL subset most accurately predicted p-tau and t-tau due to the lowest test errors.ConclusionsMultimodal 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.

Background: In 2021, the Spanish Ministry of Health launched the CIBERPOSTCOVID project to establish what post COVID was. The present study reports the level of agreement among stakeholders on post COVID and its clinical and diagnostic characteristics in the Spanish health system. Methods: The agreement on post COVID among clinicians, public health managers, researchers and patients’ representatives was explored in a real-time, asynchronous online Delphi. In a two-wave consensus, respondents rated from 1 (total disagreement) to 6 (total agreement) 67 statements related to terminology, duration, etiology, symptoms, impact on quality of life, severity, elements to facilitate diagnosis, applicability in the pediatric population, and risk factors. Consensus was reached when 70 % of ratings for a statement were 5 or 6, with an interquartile range equal or less than 1. Findings: A total of 333 professionals and patients participated in this eDelphi study. There was agreement that post COVID was “a set of multi-organic symptoms that persist or fluctuate after acute COVID-19 infection and are not attributable to other causes” with a minimum duration of 3 months. The highest levels of agreement were found in the most frequent symptoms and its impacts on everyday activities. Aspects related to the diagnostic process and the measurement of its severity reached a lower level of consensus. There was agreement on the need to rule out previous health problems and assess severity using validated functional scales. However, no agreement was reached on the risk factors or specific features in the pediatric population. Interpretation: This policy-based consensus study has allowed the characterization of post COVID generating collective intelligence and has contributed to an operational definition applicable in clinical practice, health services management and useful for research purposes in Spain and abroad. Agreements are consistent with existing evidence and reference institutions at European and international level.

Abstract Background Patients with heart failure with reduced ejection fraction (HFrEF) and central sleep apnea (CSA) are at a very high risk of fatal outcomes. Objective To test whether the circulating miRNome provides additional information for risk stratification on top of clinical predictors in patients with HFrEF and CSA. Methods The study included patients with HFrEF and CSA from the SERVE-HF trial. A three-step protocol was applied: microRNA (miRNA) screening (n = 20), technical validation (n = 60), and biological validation (n = 587). The primary outcome was either death from any cause, lifesaving cardiovascular intervention, or unplanned hospitalization for worsening of heart failure, whatever occurred first. MiRNA quantification was performed in plasma samples using miRNA sequencing and RT-qPCR. Results Circulating miR-133a-3p levels were inversely associated with the primary study outcome. Nonetheless, miR-133a-3p did not improve a previously established clinical prognostic model in terms of discrimination or reclassification. A customized regression tree model constructed using the Classification and Regression Tree (CART) algorithm identified eight patient subphenotypes with specific risk patterns based on clinical and molecular characteristics. MiR-133a-3p entered the regression tree defining the group at the lowest risk; patients with log(NT-proBNP) ≤ 6 pg/mL (miR-133a-3p levels above 1.5 arbitrary units). The overall predictive capacity of suffering the event was highly stable over the follow-up (from 0.735 to 0.767). Conclusions The combination of clinical information, circulating miRNAs, and decision tree learning allows the identification of specific risk subphenotypes in patients with HFrEF and CSA.

Elucidating the pathobiological mechanisms underlying post-acute pulmonary sequelae following SARS-CoV-2 infection is essential for early interventions and patient stratification. Here, we investigated the potential of microRNAs (miRNAs) as theranostic agents for pulmoprotection in critical illness survivors. Multicenter study including 172 ICU survivors. Diffusion impairment was defined as a lung-diffusing capacity for carbon monoxide (DLCO)

Abstract Background Obstructive sleep apnoea (OSA) has a high prevalence in patients with Alzheimer’s disease (AD). Both conditions have been shown to be associated with lipid dysregulation. However, the relationship between OSA severity and alterations in lipid metabolism in the brains of patients with AD has yet to be fully elucidated. In this context, we examined the cerebrospinal fluid (CSF) lipidome of patients with suspected OSA to identify potential diagnostic biomarkers and to provide insights into the pathophysiological mechanisms underlying the effect of OSA on AD. Methods The study included 91 consecutive AD patients who underwent overnight polysomnography (PSG) to diagnose severe OSA (apnoea-hypopnea index ≥ 30/h). The next morning, CSF samples were collected and analysed by liquid chromatography coupled to mass spectrometry in an LC-ESI-QTOF-MS/MS platform. Results The CSF levels of 11 lipid species were significantly different between AD patients with (N = 38) and without (N = 58) severe OSA. Five lipids (including oxidized triglyceride OxTG(57:2) and four unknown lipids) were significantly correlated with specific PSG measures of OSA severity related to sleep fragmentation and hypoxemia. Our analyses revealed a 4-lipid signature (including oxidized ceramide OxCer(40:6) and three unknown lipids) that provided an accuracy of 0.80 (95% CI: 0.71–0.89) in the detection of severe OSA. These lipids increased the discriminative power of the STOP-Bang questionnaire in terms of the area under the curve (AUC) from 0.61 (0.50–0.74) to 0.85 (0.71–0.93). Conclusions Our results reveal a CSF lipidomic fingerprint that allows the identification of AD patients with severe OSA. Our findings suggest that an increase in central nervous system lipoxidation may be the principal mechanism underlying the association between OSA and AD.

Abstract 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.

Abstract Background The identification of critically ill COVID-19 patients at risk of fatal outcomes remains a challenge. Here, we first validated candidate microRNAs (miRNAs) as biomarkers for clinical decision-making in critically ill patients. Second, we constructed a blood miRNA classifier for the early prediction of adverse outcomes in the ICU. Methods This was a multicenter, observational and retrospective/prospective study including 503 critically ill patients admitted to the ICU from 19 hospitals. qPCR assays were performed in plasma samples collected within the first 48 h upon admission. A 16-miRNA panel was designed based on recently published data from our group. Results Nine miRNAs were validated as biomarkers of all-cause in-ICU mortality in the independent cohort of critically ill patients (FDR

There is a limited understanding of the pathophysiology of postacute pulmonary sequelae in severe COVID-19. The aim of current study was to define the circulating microRNA (miRNA) profiles associated with pulmonary function and radiologic features in survivors of SARS-CoV-2-induced ARDS. The study included patients who developed ARDS secondary to SARS-CoV-2 infection (n = 167) and a group of infected patients who did not develop ARDS (n = 33). Patients were evaluated 3 months after hospital discharge. The follow-up included a complete pulmonary evaluation and chest computed tomography. Plasma miRNA profiling was performed using RT-qPCR. Random forest was used to construct miRNA signatures associated with lung diffusing capacity for carbon monoxide (DLCO) and total severity score (TSS). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were conducted. DLCO

Abstract Background Obstructive sleep apnoea (OSA) is the most frequent form of sleep-disordered breathing in patients with Alzheimer’s disease (AD). Available evidence demonstrates that both conditions are independently associated with alterations in lipid metabolism. However, it is unknown whether the expression of lipids is different between AD patients with and without severe OSA. In this context, we examined the plasma lipidome of patients with suspected OSA, aiming to identify potential diagnostic biomarkers and to provide insights into the pathophysiological mechanisms underlying the disease. Methods The study included 103 consecutive patients from the memory unit of our institution with a diagnosis of AD. The individuals were subjected to overnight polysomnography (PSG) to diagnose severe OSA (apnoea-hypopnea index ≥30/h), and blood was collected the following morning. Untargeted plasma lipidomic profiling was performed using liquid chromatography coupled with mass spectrometry. Results We identified a subset of 44 lipids (mainly phospholipids and glycerolipids) that were expressed differently between patients with AD and severe and nonsevere OSA. Among the lipids in this profile, 30 were significantly correlated with specific PSG measures of OSA severity related to sleep fragmentation and hypoxemia. Machine learning analyses revealed a 4-lipid signature (phosphatidylcholine PC(35:4), cis-8,11,14,17-eicosatetraenoic acid and two oxidized triglycerides (OxTG(58:5) and OxTG(62:12)) that provided an accuracy (95% CI) of 0.78 (0.69–0.86) in the detection of OSA. These same lipids improved the predictive power of the STOP-Bang questionnaire in terms of the area under the curve (AUC) from 0.61 (0.50–0.74) to 0.80 (0.70–0.90). Conclusion Our results show a plasma lipidomic fingerprint that allows the identification of patients with AD and severe OSA, allowing the personalized management of these individuals. The findings suggest that oxidative stress and inflammation are potential prominent mechanisms underlying the association between OSA and AD.

BackgroundThe World Health Organization’s strategy toward healthy aging fosters person-centered integrated care sustained by eHealth systems. However, there is a need for standardized frameworks or platforms accommodating and interconnecting multiple of these systems while ensuring secure, relevant, fair, trust-based data sharing and use. The H2020 project GATEKEEPER aims to implement and test an open-source, European, standard-based, interoperable, and secure framework serving broad populations of aging citizens with heterogeneous health needs. ObjectiveWe aim to describe the rationale for the selection of an optimal group of settings for the multinational large-scale piloting of the GATEKEEPER platform. MethodsThe selection of implementation sites and reference use cases (RUCs) was based on the adoption of a double stratification pyramid reflecting the overall health of target populations and the intensity of proposed interventions; the identification of a principles guiding implementation site selection; and the elaboration of guidelines for RUC selection, ensuring clinical relevance and scientific excellence while covering the whole spectrum of citizen complexities and intervention intensities. ResultsSeven European countries were selected, covering Europe’s geographical and socioeconomic heterogeneity: Cyprus, Germany, Greece, Italy, Poland, Spain, and the United Kingdom. These were complemented by the following 3 Asian pilots: Hong Kong, Singapore, and Taiwan. Implementation sites consisted of local ecosystems, including health care organizations and partners from industry, civil society, academia, and government, prioritizing the highly rated European Innovation Partnership on Active and Healthy Aging reference sites. RUCs covered the whole spectrum of chronic diseases, citizen complexities, and intervention intensities while privileging clinical relevance and scientific rigor. These included lifestyle-related early detection and interventions, using artificial intelligence–based digital coaches to promote healthy lifestyle and delay the onset or worsening of chronic diseases in healthy citizens; chronic obstructive pulmonary disease and heart failure decompensations management, proposing integrated care management based on advanced wearable monitoring and machine learning (ML) to predict decompensations; management of glycemic status in diabetes mellitus, based on beat to beat monitoring and short-term ML-based prediction of glycemic dynamics; treatment decision support systems for Parkinson disease, continuously monitoring motor and nonmotor complications to trigger enhanced treatment strategies; primary and secondary stroke prevention, using a coaching app and educational simulations with virtual and augmented reality; management of multimorbid older patients or patients with cancer, exploring novel chronic care models based on digital coaching, and advanced monitoring and ML; high blood pressure management, with ML-based predictions based on different intensities of monitoring through self-managed apps; and COVID-19 management, with integrated management tools limiting physical contact among actors. ConclusionsThis paper provides a methodology for selecting adequate settings for the large-scale piloting of eHealth frameworks and exemplifies with the decisions taken in GATEKEEPER the current views of the WHO and European Commission while moving forward toward a European Data Space.

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.

Abstract Background Hypoxia can reduce the levels of soluble receptor for advanced glycation end-products (sRAGE), a new anti-inflammatory biomarker of COPD. We assessed sRAGE in patients with hypoxia-related diseases such as COPD, OSA and OSA-COPD overlap. Methods Plasma levels of sRAGE were measured in 317 subjects at baseline (57 heathy nonsmokers [HNS], 84 healthy smokers [HS], 79 OSA, 62 COPD and 35 OSA-COPD overlap patients) and in 294 subjects after one year of follow-up (50 HNS, 74 HS, 77 OSA, 60 COPD and 33 overlap). Results After adjusting for age, sex, smoking status and body mass index, sRAGE levels showed a reduction in OSA (− 12.5%, p = 0.005), COPD (− 14.8%, p

Background: Obstructive sleep apnea (OSA) is associated with a recurrent cardiovascular event (CVE) risk in patients with a first acute coronary syndrome (ACS). However, the pathological pathways by which OSA promotes this deleterious role are unknown. We aim to explore the proteomic profile associated with OSA that promote the recurrent CVE risk in severe OSA patients with ACS without previous cardiovascular diseases. Methods: This post-hoc analysis from the ISAACC study (NCT01335087) included 86 patients admitted for ACS. Patients underwent respiratory polygraphy for the first 24–72 h to OSA diagnosis. We analyzed of 276 cardiovascular and inflammatory related proteins in baseline fasting plasma samples using proximity expression assay technology (Olink®, Sweden). Protein levels were compared between severe OSA patients with/without recurrent CVEs during follow-up. Random forest was conducted to select relevant proteins and generate a predictive model of recurrent CVE. Results: We included 86 patients (median age: 61 years, median BMI: 29.4 kg/m2 and 86 % males) admitted for ACS with severe OSA (56 without recurrent CVE/30 with recurrent CVE). The plasma levels of 38 proteins were differentially expressed between groups. Additionally, 12 proteins had a significant association with respiratory polygraphy parameters. Three proteins discriminate with an AUC of 0.81 (95 % CI of 0.71–0.9) between severe OSA patients with and without recurrent CVE. These proteins were implicated in cell proliferation, communication and apoptosis, and regulation/response to the inflammatory and immune systems. Conclusion: In ACS patients with severe OSA, a proteomic profile was associated with recurrent CVEs. This proteomic profile was correlated with specific OSA parameters from respiratory polygraphy. Proteomic profiling may provide an new direction for patient risk stratification and clinical management.

Abstract 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.

Background: Up to 80% of patients surviving acute respiratory distress syndrome (ARDS) secondary to SARS-CoV-2 infection present persistent anomalies in pulmonary function after hospital discharge. There is a limited understanding of the mechanistic pathways linked to post-acute pulmonary sequelae. Aim: To identify the molecular underpinnings associated with severe lung diffusion involvement in survivors of SARS-CoV-2-induced ARDS. Methods: Survivors attended to a complete pulmonary evaluation 3 months after hospital discharge. RNA sequencing (RNA-seq) was performed using Illumina technology in whole-blood samples from 50 patients with moderate to severe diffusion impairment (DLCO

Abstract Background Mortality due to COVID-19 is high, especially in patients requiring mechanical ventilation. The purpose of the study is to investigate associations between mortality and variables measured during the first three days of mechanical ventilation in patients with COVID-19 intubated at ICU admission. Methods Multicenter, observational, cohort study includes consecutive patients with COVID-19 admitted to 44 Spanish ICUs between February 25 and July 31, 2020, who required intubation at ICU admission and mechanical ventilation for more than three days. We collected demographic and clinical data prior to admission; information about clinical evolution at days 1 and 3 of mechanical ventilation; and outcomes. Results Of the 2,095 patients with COVID-19 admitted to the ICU, 1,118 (53.3%) were intubated at day 1 and remained under mechanical ventilation at day three. From days 1 to 3, PaO2/FiO2 increased from 115.6 [80.0–171.2] to 180.0 [135.4–227.9] mmHg and the ventilatory ratio from 1.73 [1.33–2.25] to 1.96 [1.61–2.40]. In-hospital mortality was 38.7%. A higher increase between ICU admission and day 3 in the ventilatory ratio (OR 1.04 [CI 1.01–1.07], p = 0.030) and creatinine levels (OR 1.05 [CI 1.01–1.09], p = 0.005) and a lower increase in platelet counts (OR 0.96 [CI 0.93–1.00], p = 0.037) were independently associated with a higher risk of death. No association between mortality and the PaO2/FiO2 variation was observed (OR 0.99 [CI 0.95 to 1.02], p = 0.47). Conclusions Higher ventilatory ratio and its increase at day 3 is associated with mortality in patients with COVID-19 receiving mechanical ventilation at ICU admission. No association was found in the PaO2/FiO2 variation.

Abstract Background Alterations in circadian rhythms are present in the presymptomatic stage of Alzheimer’s disease (AD), possibly contributing to its pathogenesis. However, it is unknown whether such alterations are associated with worse outcomes once individuals are diagnosed with symptomatic disease. We aimed to evaluate the association between the circadian rest-activity pattern and AD-related features in patients with mild-moderate AD. Methods We assessed the circadian rest-activity pattern of consecutive patients with mild-moderate AD through actigraphy for 14 days. Cerebrospinal fluid was obtained to determine the levels of important pathological markers including amyloid-beta protein (Aβ42), phosphorylated tau (P-tau), total tau (T-tau), and neurofilament light (NF-L). Neuropsychological evaluation was conducted at the beginning of the study and after 12 months of follow-up. Linear regression models were performed considering the global population and Aβ42+ patients only. Results The cohort included 100 patients with mild-moderate AD. The median age [p25;p75] was 76.0 [73.0;80.0] years and 63.0% were female. Older age (effect size [SE] of 0.324 [0.096]; p = 0.001) and male sex (0.780 [0.193]; p = 0.001) were associated with increased fragmentation and decreased synchronization of the rhythm, respectively. After adjusting for age, sex, and season of the year, increased levels of T-tau (effect size [95% CI] of 0.343 [0.139 to 0.547]; p = 0.001) and NF-L (0.444 [0.212 to 0.676]; p = 0.001) were associated with a higher amplitude of the rest-activity rhythm. Increased fragmentation of the rhythm at baseline was associated with greater cognitive decline after one year of follow-up independent of age, sex, T-tau/Aβ42 ratio, educational level, and season of the year (− 0.715 [− 1.272 to − 0.157]; p = 0.013). Similar findings were obtained considering only the Aβ42+ patients. Conclusions Our results suggest a potential role of the circadian rest-activity pattern in predicting the cognitive decline of patients with mild-moderate AD. Further studies are warranted to confirm these findings and to elucidate whether there is causality among the observed associations.

IntroductionBronchial aspirates (BAS) obtained during invasive mechanical ventilation (IMV) constitutes a useful tool for molecular phenotyping and decision making.AimTo identify the proteomic determinants associated with disease pathogenesis, all-cause mortality and respiratory sequelae in BAS samples from critically ill patients with SARS-CoV-2-induced ARDSMethodsMulticenter study including 74 critically ill patients with COVID-19 and non-COVID-19 ARDS. BAS were obtained by bronchoaspiration after IMV initiation. Three hundred sixty-four proteins were quantified using proximity extension assay (PEA) technology. Random forest models were used to assess predictor importance.ResultsAfter adjusting for confounding factors, CST5, NADK, SRPK2 and TGF-α were differentially detected in COVID-19 and non-COVID-19 patients. In random forest models for COVID-19, CST5, DPP7, NADK, KYAT1 and TYMP showed the highest variable importance. In COVID-19 patients, reduced levels of ENTPD2 and PTN were observed in nonsurvivors of ICU stay, even after adjustment. AGR2, NQO2, IL-1α, OSM and TRAIL showed the strongest associations with in-ICU mortality and were used to construct a protein-based prediction model. Kaplan-Meier curves revealed a clear separation in mortality risk between subgroups of PTN, ENTPD2 and the prediction model. Cox regression models supported these findings. In survivors, the levels of FCRL1, NTF4 and THOP1 in BAS samples obtained during the ICU stay correlated with lung function (i.e., DLCO levels) 3 months after hospital discharge. Similarly, Flt3L and THOP1 levels were correlated with radiological features (i.e., TSS). These proteins are expressed in immune and nonimmune lung cells. Poor host response to viral infectivity and an inappropriate reparative mechanism seem to be linked with the pathogenesis of the disease and fatal outcomes, respectively.ConclusionBAS proteomics identified novel factors associated with the pathology of SARS-CoV-2-induced ARDS and its adverse outcomes. BAS-based protein testing emerges as a novel tool for risk assessment in the ICU.

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 (

Summary: Background: The clinical heterogeneity of COVID-19 suggests the existence of different phenotypes with prognostic implications. We aimed to analyze comorbidity patterns in critically ill COVID-19 patients and assess their impact on in-hospital outcomes, response to treatment and sequelae. Methods: Multicenter prospective/retrospective observational study in intensive care units of 55 Spanish hospitals. 5866 PCR-confirmed COVID-19 patients had comorbidities recorded at hospital admission; clinical and biological parameters, in-hospital procedures and complications throughout the stay; and, clinical complications, persistent symptoms and sequelae at 3 and 6 months. Findings: Latent class analysis identified 3 phenotypes using training and test subcohorts: low-morbidity (n=3385; 58%), younger and with few comorbidities; high-morbidity (n=2074; 35%), with high comorbid burden; and renal-morbidity (n=407; 7%), with chronic kidney disease (CKD), high comorbidity burden and the worst oxygenation profile. Renal-morbidity and high-morbidity had more in-hospital complications and higher mortality risk than low-morbidity (adjusted HR (95% CI): 1.57 (1.34-1.84) and 1.16 (1.05-1.28), respectively). Corticosteroids, but not tocilizumab, were associated with lower mortality risk (HR (95% CI) 0.76 (0.63-0.93)), especially in renal-morbidity and high-morbidity. Renal-morbidity and high-morbidity showed the worst lung function throughout the follow-up, with renal-morbidity having the highest risk of infectious complications (6%), emergency visits (29%) or hospital readmissions (14%) at 6 months (p

Obstructive sleep apnea (OSA) has been identified as a cardiovascular (CV) risk factor. The potential of OSA promoting the synthesis of CV biomarkers in acute coronary syndrome (ACS) is unknown. Ischemia-modified albumin (IMA) has been identified as a specific CV biomarker. The aim of this study was to evaluate the role of IMA as a potential biomarker for determining the impact of OSA in ACS patients. A total of 925 patients (15.5% women, age: 59 years, body mass index: 28.8 kg/m2) from the ISAACC study (NCT01335087) were included. During hospitalization for ACS, a sleep study for OSA diagnosis was performed and blood samples extraction for IMA determination were obtained. IMA values were significantly higher in severe OSA (median (IQR), 33.7 (17.2–60.3) U/L) and moderate (32.8 (16.9–58.8) U/L) than in mild/no OSA (27.7 (11.8–48.6) U/L) (p = 0.002). IMA levels were very weakly related to apnea–hypopnea index (AHI) as well as hospital and intensive care unit stay, although they only maintained a significant relationship with days of hospital stay after adjusting for sex, age and BMI (ß = 0.410, p = 0.013). The results of the present study would suggest a potentially weaker role of OSA in the synthesis of the CV risk biomarker IMA in patients with ACS than in primary prevention.

IntroductionObstructive sleep apnea (OSA) severity is based on the apnea-hypopnea index (AHI). The AHI is a simplistic measure that is inadequate for capturing disease severity and its consequences in cardiovascular diseases (CVDs). Deleterious effects of OSA have been suggested to influence the prognosis of specific endotypes of patients with acute coronary syndrome (ACS). We aim to identify respiratory polygraphy (RP) patterns that contribute to identifying the risk of recurrent cardiovascular events in patients with ACS.MethodsPost hoc analysis of the ISAACC study, including 723 patients admitted for a first ACS (NCT01335087) in which RP was performed. To identify specific RP patterns, a principal component analysis (PCA) was performed using six RP parameters: AHI, oxygen desaturation index, mean and minimum oxygen saturation (SaO2), average duration of events and percentage of time with SaO2 < 90%. An independent HypnoLaus population-based cohort was used to validate the RP components.ResultsFrom the ISAACC study, PCA showed that two RP components accounted for 70% of the variance in the RP data. These components were validated in the HypnoLaus cohort, with two similar RP components that explained 71.3% of the variance in the RP data. The first component (component 1) was mainly characterized by low mean SaO2 and obstructive respiratory events with severe desaturation, and the second component (component 2) was characterized by high mean SaO2 and long-duration obstructive respiratory events without severe desaturation. In the ISAACC cohort, component 2 was associated with an increased risk of recurrent cardiovascular events in the third tertile with an adjusted hazard ratio (95% CI) of 2.44 (1.07 to 5.56; p-value = 0.03) compared to first tertile. For component 1, no significant association was found for the risk of recurrent cardiovascular events.ConclusionA RP component, mainly characterized by intermittent hypoxemia, is associated with a high risk of recurrent cardiovascular events in patients without previous CVD who have suffered a first ACS.

ObjectiveTo determine the association between Obstructive Sleep Apnea (OSA) with long-term symptoms and inflammatory cytokines, exploring the changes between 4-months and 1-year after COVID-19 infection.MethodsWe conducted an observational, prospective cohort study, including patients ≥18 years old with confirmed diagnosis of COVID-19 between April to July 2020. All participants underwent two clinical follow-up visits, the first at 4-months (Visit 1) and the second at 1 year, after SARS-CoV-2 infection (Visit 2). Plasma glucose, total cholesterol, HDL, and triglycerides. Regarding pulmonary function, spirometry and lung diffusion capacity tests were assessed. For mental and neurocognitive evaluation, a short-form (SF-12), Beck depression and Hospital-Anxiety depression questionnaires were conducted at both time-points, whereas the Montreal Cognitive assessment was conducted during the second follow-up. Regarding to sleep evaluation, Epworth Sleepiness Scale, Insomnia Severity index and STOP-BANG questionnaire were conducted. Additionally, a home sleep apnea test and 7-day wrist actigraphy were performed in all participants. Inflammatory cytokines were measured using an inflammatory cytokine bead array kit. p-values < 0.05 were considered statistically significant and statistical analyses were performed using R software.ResultsA total of 60 patients were included in the first follow-up, from which 57 completed the second follow-up. The mean age was 46.4 years-old (SD ± 13.1) and 53.3% were male. 30% of cases reported mild COVID-19 infection, 28.3% with moderate illness, and 41.6% with severe illness. Moreover, 56.6% of them were admitted to the ICU. Regarding to metabolic values, the OSA group showed higher values of insulin resistance (IR) (27%), systolic blood pressure (SBP) 135.2 (±19.1), dyslipidemia (67.5%), total cholesterol 202.1 (±60.5), triglycerides 176.1 (±119.0) and HOMA-IR 9.0 (±18.8) in comparison with the non-OSA group. 1 year after COVID-19 infection, DLCO test remains abnormal in OSA patients (25% OSA vs. 3.6% non-OSA, p = 0.02). Finally, those participants with OSA who develop ARDS reported an adjusted OR 20.4 (95%-CI, 1.04–504) risk of neurocognitive impairment.DiscussionAmong patients with previous COVID-19, OSA impact the development of incident glycemic, neurocognitive impairment, and abnormal functional pulmonary changes that persist up to 1 year since acute phase.